Report on Development of the Master’s Program ‘Complex Integrated System Design’ Submitted To: World Bank Project Team Sandra Sargent ssargent@worldbank.org Juan Navas-Sabater jnavassabater@worldbank.org Submitted By: JSC “Civitta BY” Daniel Krutzinna, Team Lead daniel@civitta.com September 12, 2018 List of abbreviations ADSL Asymmetric Digital Subscriber Line BA Business Analysis BSU Belarusian State University BSUIR Belarusian State University of Informatics and Radioelectronics CASE Computer-Aided Software Engineering DBMS Database Management System ERP Enterprise Resource Planning HDMI High-Definition Multimedia Interface HR Human Resources IBA IBA Group is one of the largest IT service providers in Eastern Europe ICT Information and Computer Technology IT Information Technology ITMO Information Technologies, Mechanics and Optics University LMS Learning Management System LP Linear Programming MCSE Microsoft Certified Solutions Expert MFTI Moscow Institute of Physics and Technology NAS National Academy of Sciences PMI Project Management Institute UML Unified Modeling Language Table of Contents 1. INTRODUCTION ................................................................................................................................ 1 2. GENERAL PROVISIONS OF THE ‘COMPLEX INTEGRATED SYSTEM DESIGN’ MASTER’S TRAINING PROGRAM ................ 2 2.1. Relevance..............................................................................................................................................2 2.2. Objective...............................................................................................................................................3 2.3. Differences between the proposed master’s training program and the existing ones in Belarus.......3 3. PRINCIPLES OF MASTER’S TRAINING DESIGN ............................................................................................ 5 3.1. Focus on practice ..................................................................................................................................5 3.2. Soft skills ...............................................................................................................................................6 3.3. Cross-discipline knowledge ..................................................................................................................6 3.4. Use of open education systems and international certification ..........................................................6 3.5. International cooperation ....................................................................................................................7 3.6. Wide range of potential applicants ......................................................................................................7 3.7. Principles of staff recruiting..................................................................................................................8 3.8. Feasibility in Belarus .............................................................................................................................9 4. CURRICULА AND PROGRAMS ............................................................................................................. 11 4.1. Professional competences of the master .......................................................................................... 11 4.2. Evolution of the curriculum ............................................................................................................... 11 4.3. Educational standard and programs of core disciplines ................................................................... 13 4.4. Organization of educational process ................................................................................................. 13 5. REQUIRED TECHNICAL INFRASTRUCTURE ............................................................................................... 14 6. STEPS TAKEN TO LAUNCH THE MASTER’S TRAINING PROGRAM ................................................................... 16 6.1. Development and approval of methodical academic documentation.............................................. 16 6.2. Website for master’s training and its presence in social networks .................................................. 16 6.3. Recruitment of teaching staff ............................................................................................................ 17 6.4. Enrollment of master’s students and the beginning of training ....................................................... 17 6.5. Organization of training..................................................................................................................... 17 7. COOPERATION WITH IT COMPANIES AND EMPLOYMENT OF MASTER’S GRADUATES ......................................... 19 8. FEEDBACK FROM MASTER’S STUDENTS: SURVEY RESULTS ......................................................................... 20 9. PROMOTION AND DEVELOPMENT ....................................................................................................... 24 ANNEX 1. PROGRAM FOR DISCIPLINES OF SPECIAL TRAINING ............................................................................ 26 1. Programs for disciplines of the governmental component ..................................................................... 26 1.1. Applied theory of information............................................................................................................ 26 1.2. Software design and development technologies ............................................................................... 27 1.3. Architectures of computer systems ................................................................................................... 28 1.4. Integrated security of information technologies and systems .......................................................... 29 1.5. Theory of complex systems and system analysis ............................................................................... 30 1.6. Methodologies and technologies of conceptual design .................................................................... 31 2. Programs for disciplines of University component .................................................................................. 32 2.1. Intelligent systems and machine learning .......................................................................................... 32 2.2. Applied statistics and big data analysis .............................................................................................. 33 2.3. Project management .......................................................................................................................... 34 2.4. Software-oriented data storage systems and modern DBMS............................................................ 35 2.5. Technologies and templates for information system integration ..................................................... 36 2.6. Data structures and algorithms .......................................................................................................... 37 2.7. Applied methods of optimal design ................................................................................................... 38 2.8. Object-oriented analysis and design .................................................................................................. 39 2.9. Discrete mathematics......................................................................................................................... 40 2.10. Cloud technologies ........................................................................................................................... 41 2.11. Open source software platforms ..................................................................................................... 42 2.12. Deep learning ................................................................................................................................... 43 2.13. Information technology and IТ risk management ............................................................................ 44 2.14. User behavior and interaction design .............................................................................................. 45 2.15. Business analysis basics in software development .......................................................................... 46 2.16. Internet of things.............................................................................................................................. 47 ANNEX 2. EDUCATIONAL STANDARDS OF HIGHER EDUCATION INSTITUTIONS. MAJOR 1-31 81 14 COMPLEX INTEGRATED SYSTEM DESIGN .................................................................................................................................... 49 1. Application ............................................................................................................................................... 49 2. Legal references ....................................................................................................................................... 49 3. General terms and definitions ................................................................................................................. 49 4. General provisions ................................................................................................................................... 50 4.1. General description of the major ....................................................................................................... 50 4.2. Educational requirements for applicants of the master’s postgraduate ........................................... 50 4.3. Master’s postgraduate forms of training ........................................................................................... 51 4.4. Duration of master’s postgraduate training....................................................................................... 51 5. Professional activities of the master ........................................................................................................ 51 5.1. Area of the professional activities of the master ............................................................................... 51 5.2. Objects of the professional activities of the master .......................................................................... 51 5.3. Types of the professional activities of the master ............................................................................. 52 5.4. Tasks of the professional activities of the master .............................................................................. 52 5.5. Options for the master to continue training ...................................................................................... 53 6. Requirements for the master’s competence ........................................................................................... 53 6.1. Structure of the master’s competences ............................................................................................. 53 6.2. Requirements for academic competences of the master .................................................................. 53 6.3. Requirements for social and personal competences of the master .................................................. 53 6.4. Requirements for the master’s professional competences ............................................................... 54 7. Requirements for the training program and content of the academic training documentation ............ 54 7.1. Structure of the academic training documentation ........................................................................... 54 7.2. General requirements for the development of academic training documentation .......................... 55 7.3. Requirements for the schedule of the training process..................................................................... 55 7.4. Requirements for the standard curriculum structure of the major ................................................... 55 7.5. Requirements for the development of a master’s student’s individual working plan ...................... 57 7.6. Requirements for a compulsory minimum of training programs content and competences in academic disciplines .................................................................................................................................. 57 7.7. Requirements for the research work contents of a master’s student ............................................... 59 7.8. Requirements for internship contents and organization ................................................................... 59 8. Requirements for organizing educational process .................................................................................. 59 8.1. Requirements for educational process staff ensuring ....................................................................... 59 8.2. Requirements for ensuring educational process resources ............................................................... 60 8.3. Requirements for ensuring scientific and methodical activities of the educational process ............ 60 8.4. Requirements for individual work organization ................................................................................. 60 8.5. Requirements for ideological and pedagogical work activity ............................................................ 60 8.6. General requirements for quality control of training and competence diagnostics means .............. 60 9. Requirements for the final certification .................................................................................................. 61 9.1. General requirements ........................................................................................................................ 61 9.2. Requirements for the master’s thesis ................................................................................................ 61 References ................................................................................................................................................... 61 ANNEX 3. CURRICULUM.......................................................................................................................... 62 1. Introduction At the current stage of information society development, we witness and participate in the digital transformation of the state, economy, and society. Unlike informatization, digital transformation involves conversion of key business processes into digital formats. Enterprises, branches of economy, and regions become objects of digital transformation. Modern systems of e-government, online banks, online stores, and open education serve as examples of digital transformation. The President of the Republic of Belarus, A. G. Lukashenko, has set “an ambitious task ― to turn Belarus into an information technology (IT) country.” Processes of digital transformation, design, development, and implementation of complex systems set new requirements for the education of those who provide such processes. Education in the sphere of information technologies is meant for both experts in digital system design and development and heads of the enterprises, branches, and regions organizing the transfer from traditional business processes to new ones based on digital formats and technologies. 1 2. General provisions of the ‘Complex Integrated System Design’ master’s training program 2.1. Relevance An intense use of information and computer technology (ICT) has become the strategic direction to achieve economic competitiveness in the world. At the present stage of development of the information society, a new digital economy is developed based on ICT, and its development strategies are cultivated by the governments the world over. The Government of the Republic of Belarus has ratified the Informatization Development Strategy in the Republic of Belarus for 2016–2022 and the State Program on Digital Economy and Information Society Development for 2016– 2020. The program is aimed at broad transformations of the leading sectors of the economy and raising their competitiveness. A large-scale introduction of horizontal applications for digital transformation of the government and vertical applications focused on specific industries of the economy are expected. Developing a digital economy involves creating new complex systems in spheres of public administration, industrial production, power, logistics, trade, health care, and education. Therefore, the state program recommends that the design and development of the complex integrated systems should have the following: • The Belarussian integrated service payment system • The national open data portal • A national segment of the Eurasian Economic Union integrated information system • The National Paperless Trade System of Belarus • Information and education to develop personalities adapted to living in the information society • The state control system of the digital signature open keys verification in Belarus These and many other complex systems (not only proper information systems) differ to a vast extent in integration, both internal (at the stage of separate subsystems) and external, with other systems, including those providing integration into the system of international division of labor and the world markets. The need for complex systems design and development exists not only in the domestic market of Belarus but also in foreign markets that the enterprises—resident companies of the Belarusian Hi-Tech Park—are substantially focused on. In complex, expensive systems development, the conceptual design stage, the initial phase of the systems’ life cycle, is particularly important. This step substantially defines the efficiency of expenses and the effectiveness of development. However, there is lack of training for specialists in complex integrated system conceptual design in Belarus. The few professionals available in the labor market are practitioners who have received the corresponding competence through long-term work and self-education. The number of such experts is rather small, and their capabilities on the complex integrated system design problems are often limited owing to lack of fundamental knowledge. According to research conducted by Civitta, the architects are experts with the highest demand in the Belarussian IT market. As figure 1 shows, all categories of respondents―representatives of IТ companies, students, and teachers―support this point of view. 2 Figure 1: Results of the survey on the most demanded IТ positions in Belarus Source: Civitta survey. 2.2. Objective The primary goal of the ‘Complex Integrated System Design’ major is to satisfy the requests of organizations of various ownership forms for training of professionals with fundamental knowledge in system analysis and complex integrated system conceptual design. However, the current and future requirements of the national labor market of Belarus are also considered. Moreover, the master’s training is a pilot project for the education system in Belarus to try out the principles and methodology of the master’s studies oriented toward practice and flexible adaptation to the demands of the labor market. 2.3. Differences between the proposed master’s training program and the existing ones in Belarus The distinguishing elements of the master’s training are as follows: • Content. There is no master’s training on system conceptual design in Belarus. • Focus on practice. All the stages of the master’s training are practice oriented (see section 3.1 for more details). • Flexibility. In reality, the course curriculum is framed based on the results of knowledge gap diagnostics and the background of master’s students. For example, when the ‘applied theory of information’ discipline was mastered, knowledge gaps in probability theory and information transfer in computer networks were revealed. These gaps were addressed through lectures and independent work of master’s students. 3 • A form of educational process organization. Together with entrance lectures, workshops, and practical classes, master’s students independently study the academic content and learn to write and present reports. The program includes practical work together with tasks as small projects that master’s students undertake individually or in groups. Examples of such projects are provided in the next section. • Sequential mastering of educational modules. Exams are held after the module is finished and credits awarded. • The possibility of using open education systems. Optional courses can be mastered in the open training system (see section 3.4). 4 3. Principles of master’s training design 3.1. Focus on practice According to the survey of IT experts, teachers, and students about the importance of practical activities in a master’s program, 63 percent to 68 percent of the total training period should be dedicated to practical exercises. To satisfy this requirement, the curriculum of the master’s program includes (see Figure 2) • One-third of the duration on classroom work (300 hours out of 894); • About 900 hours of independent work on disciplines (out of 3,038); • 960 hours of practice-oriented scientific research; and • 810 hours of internship including writing a thesis based on the results of practical activities as part of a real project on complex integrated system development. A master’s student takes 2,970 out of 4,482 total periods (about 66 percent) to perform the abovementioned practical activities provided by the curriculum. The classroom work for master’s students (lectures, workshops, consultations on practice) takes 894 periods, that is, less than 20 percent of the total periods. Thus, different forms of practical activities of the master’s student are as follows: First, each educational module includes practical tasks. These tasks can be performed as part of independent work both individually and in small groups. About one-third of classroom work is dedicated to consulting on completion of practical tasks. The results are heard at workshops and are discussed in the network community of masters and teachers. Moreover, practical activities usually include mini-projects— performed individually or in groups. Examples of such projects for the ‘applied theory of information’ course include (a) developing a concept of the backup data center for the national library and (b) developing a concept of an Internet-broadcasting system for a large university. Figure 2: Place of practical activities in the master’s training curriculum Source: BSU. Second, from the first year of training, the curriculum presupposes several academic periods for practice- oriented scientific research. This activity is about real project fulfillment. The results of it are heard at the ongoing scientific workshop. Example topics for practice-oriented scientific research are design of cloud 5 ERP system for retail enterprises, integrated system security for private information space, and development of a concept project for the paperless trade system. Finally, the fourth semester is entirely dedicated to practical training and writing of the master’s thesis. The master’s students will have their internship at the enterprises of the BSU cluster. Those who already work in IT can do a course at their organization (if possible). Internship involves designing a real complex integrated system in one of the subject areas. The results of this internship will form the basis of the master’s thesis. In the third semester, the master’s students will be offered some disciplines as optional courses, for example, banking and insurance information systems, geographic information systems, the Internet of things, e-economy, and e-commerce, to prepare for the internship. 3.2. Soft skills The master’s students obtain soft skills—ability for team cooperation—in several ways. First, they develop the skills while studying disciplines such as project management, document and presentation development, personnel management, and communication technologies. Second, they gain communication skills through teamwork for practical tasks and projects and during reporting the results of task completion on each discipline. 3.3. Cross-discipline knowledge To obtain such knowledge, there is a separate unit (module) of optional subjects for master’s students, including public administration and e-government, bank and insurance systems, e-economy, and e- commerce. 3.4. Use of open education systems and international certification For some modules including optional courses (‘mathematics and informatics’, ‘program engineering’, and so on), the certificates obtained in the systems of open education, such as Coursera, openedu.ru, and so on, will be credited to the master’s students. There are recommended courses and courses chosen by master’s students themselves. For example, the recommended courses in the ‘mathematics and informatics’ unit are as follows: In the openedu.ru Russian national system of open education: • Graph theory (Moscow Institute of Physics and Technology) • Coding theory (Moscow Institute of Physics and Technology) • Methods and algorithms of the graph theory (Information Technologies, Mechanics and Optics University) In the Coursera system: • Data structure and algorithms (University of California, San Diego) • Discrete mathematics (University of Shanghai) The possibility of passing examinations for international certificates following the results of studying separate modules is significant. At present, the options for international certification for master’s students (Scrum Alliance, PMI, Microsoft MCSE, and so on) following the results of studying separate modules are under investigation. Such a possibility (to obtain the Scrum Alliance certificate) has already been fulfilled in the first semester during the ‘project management’ discipline training. 6 Figure 3: Examples of open education systems Source: BSU, Civitta analysis. 3.5. International cooperation Collaboration with the foreign universities and training centers is of particular interest. Exchange of teachers can be the main direction of such cooperation, followed by students’ internships abroad. At present, the issue of cooperation in various directions with the University of Trento (Italy) and the Technical University of Mittweida (Germany) is being handled. Joint diplomas with foreign universities can become an attractive course of action in this regard. However, the interest for such cooperation in the sphere of ICT is only moderate as the experience of BSU Faculty of Applied Mathematics and Computer Science shows. Figure 4: Universities that are potential partners of the master’s program Source: BSU, Civitta analysis. 3.6. Wide range of potential applicants The potential applicants for the master’s training are as follows: • Those working in business analysis (BA), design and development of information, communication, and other systems • Senior and middle management-level professionals who manage design, development, and deployment of large systems in various branches of economy • Entrepreneurs It was decided to widen, to the extent possible, the list of majors that allow entering the master’s training because people working in IT in Belarus might have majors that vary greatly. The majority of such applicants underwent additional training through various courses. As a result, the level of basic education of those who apply for master’s training was established along with subjects as follows: 7 • 25 Economy • 27 Economy and production organization • 38 Appliances • 39 Radio-electronic equipment • 40 Informatics and computer equipment • 41 Equipment components • 43 Power • 45 Communications • 53 Automation • 55 Intelligent systems • 58 Ergonomics • 98 Information security Groups of subjects: • 02 05 Teaching of physical and mathematical disciplines • 26 02 Business management • 26 03 Information resources management • 26 04 Innovative processes management • 31 03 Mathematical sciences • 95 02 Military and engineering activity Those graduating with a bachelor’s degree in other majors are also eligible for entry based on the results of supplementary examinations on academic disciplines; their list is created by a higher education institution based on the guidance of the academic association on training in natural sciences. Those who have a bachelor’s diploma can join the master’s training on successfully passing the entrance examination. The entrance examination has been developed according to the current university requirements. At first sight, it may seem too difficult, but the applicants are allowed to use open Internet sources to answer the questions. In fact, the examination committee was formed to estimate the abilities of applicants to evaluate the question quickly, to refer the content of open sources critically, and to interpret it adequately using the corresponding terminology correctly. 3.7. Principles of staff recruiting The analysis of different categories of IT professors, teachers, and practical specialists available allows selecting the following types of teachers for the master’s training. 1. Professors and teachers of the leading Belarussian universities who train IT specialists (especially BSU and Belarusian State University of Informatics and Radioelectronics [BSUIR]). Unfortunately, considering the personnel capacity of these universities, no more than 20–25 percent of master’s courses can be covered by these resources. 2. Those who graduated from the IT departments of leading universities in Belarus (applied mathematics and informatics, radio physics, and computer technologies of BSU, BSUIR, and so on), who usually have academic degrees and ranks, work in IT companies in Belarus and abroad, and combine work with teaching activities or have experience of teaching. They can cover up to 60 percent of courses. 8 3. The foreign teachers invited to Minsk or delivering remote classes, who can cover 15–20 percent of courses. The quality of teaching should always be the center of attention. Thus, continuous feedback is needed from both students and employers capable of assessing the graduates’ training level; specific guidelines are necessary for this purpose. Feedback from students will be gathered through surveys after each discipline and the whole program are completed. Besides, a database of graduates will be created, and repeated surveys will be organized at the end of the first and third years of master’s training completion. The surveys will be focused on the career prospects of the master’s graduates, their assessment of the impact of training on their further advancement, and how the master’s training can be included in their continuous development. Feedback from employers will be gathered through surveys, meetings of heads of IT companies, and teachers. It seems useful to invite potential employers to the meetings with master’s students. The first such meeting was organized in October 2017, with V. I. Dravitsa, head of the Identification System Center of National Academy of Science (NAS) of Belarus. Requirements for teachers: • Master’s degree, PhD, or doctorate • Teaching experience not less than five years • Ongoing practical activities in IT • Experience in modern technologies of distance, ‘flipped’, social education, and so on • Communicative skills and flexibility 3.8. Feasibility in Belarus Implementing the master’s program requires resolving the following issues: A. Regulated term, amount, and forms of training; strict requirements for the form and content of methodical academic documentation These are regulated by the Code on Education of the Republic of Belarus1 and by legal acts of the Ministry of Education of the Republic of Belarus.2 These rules do not allow using new, undefined forms of training. They restrict the ability to change the ratio of mandatory and optional disciplines for the master’s students and regulate the amount of internship and independent work, practical and research activities, and so on. This problem was partially solved through negotiation with the Ministry of Education on the program as an innovative pilot project. B. Complex and long procedure for opening major training programs There are a number of administrative procedures: development of justification, obtaining the consent of the university’s Educational Methodical Council and the Educational Methodical Association of the Ministry of Education, assessment of the educational methodical documentation draft at the Republic Institute of Higher School, including majors into the National Classifier, obtaining permission to launch new training programs in education institutions, repeated examination at the Republic Institute of Higher School, approval of the standard curriculum and the educational standard by the Ministry of Education, approval of the curriculum based on the standard curriculum by the university rector, approval of training programs under the established sample, and including the major program into the license for implementation of educational activity by the Ministry of Education. After the preparation begins, the Ministry of Education certifies the major. In such cases, the launch of a major program usually takes not less than one year. 1 http://www.pravo.by/document/?guid=3871&p0=hk1100243. 2 http://www.nihe.bsu.by/index.php/ru/norm-doc. 9 This issue was solved by the individual work of the master’s training developers together with the BSU leaders and the Ministry of Education. C. The problem of staff recruiting The compensation for higher education teachers in Belarus regulated by the state does not allow employing qualified specialists on regular terms. For example, the period payment to a PhD teacher amounts to less than €2 for a lecture. A considerable number of teachers ages 28–33 years are leaving teaching positions, and experts working in real business are not interested in this work. The issue of compensation for teachers was solved by contracting them for the full life cycle of teaching the discipline―from a research of international and domestic experience of teaching similar disciplines, development and approval of the training program, and development of a methodical educational complex, to teaching and holding examinations and awarding credits. Compensation for this work amounts to €1,500–2,000 per discipline with an average academic load of 50 hours. Thus, it is essential to resolve these issues during project implementation, often by finding compromises. 10 4. Curriculа and programs 4.1. Professional competences of the master Curricula and programs were developed according to the following professional competences that the master’s graduate shall possess: Innovative. To carry out search, systematization, and analysis of information on perspective directions, technologies, and standards of complex integrated system design and to carry out development and implementation of innovative projects and decisions Analytical. To carry out analysis of subject domains and requirements for the designed systems, to develop conceptual models and architectural concepts of complex integrated systems, to define technologies providing functioning of the designed systems, and to carry out consulting activities. Communicative. Ability and skills to carry out analytical and practical information transfer and ability to keep in touch with representatives of organizations that carry out development and operation of adjacent systems integrated with the developed ones including those in the international environment. Administrative. Ability to manage groups of complex system designers and developers. 4.2. Evolution of the curriculum The curriculum drew upon the analysis of educational standards of graduate studies relevant to the master’s training, research of international experience in training on system analysis and concept system design, and the analysis of modern educational trends that were conducted before its development (Annex 1). Gaps in the fundamental knowledge necessary to successfully completing the master’s training were found in the master’s students. To address this, both mandatory disciplines and optional courses were included in the curriculum, relating to mathematics, informatics, and modern information technologies. Some of these allow eliminating the gaps inherent in those master’s students who were trained in economic and engineering majors. The preliminary curriculum was presented in the Preliminary Report on master’s training, based on which another version of the curriculum was developed. It involved introducing the editor's changes and accommodating formal requirements on the number of hours and quantity of credit units. This version of the curriculum is given in Table 1. Table 1: Preliminary curriculum as proposed Credit No. Name Hours: total/classwork units Mandatory disciplines of the governmental component 1. Applied theory of information 100/50 4 2. Software design and development technologies 100/50 4 3. Architectures of computer systems 100/50 4 4. Integrated security of information technologies and systems 100/50 4 5. Theory of complex systems and system analysis 100/50 4 6. Methodologies and technologies of conceptual design 98/42 3 Mandatory disciplines determined by the university 1. Intelligent systems and machine learning 96/44 4 2. Applied statistics and big data analysis 96/44 4 3. Project management 36/62 2 4. Software-oriented data storage systems and modern DBMS 102/48 4 5. Technologies and templates for information system integration 78/44 3 Training modules including optional disciplines 11 Credit No. Name Hours: total/classwork units 1. Mathematics and informatics (2 courses of 4) 80/160 6 2. Modern information technologies (2 courses of 4) 188/88 8 3. Information security (1 course of 3) 78/42 3 4. Complex systems analysis and design (2 courses of 4) 200/100 8 5. Applied information technologies and systems (2 courses of 4) 160/76 6 Other forms of training 1. Practice-oriented research work (project work) 960 27 2. Internship 540 14 3. Final certification (writing, discussing, and defending of master’s 270 7 thesis) Source: BSU. Note: DBMS = Database management system. A standard curriculum given in Russian in Annex 2 was approved in August 2017. It formed the base for the curriculum (Annex 3) that is now used for training. These curricula have retained the structure and content of the curriculum shown in the Preliminary Report. The prospective curriculum has been developed based on the discussion of the curricula and programs of master’s training within the expert society. The curriculum will be implemented by 2018 (Table 2). Table 2: Preliminary curriculum as implemented Hours: Credit No. Name total/classwork units Mandatory disciplines of the governmental component 1. Applied theory of information 100/50 4 2. Software design and development technologies 100/50 4 3. Architectures of computer systems 100/50 4 4. Integrated security of information technologies and systems 100/50 4 5. Theory of complex systems and system analysis 100/50 4 6. Methodologies and technologies of conceptual design 98/42 3 Mandatory disciplines determined by the university 1. Intelligent systems and machine learning 96/44 4 2. Applied statistics and big data analysis 96/44 4 3. Project management 36/62 2 4. Software-oriented data storage systems and modern DBMS 102/48 4 5. Business analysis in large system design 78/44 3 Training modules including optional disciplines 1. ’Soft skills’ (2 courses of 4) 80/160 6 2. Informatics and modern information technologies (2 courses of 4) 188/88 8 3. Information security (1 course of 3) 78/42 3 4. Complex systems analysis and design (2 courses of 4) 200/100 8 5. Applied information technologies and systems (2 courses of 4) 160/76 6 Another form of training 1. Practice-oriented research work (project work) 960 27 2. Internship 540 14 3. Final certification (writing, discussing and defending of master’s 270 7 thesis) Source: BSU. The differences are as follows: • The ‘mathematics and informatics’ optional module is excluded from the curriculum. 12 • The experience in developing academic programs has shown that missing knowledge in this area resulting from the gap in training at graduate and postgraduate levels is eliminated during training itself with the help of relevant master’s disciplines. • The ‘soft skills’ module dedicated to the development of communication and creativity skills of trainees is included instead. • The ‘technologies and templates of information system integration’ mandatory course is reluctantly made an optional course; the ‘business analysis in large system design’ course is made a mandatory course instead. 4.3. Educational standard and programs of core disciplines The formal document that characterizes the postgraduate master’s training is the educational standard (see Annex 2). This standard contains the following main paragraphs: • General provisions • Professional activities of the master’s • Requirements for the master’s competence • Requirements for the training program and content of the academic training documentation • Requirements for educational process organization • Requirements for the final certification 4.4. Organization of educational process The master’s training program curriculum consists of modules. Each module includes a certain amount of classwork hours and independent work hours. Classwork hours for some modules including compulsory courses are 40–50 hours, and for the module with two optional courses, it is 80–88 hours. About 96–108 and 172–180 hours of independent work are planned for modules with compulsory courses and those with optional courses, respectively. Up to half of independent work is given to the fulfillment of individual and group practical tasks. Up to one- third is given to the accomplishment of individual tasks that assume independent development of educational content, shared by the students within the network community of master’s students and teachers. Such content includes abstracts, articles, and essays of 6 to 20 pages length. The development of educational content should result in the report for each master’s student. The university-based classes can be divided into three types. 1. Lectures (12–18 academic hours) 2. Facilitation and discussion of the results of independent work on educational content creation 3. Consultation on practical tasks completion. The university-based classes can be held both in the classroom and online (webinars and so on). Lectures are video recorded, to which master’s students are given free or authorized access. 13 5. Required technical infrastructure The following requirements for the technical structure have been developed: 1. Network infrastructure for wired and wireless connection of mobile devices of master’s students to the local university network with the connection speed at each working place of not less than 20 Mbit/s. 2. Hardware equipment providing • Video recording of classes (not less than three parallel video flows, one of them from the projector); • Live Internet broadcasting of events; and • Video conferencing including multipoint ones. 3. Not less than 4,000-lumen full HD video projector with High-Definition Multimedia Interface (HDMI) source connection in the classroom For ensuring an effective educational process in the BSU State Institute of Management and Social Technologies, its information infrastructure has been significantly updated, and all the required educational technology equipment has been bought. Room 311, a separate classroom in the academic building at 7, Oboynaya st., situated in the center of Minsk, was provided for training of master’s students. Equipment at a specialized classroom A specialized classroom for university-based classes for master’s students has been organized in room 311 of the academic building at Oboynaya st. New furniture, a 4,000-lumen full HD video projector, and a whiteboard have been arranged for this class. The classroom has all necessary infrastructure for master’s students to easily use private laptops (20 computer network outlets, 30 power sockets, and wireless Wi-Fi for 30 simultaneous connections). The Softline Company at its own expense has installed a complex of equipment providing three-channel video recording of lectures, online broadcasting of lectures and workshops, and multipoint video conferencing in the classroom. Upgrading of local computer network The existing local computer network of the State Institute of Management and Social Technologies in the building at 7, Oboynaya st. has been significantly upgraded. New wire and wireless segments of the network have been created. The institute’s network instead of old asymmetric digital subscriber line (ADSL) internet channel is now connected at a speed of 1 Gbit/s via the provided fiber optic cable to the BSU head communication hub with access to the Internet at two 1.2 Gbit/s channels and the Belarussian segment of the Internet at 2 Gbit/s. Eduroam All master’s students have access to the BSU information network. Thus, they can use the Eduroam service. The Eduroam global service (EDUcation ROAMing) enables users (scientists, teachers, students, and researchers) to immediately and safely access to the Internet from any institution participating in the service. In its turn, the wireless network segment of the State Institute of Management and Social Technologies is also integrated into the world federation of Eduroam roaming authentication. Owing to this, teachers and scientists, the majority of whom came from European, American, Australian universities with their logins and passwords, can have immediate access to public network resources of the university and the Internet. 14 Learning Management System A major Belarussian IT company, IBA has refined, as part of the master’s training, and rendered to the university the eUni learning management system (LMS) for free. This is a multifunctional system for organization training with distance and online learning options appropriate • To organize training and consultation for an unlimited number of trainees via the Internet or in the local network; • To combine traditional academic methods and latest communication and multimedia technologies; • For the efficient cooperation of teachers and students at any time convenient for everyone; • For an independent study of students; • For tests and automated assessment of knowledge; and • For training organization and efficiency control. 15 6. Steps taken to launch the master’s training program 6.1. Development and approval of methodical academic documentation The development of methodical educational documentation preceded the analysis of educational standards of higher education relevant to the master’s program, research of international experience in system analysis and system conceptual design training, and analysis of modern educational trends. Opening of the major In accordance with the existing procedure for opening new majors in Belarus, the justification was developed and the requests from potential employers of the master’s graduates for the next five years were collected. According to the existing legal acts and the drafts approved by the Ministry of Education, the standard curriculum and the educational standard drafts were developed. These documents were analyzed and negotiated at the Head Department of Academic and Scientific Methodical Work of BSU. The external reviews of the standard curriculum and the educational standard drafts were also conducted. Justification of the major opening was discussed at the meeting of the Educational Methodical Association on natural science training of the Ministry of Education. Following the Educational Methodical Association approval, the justification, the standard curriculum, and the educational standard drafts together with their reviews were transferred to the Republican Institute of Higher School for further analysis and review. After the institute negotiated and refined the curriculum and the educational standard drafts, the Ministry of Education prepared and signed the order for the launch of the master’s training program. The final stage of the major opening will be including it in the Republican Classifier. Approval of curricula and the educational standards The curricula and the educational standards modified based on remarks received underwent the recurrent review at the Republican Institute of Higher School and were then approved by the first deputy Minister of Education. Opening of training To open the training, approval by the Academic Council of the State Institute of Management and Social Technologies as well as the Council of BSU was essential. Then, all the necessary materials for the ministry were prepared, which introduced the required amendments to the license of the BSU. 6.2. Website for master’s training and its presence in social networks A special website for the master’s training program3 has been created to inform about its activities. The website presents general information about the master’s training, curriculum, terms of entrance, entrance exam program, teachers and partners, and so on. There is a feedback option for communication with website visitors. Also, master’s pages have been created on local Facebook and LinkedIn networks. There is a constantly functioning private group on Facebook called ‘Master’s Students and Teachers of Complex Integrated System Design’. Also after the beginning of the training, the Master’s YouTube channel4 was launched where videos of lectures and other events are available. 3 http://msys.bsu.by. 4 https://www.youtube.com/channel/UCgEOU2r9cYsRho02PPzAGpA. 16 6.3. Recruitment of teaching staff Teaching staff for master’s training were recruited according to the principles detailed in section 3.7. The emphasis was on inviting experts who actively work in IT. Some of them continue teaching activities. Altogether, almost all the university teachers involved in the master’s training deal with practical activities as well. 6.4. Enrollment of master’s students and the beginning of training Due to the late dates of enrollment, which was held during the summer vacations, the first enrollment saw only ten trainees joining the program. Nevertheless, they represent various groups of potential master’s students that were planned to be enrolled. It gives an opportunity to try out the training methods and enhance the curricula and programs even with such a limited number of master’s students. Different categories of master’s students are as follows: • Graduates of the university and experts with practical experience in software development in IТ: 40 percent; • Graduates of the BSU majors who work in IТ but do not have any relevant practical experience: 40 percent; • Graduates of technical majors who work in other areas, including business owners: 20 percent. 6.5. Organization of training The educational modules are scheduled sequentially. The schedule for the first semester is given in Table 3. Table 3: First semester schedule for the academic year 2017/18 Consultation, No. Educational module Teachers Term of training Lections exams/passes 1. Optional course 1 Doctor of Physics- September 11 September 11 October 23 to Mathematics to October 28 to September October 28 Sciences, professor, 23 Kotov Vladimir Credit Mikhailovich 2. Project management PhD in technical September 25 September 25 November 8 to sciences, associate to November 11 to October 7 November 11 professor Lukyanov Dmitriy Exam Vladimirovich 3. Applied theory of PhD in Physics- October 9 to October 9 to November 20 to information Mathematics November 25 October 21 November 25 Sciences, associate professor Exam Vorotnitskiy Yuriy Iosifovich 4. Optional course 2 PhD in Physics- October 23 to October 23 to December 4 to Mathematics December 8 November 4 December 8 Sciences, associate professor Pobegailo Credit Aliksandr Pavlovich 5. Intelligent systems and PhD in Technical November 6 to November 6 to December 18 to machine learning Sciences, associate December 23 November 18 December 23 professor Strikelev Credit 17 Dmitriy Aleksandrovich 6. Software design and Soroka Aleksandr November 20 to November 20 to January 3 to development Mikhailovich Janiary 6 December 2 January 6 technologies Exam 7. Applied statistics and Mayuk Sergey December 4 to December 4 to January 15 to big data analysis Petrovich January 20 December 26 January 20 Exam 8. ‘Complex integrated Doctor of Technical September 11 January 15 to systems’ workshop Sciences, Professor, to January 20 January 20 Honorary Scientist of the Republic of Independent Belarus Kurbatskiy research work Aleksandr credit Nikolaevich Source: BSU. • Lectures are held every Wednesday from 18:00 until 19:20 hours and from 19:30 until 20:50 hours, and on Saturdays from 10:00 until 11:20 hours and then from 11:30 until 12:50 hours. • The meetings of a permanent open workshop are held once a week. The schedule and topics are shared on the web page of the master’s studies and in its Facebook group. • All internal classes are held in room 311 of the State Institute of Management and Social Technologies building at 7, Oboynaya st. • The schedule of internal and remote practical classes, workshops, and consultations on labs is finalized with the teacher who should post the schedule in the private Facebook group. 18 7. Cooperation with IT companies and employment of master’s graduates The issues of creating the master’s training were discussed with the heads and professionals of leading Belarussian IТ companies. At the moment we have received requests for the master’s training on ’complex integrated system design’ from the Infopark Research Technology Association that unites leading Belarussian organizations specializing in development and implementation of progressive information technologies. Other organizations include major resident IT companies of the Belarusian Hi-Tech Park, ООО ‘Novacom group’ and ООО ‘Belhard Development’, and the parent organization in Belarus on creation and functioning of information resources about goods (products), their automatic identification, and e-flow of documentation of goods production networks and electronic trade processes, the ‘Identification System Center of the NAS of Belarus’ State Organization. The total prognostic demand calculated based on the requests is not less than 25 master’s graduates per year. 19 8. Feedback from master’s students: Survey results In late November 2017, a meeting with master’s students on the issues of classwork organization and surveys aimed to evaluate training disciplines and teachers was held, where the following common problems were revealed: Master’s students are not ready for such a huge amount of independent creative work. First, this activity is poorly used in the Belarussian high school, and it required additional effort from master’s students to switch over. Second, they were not ready for proper time management to fulfill tasks such as development and assessment of own educational content, mini-projects, and so on. Finally, almost all the master’s students have a full-time job (allowed by Belarusian law) that results in lack of time. Differences between master’s students in the level of education and actual professional activity. The level of teaching of some disciplines not fully comprehensible for some students might seem simple for others due to their professional background. Uncertainty of teachers regarding the volume of teaching subjects. Teachers themselves have not yet decided the appropriate depth of coverage for certain disciplines required for future professionals in complex integrated system design. During surveys on each discipline and each teacher, master’s students were asked to describe the weak and strong points and rate them on a scale of 1 to 10. The results are summarized in Tables 4 and 5. It is of great importance that master’s students highly assessed practical skills of the teachers. Table 4: Survey results by discipline Average No. Discipline Strong points Weak points score 1. Theory of “Main types of algorithms are “Representation of the material is 8.25 algorithms basics shown very briefly, concisely for students of profile courses. I but clearly with practical tasks have no idea if I would ever use the as an example but without knowledge received within this going deep into theory.” discipline.” “Interesting practical tasks from “Personally I was a bit bored as we real requirements.” studied this at a deeper level at university and further at work.” “Little amount of academic periods for such a course.” 2. Project “An important subject for “No” 9.4 management architects” “Modern (not only) project management methodologies are represented. Personally, I see the great practical value of it as I face it in my everyday work. It became more clear how to negotiate with the customer and how to build a relationship with the team of developers.” “Lectures were useful for me. Soon after attending them I could prove my knowledge at 20 Average No. Discipline Strong points Weak points score 80% while passing a test for introduction to Scrum methodology on the scrum.org platform.” “Interesting practical tasks with real process modeling. Practical tasks fulfilled in team and ready-made scrum-board in the end. Scrum certificate” 3. Applied theory of “The review part of I. “I would like to learn more about 8.25 information Heydorov’s lectures were 100% the information concept and work useful. The material is easy to with it on a conceptual level that understand and explained was touched in the first lecture.” through examples.” “Sometimes there was lack of “An interesting course for cooperation in giving the material overall development. Especially by the two lecturers: there I liked topics on human sound appeared unreasonable perception.” repetitions.” “The course was well prepared by each teacher. Vorotnitskiy tried to direct it into his subject field, telecoms, and Heydorov to the signal processing, but these movements have made the course even more interesting.” “A perfect balance of course detailing level. Easy to master. A brilliant lecture of Heydorov on cryptocurrencies.” 4. Object-oriented “An important subject, as I see “Mainly it was UML detailed 5.75 analysis and it, it’s the closest to the learning. During my work, I have design master’s major among other never needed to know UML at a technical disciplines. I am low level. Enterprise Architect was interested to continue training recommended as a program, but it on it individually.” is not a free program itself.” “Practical tasks connected to “The course is overloaded with the actual practical targets.” unnecessary detailing and terms hard to memorize. It is focused only on one tool—UML.” 5. Intelligent “A very relevant issue. If to “The subject is the hype. However, 7.25 systems and change the course a bit so that it is not the most essential at the machine learning to leave theoretical training on stage of mastering the system the low level and to spend architecture. There are many more time on basic issues peculiarities and mathematical (what, why, restrictions, tasks, proofs in representing it.” etc.) and to give plenty of examples of real completed “The first classes were a try for a tasks so that the students could considerably low level in mastering generally understand what and algorithms of linear and logic when it can be applied; thus the regression. Those who need deep 21 Average No. Discipline Strong points Weak points score course will become not good understanding of machine learning but perfect” algorithms had better use a free course in SHAD by Vorontsov.” “The course itself is fascinating and up-to-date.” “A perfect balance of course detailing and adaptation amendment of content and complexity based on master’s students’ requests. Interesting practical tasks divided into three levels: deep theory, applied (coding), and level of ‘black box’ research — 3D party services.” Source: BSU. Note: UML = Unified Modeling Language. Table 5: Survey results by teacher Average No. Discipline Strong points Weak points score 1. V. М. Kotov “The teacher is experienced, “Total improvisation at lectures. 7 knows the subject well.” Generally, the lectures and the subject are not structured. Loose “V. М. Kotov is very good at formulation of independent the subject, answers any work.” question that is asked” “A lively form of classwork, no syndrome of dozing.” 2. D. V. Lukyanov “A perfect lecturer ­ “Sometimes there is lack of 9.5 practitioner. Joins concept distance from a younger information to exact audience that results in the examples from reality. I was feeling of familiarity.” able to apply immediately the information in my present work of an architect. The teacher has developed an integrated system prototype within his subject.” “Ability to concentrate on the practical part of the subject. Capable of holding the audience’s attention.” “Lukyanov is a strong practitioner. During the training, he constantly demonstrated examples from real projects. The presentation was well 22 Average No. Discipline Strong points Weak points score prepared. Homework was formulated easily, but the discussion meeting was beneficial.” “Lively lectures with real-life cases. Experience in project management.” 3. Yu. I. Vorotnitskiy “Ability to explain the “It would be better to maximally 9.1 essence of the subject at shorten the number of formulas restricted time, in brief, and represent information with supporting with the examples more examples as the level of from personal practice.” math’s training is different among students.” “Experienced teacher.” 4. I. E. Heydorov “Ability to attract and hold “No” 9.6 the audience’s attention for a long time explains complicated issues in a light and interesting manner, doesn’t use stock phrases at work with audience.” 4. A. P. Pobegailo “Deep and systematic subject “It seems that the teacher uses 7.5 representation.” complicated words to describe simple things. He excessively “Pobegailo is a strong highlights the importance of the practitioner who has taught course.” the course for a long time. The narration is exact and continuous.” “Experience: А. P. has worked on real projects through all his life.” 5. D. А. Strikelev “Professional representation “Mathematics in the subject 7.5 of the subject.” representation dominates over the sense representation.” “Strikelev is very strong as a practitioner and teacher. His “The teacher has obviously had interesting manner of lack of time to prepare the narration should be course. The narration often has mentioned.” “slacks” and pauses as well as inconsistency. I have lowered the mark not for personal qualities of the teacher but poorly prepared course.” Source: BSU. 23 9. Promotion and development The ‘Complex Integrated System Design’ master’s postgraduate program is seen as a pilot project for trying out a new IТ education model in Belarus. The main features of this model are discussed in the following paragraphs. The involvement of a potential employer at all stages of preparation from requests for training, participation in the development of curricula and programs, establishment of grants on training for master’s students, and the involvement of IT companies’ specialists in teaching to internship support, assessment of graduates, and the work results of education institutions. The key role of practice. Practical training is provided for each educational module. From the very beginning, the postgraduate master’s students are involved in scientific work with results discussed at a permanent workshop. Four months are planned for the internship. In addition, this shall be a real practical activity according to the major where the postgraduate master’s student is to develop an integrated complex system project. To provide such internship, we involve enterprises from the BSU IT cluster (SoftClub, NTLab, ZTE, and so on). Experienced teachers from the real IT industry. The teaching staff is generally formed from the graduates of the leading universities with pedagogical work experience and degrees and those working in IT companies. New forms of training classes. Academic periods for each module are conventionally divided into three parts: lectures (seven to eight lectures on fundamental issues of the course), consultations for master’s students on the independent creation of educational content and its discussion in social network groups or at the forum created in the educational process control system, and consultations on practical training carried out within the periods devoted to independent work. Here online training technologies are used. The curriculum has a modular structure, and modules are studied sequentially. Certification. While developing course programs, we seek to create an opportunity for master’s students to obtain international certificates based on the results of mastering certain courses. Using of Openedu systems. Some optional courses can be studied in the existing open educational systems. The cross-disciplinary knowledge ensured by modules such as public administration and e-government, bank and insurance systems, e-economy, and e-commerce. Finally, this is an example of successful cooperation between the public education and nongovernmental organizations (the World Bank, Softline Group) on the implementation of an educational project where cooperation is seen in actual funding of certain work directions on postgraduate maser’s training development. 24 Figure 5: Current requisitioners of the graduates of the master's program Source: BSU. Today the key Belarussian IT companies, such as Itransition, Belhard, IBA, EPAM Systems, SoftClub, Novacom, and others, support this master’s training. Figure 6: Companies supporting the development of the master’s program Source: BSU. 25 Annex 1. Program for disciplines of special training 1. Programs for disciplines of the governmental component 1.1. Applied theory of information Program structure Hours Classwork 50 Lectures 16 Workshop (webinar) 18 Consultations on practice 8 Project discussion 8 Individual work 100 Independent development of academic materials on topics 24 Practice accomplishment 32 Group project development 44 Expected academic result Master’s students • Various approaches defining the information concept; are to know • Methods and means to determine the amount of information; • Methods of analog-digital transformation of signals; • Ways of digital data transmission; • Methods of data compression; and • Major methods of data encrypting. Master’s students • To calculate the amount of information in messages; are to be able • To use the Kotelnikov’s theorem for solving analog-digital and digital-analog signal converting problems; and • To assess required parameters of communication channels, data storage, and processing systems for solving applied tasks on information storage, transfer, and processing. Course content Information in the material world. Information in computer and communication systems. Information, message, and signal. Analog and digital messages. Sampling and quantization. Recovery of analog signals. Kotelnikov's theorem. Information measurement. Combinatory approach to the concept of information. Problems of optimum search in data arrays. The task of the ideal secret division. Probabilistic approach to the concept of information. Shannon's entropy. Algorithmic approach to the concept of information. Kolmogorov complexity. Relation of algorithmic measure of information to combinatory and probabilistic approaches. Communication complexity. Main characteristics of physical channels of information transfer. Division of channels. Modulation and demodulation. Interference-free information transfer via channels. Generalized information channel model. Shannon's theorem on coding for the interference-free discrete channel. Effective coding. Information transfer on channels with interference. The simplest, highest, and lowest estimates of code redundancy. Correcting codes. Probabilistic models of channels with noise. Shannon's theorem on coding for channels with noise. Applications of the theory of information (computer networks and wireless technologies, data compression, storage, transfer and processing of multimedia information, cryptography, and cryptoanalysis). 26 Recommended literature: Gleick, James. 2016. Information: A History, a Theory, a Flood. AST Publishing House, Corpus. ISBN: 978-5- 17-097070-4. Kudryashov B.D., 2010. Information Theory. St. Petersburg: SPbSU ITMO. 188 p. Panin, V. V. 2009. Fundamentals of Information Theory: A Textbook for High Schools. 3rd ed. cor. Moscow: BINOM. Laboratory of Knowledge. 438 p. 1.2. Software design and development technologies Course structure Hours Classwork 50 Lectures 16 Workshop (webinar) 18 Consultations on practice 10 Project discussion 6 Independent work 100 Independent development of academic materials on topics 24 Practice accomplishment 24 Project development 52 Expected academic result Master’s students • Software life-cycle models; are to know • Various approaches to program systems design; • Basic architectural styles; and • Purpose of design patterns. Master’s students • To build cascade, spiral, incremental, and ХР-models of software; are to be able • To practically use the object-oriented paradigm and build UML diagrams of a program product; and • To assess the necessity and efficiency of using the design patterns in program product development. Course content Models of software and system development life cycle. Cascade model, cascade model with the intermediate return. Spiral model. Incremental model. XP model. Classical technologies of software development. Computer-aided software engineering (CASE) technologies of software design. Description of system behavior. Description of a system condition space. Appointment and basic concepts of the UML. Functional requirements and charts of usage options. Main architectural styles. Object-oriented paradigm. Architecture of a data flow. Hierarchical architecture. Interaction directed architecture. Distributed architecture. Component architecture. Layered architecture. Design term patterns. Design patterns as result of knowledge systematization of object-oriented design methods. Generating design patterns and their comparison. ‘Abstract factory’, ‘Particular factory’, ‘Single’, ‘Builder’ design patterns. Structural design patterns. ‘Adapter’, ‘Bridge’, ‘Decorator’, ‘Façade’, ‘Deputy’ design patterns. Comparison of structural design patterns. Purpose of behavior patterns. ‘Chain of duties’, ‘Team’, ‘Interpreter’, ‘Observer’, ‘Strategy’, ‘Visitor’ behavior patterns’. Comparison of behavior patterns. Recommended literature: Gamma, E., R. Helm, R. Johnson, and D. Vlissides. 2014. Methods of Object-oriented Design. Patterns of Design. St. Petersburg [and others]: St. Petersburg. 366 p. 27 McConnell, Steve. 2005. Code Complete. St. Petersburg. 896 p. (Master class). ISBN 5-7502-0064-7, 5-469- 00822-3. Fowler, Martin. 2002. Patterns of Enterprise Application Architecture (Addison-Wesley Signature Series). Massachusetts. 558 p. ISBN 978-5-8459-1611-2. 1.3. Architectures of computer systems Course structure Hours Classwork 20 Lectures 16 Workshop (webinar) 8 Consultations on practice 26 Independent work 100 Independent development of academic materials on topics 36 Practice accomplishment 64 Expected academic result Master’s student is • Hardware, software components and interfaces of computer systems; to know • Main approaches to the organization of computer systems; • Parallel and distributed architecture of computer systems; • Levels and ways to organize processes interaction of computer system; • Methods of assessment of computer systems productivity; and • Ways of the organization of computer systems reliability. Master’s student is • To develop an architecture of a computer system; to be able • To organize interaction of computer system processes; • To assess the productivity of a computer system; and • To provide reliability of a computer system. Course content Computer systems. Components and interfaces of computer systems. Organization of computer systems: modularity, hierarchical organization, virtualization. Architecture of computer systems. Parallel computer systems. Distributed computer systems. Processes and streams. Virtual memory. Addressing of processes. Object naming. Naming levels. Schemes of naming. Permission of names. Interaction of processes. Interaction levels. Protocols of interaction. Communication via messages. Communication based on data flows. Sockets. Remote call of procedures. General memory. Appeal to remote objects. Architectural templates of component interaction. Synchronization of processes. Synchronization of hours. Ordering of events. Global state. Mutual exception. Deadlocks. Transactions. Vote algorithms. Coordination algorithms. Replication and consistency of data. Purpose of replication. Passive and active replication. Data-oriented consistency models. Client-oriented consistency models. Distribution protocols. Consistency protocols. Productivity metrics. Response time decrease. Capacity increase. Multilevel memory management. Scheduling of processes. Division of resources. Scheduling metrics. Loading balancing. Reliability of a computer system. Fault tolerance of processes. Reliability of processes connection. Reliability of calculations. Detection and recovery after failures. Control points and kickback. Recommended literature: A. N., Stepanov. 2017. Architecture of Computer Systems and Computer Networks. St. Petersburg. 509 p. 28 Tanenbaum, Andrew S., and M. Van Steen. 2003. Distributed Systems. Principles and Paradigms. St. Petersburg. 877 p. Saltzer, J.H., and M. F. Kaashoek. 2009. Principles of Computer Systems Design. An Introduction. Part I. Morgan Kaufmann Publishers. 526 p. Saltzer, J.H., and M. F. Kaashoek. 2009. Principles of Computer Systems Design. An Introduction. Part II. Massachusetts Institute of Technology. 826 p. 1.4. Integrated security of information technologies and systems Course structure Hours Classwork 50 Lectures 16 Workshop (webinar) 12 Consultations on practice 8 Project discussion 14 Independent work 100 Independent development of academic materials on topics 24 Practice accomplishment 16 Project development 60 Expected academic result Master’s students • Basic concepts of information security; are to know • Legal base on information security; • Methodologies of compliance design and assessment of information security systems; and • Standards of information security. Master’s students • To apply methodologies of compliance design and assessment of information security are to be able systems at complex integrated system design; • To develop tasks on security; • To develop security policy; and • To use standards and legal documents on information security in professional activity. Course content Complex security of information systems. Elements of information security. Assets, objects, subjects of information security. Attacks, threats, vulnerabilities. Classification of attacks. Cybercrime. Modern trends in cybercrimes. Modern types of attacks. Responsibility for illegal acts in information technologies area. International legislation and international standards on information security. National legislation of Republic of Belarus and national standards on information security. Information security management system (ISO/IEC 27001). Ensuring information security at all stages of information systems life cycle. Classification of information systems and processed information. Requirements to information system security. The model of the violator. Design, creation, and assessment of information security system compliance. Technical and organizational measures of ensuring information security. Audit of information security. Information security risk management. Reputational risks. Main stages of risk management. Tools for information security risk monitoring. Economic feasibility. Efficiency of information security measures. Security assessment methodologies. 29 Ensuring safe functioning of information systems in cloud infrastructure. Ensuring safe processing of personal data. Features of ensuring of the complex integrated information systems information security. Ensuring information security at cross-border information exchange. Recommended literature: V., Bondarev. 2016. Introduction to Information Security of Automated Systems: Textbook. Moscow: Publishing house MSTU. 250 p. A.B., Petrakov. 2005. Basics of Practical Information Protection. Tutorial. Moscow. 281 p. V., Shangin. 2015. Integrated Information Security in Corporate Systems. Moscow. 592 p. 1.5. Theory of complex systems and system analysis Course structure Hours Classwork 50 Lectures 16 Workshop (webinar) 12 Consultations on practice 8 Project discussion 14 Independent work 100 Independent development of academic materials on topics 24 Practice accomplishment 16 Project development 60 Expected academic result Master’s student is • Basic concepts of system analysis; to know • Methods of system modeling; • Principles of automatic control systems functioning; and • Basics of the dynamic systems theory. Master’s student is • To investigate systems by methods of system analysis; to be able • To carry out modeling of complex systems; and • To apply methods of system analysis at design and development of information systems in various subject domains. Course content Concept of a complex system. Features and properties of complex systems. State and functioning of a system. Functions of feedback. Structures of systems. Classification of systems. Complexity of systems. Complexity measures of systems. Modeling of systems. Appointment and types of models. Modeling levels. Classification of methods of system modeling. Information approaches the system analysis. Discrete information models. Automatic control systems. Mathematical models of automatic control systems. Transfer function. Stability of automatic control systems. Intellectual automatic control systems. Basics of the dynamic systems theory. Systems with discrete and continuous time. Ways of description and main properties of dynamic systems. Decomposition of systems. Analysis and synthesis in system research. Models of systems as decomposition basis. Decomposition process algorithmization. Aggregation of systems. Types of aggregation. Emergence as result of aggregation. Examples of units. Semantic networks. 30 Life cycle of complex systems. Evolution of complex systems (laws of evolution, the S-curve law, the law of increase in the degree of ideality, laws of transition into the super system). Recommended literature: Chernyshov V.N., Chernyshov A.V. 2008. Theory of systems and systems analysis. Tambov: TSTU. 96 p. F. P., Tarasenko F.P. 2010. Applied system analysis. Moscow: KnoRus. 224 p. Volkova V.I., Denisov A.A. 1997. Fundamentals of the theory of systems and systems analysis. St.Petersburg: SPbSTU. 510 p. Loskutov A., Mikhailov A. 2007. Fundamentals of the theory of complex systems. Moscow - Izhevsk: Institute for Computer Research. 620 p. 1.6. Methodologies and technologies of conceptual design Course structure Hours Classwork 42 Lectures 16 Workshop (webinar) 12 Project discussion 14 Independent work 98 Independent development of academic materials on topics 36 Project development 62 Expected academic result Master’s students • Conceptual design and its place in a system life-cycle model and are to know • Methods of modeling of a subject domain and synthesis of a projected system concept. Master’s students • To perform a pre-design inspection of the object of informatization; are to be able • To build models of the subject domain according to IDEF0 (Function Modreling Method) and IDEF1 (Information Modreling Method) using relevant equipment; and • To synthesize concept solutions of complex systems. Course content The concept of conceptual design as the initial phase of design. Concept of the system. Concept of a concept. Main stages of concept design. Understanding of structure and functioning of the organization. Predesign inspection. Analysis of business processes and the current state of the organization infrastructure, description of adjacent systems and their interrelations. Problem identification and analysis, the definition of requirements. Definition and documenting of entities and communications between them. Modeling of a subject domain. IDEF methodologies. Functional modeling, modeling of information streams. Synthesis of solutions: development of options of solution architecture and key components of information and communication infrastructure and systems; comparative analysis of each component and choice of target architecture option. Application of methods and technologies of the theory of inventive problem solving for the concept design of complex systems. Alternative methods of decision-making: morphological analysis, brainstorming, and synectics, trial and error method. Development of recommendations on reengineering of business processes by the developed system concept. Recommended literature: 31 Coburn, Alistair. 2011. Modern Methods of Describing Functional Requirements for Systems. Moscow: Lori. 288 p. Carl I. Wiggers, Joy Beatty. 2014. Development of Software Requirements. St. Petersburg: BHB. Repin V., and Eliferov V. 2012. Process Approach to Management. Modeling of Business Processes. Moscow: Mann, Ivanov and Ferber. Goldstein E. and Korobko P.F. Theory of Inventive Problem Solving. Tomsk: Publishing house of Tomsk Polytechnic University, 2009. 153 p. 2. Programs for disciplines of University component 2.1. Intelligent systems and machine learning Course structure Hours Classwork 44 Lectures 16 Workshop (webinar) 12 Consultations on practice 16 Independent work 96 Independent development and study of academic materials 44 on topics Practice accomplishment 52 Expected academic result Master’s student is • Basic concepts and principles in machine learning and to know • Main types of machine learning algorithms, their features and terms/limits of applicability. Master’s student is • To develop machine learning algorithms in of Matlab/Octave environment and to carry to be able out their debugging and • To research machine learning algorithms efficiency and to perform optimization of their parameters. Course content The task of learning. Objects and features. Types of tasks: regression, classification, forecasting, ranging. Learning model, learning method, function of losses. Degrees of model proficiency and retraining. Linear regression. Model and criterion function task. An iterative method of parameter value calculation. Scaling of features and learning speed control. Analytical calculation of parameter values. Transfer from linear to nonlinear regression. Logistic regression. Classification problem definition and formulation of a hypothesis with function- sigmoid. Limit of classes (decision-making limit). Criterion function for a logistic regression problem. Regularized logistic regression. Metrics of classification quality. Multiclass classification. Neural networks. Biological motivation for neural networks. Neuron and multilayered perceptron. Activation function. Classification of neural networks. Direct distribution neural networks. Method of mistake reverse distribution. Mathematical interpretation of neural network learning. Multiclass classification. Method of basic vectors. The principle of an optimum dividing hyperplane. Concept of a basic vector. Similarity assessment. Core function. Support Vector Machine (SVM) interpretation as a two-layer neural network. 32 Learning without a teacher. Clustering task—basic provisions and possible application. Closest neighbours method—casual initialization, the definition of clusters number. Generalization and visualization tasks—basic provisions and possible application. Major component method—compression and reconstruction. Recommended literature: Merkov, A. 2011. Pattern Recognition. Introduction to Statistical Learning Methods. Editorial URSS. 256 p. Falkh, P. Machine Learning. 2015. Science and the Art of Constructing Algorithms That Extract Knowledge from Data. Textbook. DMK Press. 400 s. Alpaydin E. 2009. Introduction to Machine Learning (Adaptive Computation and Machine Learning Series).The MIT Press. 584 p. Bishop, C.M. 2006. Pattern Recognition, and Machine Learning. Springer. 738 p. 2.2. Applied statistics and big data analysis Course structure Hours Classwork 44 Lectures 16 Workshop (webinar) 8 Consultations on practice 8 Project discussion 12 Independent work 96 Independent development of academic materials on topics 24 Practice accomplishment 46 Project development 26 Expected academic result Master’s students • Methods of descriptive statistics; are to know • Methods and algorithms for data analysis, processing, and systematizing; and • Technologies of big data arrays extraction and processing. Master’s students • To develop a necessary model and an algorithm for solving a specific data analysis are to be able to task; • To investigate the efficiency of application of a certain method for solving a data analysis task; and • To apply technologies and tools of data analysis. Course content Descriptive and analytical statistics. Scales of relations. Discrete and interval variation ranks. Numerical characteristics of one-dimensional features. Average magnitudes and sedate averages. Structural averages. Characteristics of dispersion and distribution forms. Types of connection between phenomena. Two-dimensional frequency distributions and marginal distributions. Covariance. Pearson’s pair linear coefficient of correlation. Main definitions, terms, tasks of the big data analysis. The process of knowledge discovery. Information sources for data collection. Portals of open data. Cognitive data analysis. Search methods of associative rules. Support and reliability of the associative rule. Types of associative rules. Search algorithms for associative rules. 33 Search of standard sequences. Problem of sequence template detection. Expressions of sequence, length and extent of a sequence, maximum sequence. Classification and clustering. Tasks of forecasting. Analysis of text information. Visual analysis of data. Technologies for big data storage. Horizontal scalability of big data storage and processing. Databases and models of data applied for big data storage and processing. Storage and processing of the structured and unstructured information. Hadoop and HBase file system. Technologies of big data processing. Map Reduce and Pig. The R language. Stack of Elastic software products. Recommended literature: Khatskevich G.A. 2002. Statistics. Descriptive Approach. Minsk: Research and Development Institute. Nathan Marz and James Warren. 2017. Great Data. Principles and Practice of Building Scalable Data Processing Systems in Real Time. Moscow: Williams. Leskovets Y., Anand Rajaraman, and Jeffrey D. Ullmann. 2016. Analysis of Large Data Sets. Moscow: DMK Press. 2.3. Project management Course structure Hours Classwork 36 Lectures 16 Workshops 12 Project discussion 8 Independent work 62 Independent development of academic materials on topics 16 Project development 46 Expected academic result Master’s students • Structure of knowledge areas of (a Guide to the Project Management Body of are to know Knowledge (PMBOK) standard and its extension for program projects management; • Values and principles of flexible project management; • Role models in software development teams; • Scrum basics; • Possibilities of specialized software applied to project management; and Structure of a technological maturity model in Capability Maturity Model Integration (CMMI) software development. Master’s students • To create the project plan using recommendations of the PMBOK standard; are to be able • To develop requirements to project content; • To develop requirements to the structure of a design team; • To develop a model of the project using specialized software for project management; and • To assess project team efficiency during software development using Scrum approach. Course content History of project management. ‘Waterfall’ approach. Method of control points. ‘Stages and gates’ approach. History of the creation of the PMI project management institute and the PMBOK standard. Extension of the PMBOK standard for a software development area. Iterative and incremental models of development. ‘Flexible’ approaches to software development. The Agile manifesto. The Crystal methodology. Pair programming. Refactoring. Dynamic systems development methodology (DSDM). Integration of ‘waterfall’ and ‘flexible’ approaches in project management in the PMI PMBOK standard of the 6th edition. 34 Concept of Scrum. Scrum values. The principles of empiricism in Scrum: transparency, inspection, and adaptation. Roles in design teams of scrum: product owner, development team, Scrum master. Team size in Scrum. Scrum artifacts. Project backlog. Sprint. Sprint backlog. Increment. Readiness. Scrum poker. Retrospective. Certification in Scrum. The principle of transparency and project visualization Scrum board. Design of Scrum board structure. Chart of combustion. Principles of work distribution. Creation of project model using the software. Software possibilities on the example of Microsoft Project. Scaling in software development project management. Scalable Agile approaches in software development project management. Principles of SAFe. Principles of Nexus. Software development life-cycle management. Principles of DevOps. Maintenance processes of I-systems. Information Technology Infrastructure Library (ITIL) and IT service management (ITSM). ‘Program of projects’ and ‘portfolio of projects’ concepts. Recommended literature: Project Management Institute. 2014. A Guide to the Project Management Body of Knowledge: (the RMRS Manual): [translation]. 5th ed.M: Olimp-Business. 586 p. Sutherland, D. Scrum. 2016. The Revolutionary Method of Project Management. Moscow: Mann, Ivanov, and Ferber. 288 p. Royce, U. 2014. Project Management Software Development. Moscow: Lori. 424 p. 2.4. Software-oriented data storage systems and modern DBMS Course structure Hours Classwork 48 Lectures 16 Workshop (webinar) 12 Consultations on practice 12 Project discussion 8 Independent work 102 Independent development of academic materials on topics 36 Practice accomplishment 42 Project development 24 Expected academic result Master’s student is • Principles of data storage systems creation; to know • Main classes of program-oriented data storage systems; • Advantages and drawbacks of program-oriented data storage systems; • Program-oriented data storage systems application areas; • DBMS data construction principles and basic models; • Methodologies of DBMS design; and • Information security methods in DBMS. Master’s student is • To assess usage reasonability of various architectures of program-oriented storage to be able information systems and to carry out their conceptual design; • To choose data models and DBMS for applied tasks solving; and • To apply database management systems for applied tasks solving. Course content Concept of the program-oriented data storage systems. Efficiency of their use. 35 Basic classes of program-oriented data storage systems. Hardware-software solutions are repeating architecture of classical data storage arrays. Independent software for solutions based on x86 servers. Object data storages. Hadoop-compatible storages. Systems of disk resources virtualization. Object principle of data storage organization. Data backup in object storages. Dynamic storage algorithms. Advantages and drawbacks of object storages. Basic application areas of program-oriented data storage systems: test environments and development environments, backup and archive data storage, systems of public/corporate cloud storage (Dropbox and so on), public/corporate data web hosting, systems of unstructured data machine processing (social networks, statistical data processing, and so on), storages of virtual machines, BLOB storages of information systems secondary data. File systems and databases. Models of DBMS data. Hierarchical, network, relational, object-oriented, object-relational data models. NoSQL. Methodologies of conceptual, logical and physical database design. Information security in databases. Storage of unstructured data. Formats for unstructured data storage and exchange. Recommended literature: G. Somasundarama and A. Shrivastava. ed. 2017. From Data Storage to Information Management. 2nd edition. St. Petersburg: Peter. 544 p. Date K.J. 2008. Introduction to Database Systems. Moscow: Williams. Connolly T. and Begg C. 2017. Database. Design, Implementation, and Maintenance. Theory and Practice. 3rd ed. Moscow: Williams. 2.5. Technologies and templates for information system integration Course structure Hours Classwork 44 Lectures 16 Workshop (webinar) 8 Consultations on projects and their discussion 20 Independent work 78 Independent development of academic materials on topics 22 Project development 56 Expected academic result Master’s students • Main ways of corporate systems integration; are to know • Main integration templates based on messages; • Technologies of web services; • Service-oriented architecture; and • XML, YAML, and JSON formats. Master’s students • To reasonably choose interaction technologies in developing the integrated system are to be able concept and • To apply basic ways and templates of information system integration at integrated system architecture design stage. Course content Corporate systems integration issue. Integration purposes. Types of integration tasks. Technologies of integration: file exchange, general database, remote call, asynchronous messaging. Solutions based on messaging. Message, message channel, channels and filters, router and message translator. Message endpoint. 36 Types of messaging channels. Guaranteed delivery. Channel adapter. Messaging bridge. Message bus. Construction and structure of messages. Message routing. Simple and compound routers. Architectural templates. Content-based router. Message filter. Dynamic router. List of recipients. Splitter. Aggregator. Order converter. Message processor. Mailing assembly. Routing map. Process manager. Message broker. Transformation of messages. Envelope cover. Contents dilator. Contents filter. Receipt. Normalizer. Message exchange endpoints. Message sending and receiving patterns. Patterns of message consumers. Messaging gateway. System management patterns. Management bus. Roundabout way. Branch. Delivery record. Message storage. Intellectual Proxy. Web-services technology-based solutions. Advantages and drawbacks of web-services. Service-oriented architectures. XML, YAML, and JSON. Recommended literature: Gregory Hop and Bobby Woolf. 2007. Corporate Application Integration Templates. Moscow: Williams. Newcome E. 2003. Web Services: XML, WSDL, SOAP, and UDDL. St. Petersburg. 2.6. Data structures and algorithms Course structure Hours Classwork 40 Lectures 16 Workshop (webinar) 8 Consultations on practice 8 Project discussion 8 Independent work 80 Independent development of academic materials on topics 24 Practice accomplishment 24 Project development 32 Expected academic result Master’s students • Modern data structures, features of their efficient use; are to know • Approaches to efficient algorithm development in applied tasks solving; • Basic principles of algorithm efficiency assessment; and • Models and methods of applied tasks solving. Master’s students • To build mathematical models and correctly choose data structures for efficient are to be able algorithm realization; • To use formal methods at algorithm labor input assessment; and • To solve practical tasks using data structures. Course content Dimensions of a task. Algorithm labor input: the best case, the worst case, average labor input, average assessment of a group of operations labor input. Ο, Ω, Θ asymptotics. Polynomial and nonpolynomial algorithms. Examples. Algorithm design and analysis. Concept of the recurrent equation. Correct and wrong recurrent equations. Full recurrent equation. Main methods of recurrent equations solution. Assessment of a recurrent equation solution. Ways of information ordering: main algorithms of internal and external sorting and their labor input. 37 Data structures. Complex data structures: binary heaps, binomial heaps, and Fibonacci's heaps. Sets. Various ways of set representation and accomplishment of basic operations over them. Application of sets for tasks solution. Search organization. Search trees. Basic operations over them and their lowest labor input. Hash tables and hash functions. Collisions. Methods of collision resolution. Open and closed hashing. Graph models. Methods of graphs and trees storage. Use of modern data structures in main graph algorithms. Labor input of algorithms. Strategy of task solution. ‘Divide and rule’ principle, dynamic coding, gradient algorithms. Approximate algorithms and heuristics. Heuristics types: local search, algorithms of local improvement, genetic algorithms, taboo search. Recommended literature: Aho, Alfred V., John E. Hopcroft, and Jeffrey D. Ullman. 2000. Data Structures, and Algorithms. Moscow: Williams. 384 p. Aho, Alfred V., John E. Hopcroft, and, Jeffrey D. Ullman. 1979. Construction and Analysis of Computational Algorithms. Moscow: Mir. 536 p. Kotov, V., E. Sobolevskaya, and A. Tolstikov. 2011. Algorithms and Data Structures. Moscow: BSU. 264 p. 2.7. Applied methods of optimal design Course structure Hours Classwork 40 Lectures 16 Workshop (webinar) 8 Consultations on practice 8 Project discussion 8 Independent work 80 Independent development of academic materials on topics 24 Practice accomplishment 24 Project development 32 Expected academic result Master’s students • Modern data structures, features of their efficient use; are to know • Approaches to efficient algorithm development in applied tasks solving; • Basic principles of algorithm efficiency assessment; and • Models and methods of applied tasks solving. Master’s students • To build mathematical models and correctly choose data structures for efficient are to be able algorithm realization; • To use formal methods at algorithm labor input assessment; and • To solve practical tasks using data structures. Course content Subject and method of the discipline. Stages of task setting and solution of optimum design. Options and outcomes. Comparison of options and ways of preference system description. Linear programming (LP) task setting. Standard form of a LP task. Simplex method algorithm. LP computing methods. 38 Network and transport models. Basic concepts of a network model. Main classes of network tasks (creation of the minimum basic tree, search of the shortest route, a task about the maximum stream, finding of a stream of the lowest cost, network planning) and methods of their solution. Transport models (transportation, inventory management, distribution of resources). Evolutionary algorithms of integer coding task solution. Evolutionary algorithms of integer coding task solution and their realization with a computer. Genetic algorithms: application areas and principles of design. Nonlinear coding. Classification and optimality conditions of mathematical task models of optimum design. Unconditional minimization of one variable functions. Unconditional minimization of n variable functions. Methods of direct search. Gradient methods. Method of consecutive unconditional minimization. Research of task solution sensitivity of nonlinear coding. Multicriteria optimization tasks and vector criteria of optimality. Global minimum search issue in multi- extreme tasks. Heuristic algorithms of global minimum search. Application of casual evolutionary process models for multi-extreme and multicriteria optimization task solving. Recommended literature: Taha, H. Introduction to the Study of Operations. 2005. Moscow: Williams Publishing House. 912 p. Attetkov, A. V. Optimization Methods. 2003. Moscow: MSTU. 440 p. Chang, C.W. Advances in Evolutionary Algorithms. Theory, Design and Practice. Berlin-Heidelberg: Springer- Verlag. 171 p. 2.8. Object-oriented analysis and design Course structure Hours Classwork 40 Lectures 16 Workshop (webinar) 8 Consultations on practice 8 Project discussion 8 Independent work 80 Independent development of academic materials on topics 24 Practice accomplishment 24 Project development 32 Expected academic result Master’s student is • Graphic notation of UML systems modeling language; to know • Methods of object-oriented analysis of a program system application area; • Methods of object-oriented program system design; • Design patterns used in program systems development; • Main architectural templates used in program systems development; and • Basic processes of program systems development. Master’s student is • To simulate functional requirements to a program system; to be able • To develop a program system, logical model; • To develop a program system component model; and • To apply architectural templates in program system architecture development. Course content Concept of the system. System structure and architecture. System behavior and state. System model. Object-oriented system model. System analysis and synthesis. System design. 39 Purpose of the UML. UML elements and charts. Rules of the UML. General mechanisms of the UML. Classification of models and charts. Program system. Architecture of a program system. Analysis of subject domain. Process of program system development. Roles of project performers. Development of functional requirements to a program system. Functional model of a program system. Chart of application options. Functional architecture of a program system. Modeling of system dynamic behavior. Activity chart. State chart. Sequence chart. Communication chart. Modeling of the interaction of system objects. Synchronous and asynchronous interaction of objects. Interaction patterns. Modeling of program system logical organization. Chart of classes. Types of relations between classes. Class Stereotypes. Conceptual model of a program system. Design patterns. Modeling of logical system architecture. Modeling of system physical organization. Component chart. Component specification. Relations between components. Modeling of component system architecture. Processes of program systems development: waterfall, spiral, and incremental models. Unified process. Design based on usage options. Model-based design. Design through testing. Recommended literature: Larman, K. 2013. Application of UML and Design Patterns. Introduction to Object-oriented Analysis and Design. 3rd ed. Translated from English. Moscow: Williams Publishing House. 736 p. Matseashek, L. A. Analysis of Requirements and Design of Systems. Development of Information Systems using UML. Translated from English. Moscow: Williams Publishing House. 432 p. 2.9. Discrete mathematics Course structure Hours Classwork 40 Lectures 16 Workshop (webinar) 8 Consultations on practice 8 Project discussion 8 Independent work 80 Independent development of academic materials on topics 24 Practice accomplishment 24 Project development 32 Expected academic result Master’s student is • Basic concepts and methods of discrete mathematics: logical calculations, functional to know systems with operations, discrete structures (graphs, networks, codes), disjunctive normal forms and schemes from functional elements, the theory of combinations. Master’s student is • To apply math symbols for expressing quantitative and qualitative relations of objects; to be able • To apply the device of discrete mathematics while developing and analyzing personal design decisions; and • To solve standard problems of the discipline, the theory of graphs, formal languages, and automatic machines. Course content Language, logic, and calculation of predicates. Basics of formal languages. Logic algebra. Functions of logic algebra. Statement calculation. 40 Language of predicate calculation. Subject constants, variable, functional constants, predicate constants, capacity (number of arguments, dimension). Informal concepts of function and relation. Theory of sets. Concept of a class of abstract sets as the subject domain of the theory of sets. Constants, predicates, and functions of the theory of sets. Relations and functions in the theory of sets. Semigroups, groups, lattices. Functions. Reverse relation. One-to-one correspondence. Superposition and iteration of relations. Concept of injection, surjection, and bijection. Area of definition, set of values. Streamlining. Properties of orders. Linear orders. Maximum and minimum, smallest and greatest elements. Full orders. Preorders. Final full orders. Properties of equivalence relations. Classes of relations contiguity, equivalence classes, factorization, quotient set, splitting into equivalence classes. Basic concepts and tasks of the theory of graphs. Types of graphs, ways of a graph setting. Graph Isomorphism. Connectivity. Planarity. Planarity criteria. Trees. Types and properties of trees. Algorithms of graph tops evasion. An algorithm of graph splitting into subgraphs of the set type. Fundamentals of combination theory. Shifts, placements, combinations, combinations with repetitions, splittings, coverings. Recurrence relations. Concept of course-of-value functions. Automatic machines. Recognition of automatic machines sets. Automatic machines networks, their analysis, and synthesis. Program realization of logical functions and automatic machines. Recommended literature: Kuznetsov, O. 2014. Discrete Mathematics for Engineers. Moscow: Lan. 400 p. Graham, R., D. Knut, and O. Patashnik. 2016. Specific Mathematics. 2nd edition. Moscow: Williams Publishing House. Hopcroft, J., Motvani R., and Ulman J. 2002. Introduction to the Theory of Automata, Languages, Computations. Moscow: Williams Publishing House. 2.10. Cloud technologies Course structure Hours Classwork 44 Lectures 16 Workshop (webinar) 12 Consultations on practice 8 Project discussion 8 Independent work 94 Independent development of academic materials on topics 24 Practice accomplishment 24 Project development 46 Expected academic result Master’s students • Basic concepts and terminology of cloud technology; are to know • Cloud technology application areas; • The concept of cloud computing; • Basic principles of cloud computing, principles and methods of application development for cloud systems using various platforms; and • Security, scaling, expansion, backup issues in the context of cloud infrastructure. Master’s students • To design information systems based on cloud technology and are to be able • To simulate cloud infrastructures on public cloud services platforms. 41 Course content Introduction. History of basic types of high-performance computing, trends in modern infrastructure decisions development. Infrastructure consolidation. Virtualization. Services. Main development directions. Main types of virtualization. Review of virtualization software products. Virtual machine. Virtualization of servers. Virtualization of applications. Virtualization of representations (jobs). Kinds of hypervisor architecture. Introduction to concepts of cloud computing. Review of a cloud computing paradigm. Architecture of cloud systems. Models of cloud expansion of private cloud, open cloud, hybrid cloud, public cloud. Main models of cloud computing services. Differences between cloud and cluster computing. Advantages and drawbacks of cloud computing. Review of existing services and platforms. Solutions of leading vendors: Microsoft, Amazon, Google. Cloud system development on OpenStack platform. Technologies of cloud computing. Programming methods, bases of application cloud system administration. Security, scaling, expansion, backup issues in the context of cloud infrastructure. Advantages of cloud infrastructure in application scaling. Features of emergency recovery in cloud environment. Recommended literature: 1. Buyya R. Cloud Computing: Principles and Paradigm, / Rajkumar Buyya, James Broberg, Andrzej Gościński // John Wiley&Sons. 2011 2. Tim O'Reilly, «Web 2.0 and Cloud Computing» [Electronic resource] – Mode of access: http://radar.oreilly.com/2008/10/web-20-and-cloud-computing.html. 3. MacLeod G. "The best-protected secret of clouds" [Electronic resource] – Mode of access: http://technorati.com/posts/lv3vwaZ9hNoZ4b0%3D?reactions 2.11. Open source software platforms Course structure Hours Classwork 44 Lectures 16 Workshop (webinar) 12 Consultations on practice 8 Project discussion 8 Independent work 94 Independent development of academic materials on topics 24 Practice accomplishment 24 Project development 46 Expected academic result Master’s students • Basic concepts and terminology of cloud technology; are to know • Cloud technology application areas; • The concept of cloud computing; • Basic principles of cloud computing, principles, and methods of application development for cloud systems using various platforms; and • Security, scaling, expansion, backup issues in the context of cloud infrastructure. Master’s students • To design information systems based on cloud technologies and are to be able • To simulate cloud infrastructures on public cloud services platforms. Course content 42 Concept of an open source software. Artifacts of the open source software: an open source code, development processes, communications, interaction processes in the community of developers and users. Open source software development processes. Open source and closed source (proprietary) development projects. Closed source components and commercial versions. Communities of developers and interaction with them. Distribution and support of the open source software. Support models: support by the developer community, commercial support. Cost of open source software possession. Mechanisms of the open source software quality ensuring: open joint development, testing of changes, and additions by the developer community. Positive effects and risks of the open source software use in system design and development. Stack of the open source software. Workstation software: operating systems, office, and other applications. Server platforms based on Linux. Open source code server operating systems. Terms of their use. Open source code DBMS: MySQL and PostgreSQL. Open source code means of virtualization. Cloud platforms for corporate data-processing centers. OpenStack platform. Recommended literature: Rao, M. N. 2015. Fundamentals of Open Source Software. PHI Learning Private. Vaquero, L., J. Caceres, and H. Hierro. 2012. Open Source Cloud Computing Systems: Practices and Paradigms. Information Science Reference. Ward, B. 2016. Internal Device Linux. St. Petersburg. Zhdanov, S., Manyakhin V., and Matrosov V. 2014. Operating Systems, Networks and Internet Technologies. Moscow: Academia. 2.12. Deep learning Course structure Hours Classwork 44 Lectures 16 Workshop (webinar) 12 Consultations on practice 8 Project discussion 8 Independent work 94 Independent development of academic materials on topics 24 Practice accomplishment 24 Project development 46 Expected academic result Master’s student is • Basic principles of building and educating of deep learning networks. to know Master’s student is • To efficiently design and build classifiers based on deep learning networks. to be able Course content Machine learning: logistic regression, stochastic optimization. Loading and data preprocessing, selection of parameters, cross-validation, quality assessment. Training of perceptrons, return error distribution procedure, receiving sign vectors for words, object recognition with neural networks. Optimization: learning process acceleration, recurrent neural networks. Improvement of neural networks generalizing 43 ability, a combination of neural networks. Hopfield’s networks and Boltzmann's machines. Restricted Boltzmann machines, Deep Belief neural networks. Deep neural networks: the architecture of deep neural networks, hyperparameters selection, regularization. Convolutional neural networks: introduction and basic principles of work, convolutional neural networks architecture, regularization and parameter selection, image processing and other applications. Deep neural networks for work with texts: major approaches to text processing in machine learning, recurrent neural networks, Long short-term memory (LSTM), regularization. Application of deep learning networks for solving practical tasks. Introduction to natural languages and deep learning processing, simple vector representations of words: word2vec, GloVe, advanced vector representations of words, neural networks for named entities recognition, practical issues of network design, learning and selection of parameters. Machine translation based on recursive neural networks. Convolutional neural networks in text classifying, speech recognition and machine translation, seq2seq models, the future of neural networks for natural languages processing: dynamic memory networks. Graphic images recognition using convolutional neural deep learning networks. Principles of deep learning network architecture for object localization at the graphic representation. Semantic pixel-by-pixel segmentation using deep learning networks. Recognition of sequences of events using deep learning networks. Recommended literature: Goodfellow, J., I. Benjio, and A. Courville. 2017. Deep Learning = Deep Learning. Moscow: DMK Press.652 p. ISBN 978-5-97060-554-7. Hastie, T., R. Tibshirani, and J. Friedman. 2014. The Elements of Statistical Learning. Springer. 739 p. Bishop, C. M. 2006. Pattern Recognition and Machine Learning. Springer. 738 p. Merkov, A. B. 2011. Pattern Recognition: Introduction to Statistical Learning Methods. 2.13. Information technology and IТ risk management Course structure Hours Classwork 42 Lectures 15 Workshop (webinar) 14 Project discussion 12 Independent work 78 Independent development of academic materials on topics 32 Project development 46 Expected academic result Master’s students • Basic risks in information systems design and are to know • Risk sources and risk management principles at different life-cycle stages of information systems. Master’s students • To choose technologies and project solutions in the designed information system as to are to be able minimize risks and • To assess outcomes of decisions made at the stage of information system concept design. Course content Concept of the life cycle of an information system. Information system design, development, and maintenance ecosystem. Evolution of an information system. 44 Concept of risk. Life cycle of risk. Standard risks in information system life cycle. Risks at information systems design. Approach to risk analysis. Decision making based on risk analysis. Evolution of risks within information system evolution. Iterativity of information system life-cycle stages. Change of requirements during information system evolution as the main source of risks. Methods of changes and risks management. Architecture of decision considering subsequent changes of requirements. Choice of approach to information system design/realization: insourcing, development, services, and business processes outsourcing. Risk identification and analysis choosing the approach. Types of projects: new development, development by the existing platform, the introduction of a ready- made decision, integration. Risk identification and analysis choosing the type of projects. Risks in system architecture design. Risks at user interfaces design. Risks at database design. Criteria for choosing the design decisions: terms, price, the probability of success, risk—taking into account requirements to operation process and further system support. Information systems IT risks management. Forecasting of consequences for the design decision made at information system evolution. Decision assessment. Economic assessment. Total cost of ownership. Time assessment. Monitoring of the revealed risks. Recommended literature: Lutai, L. 2013. Methods and IT Synthesis of the Component Structure of the Technical System. Lambert Academic Publishing. 172 p. DeMarco, T. 2005. Waltzing with Bears: Risk Management in Software Development Projects. Moscow: Company. P.M. Office. 208 p. Capers Jones, T. 1994. Assessment, and Control of Software Risks. Yourdon Press. 619 p. Zhdanov S., Manyakhin V., and Matrosov V. 2014. Operating Systems, Networks, and Internet Technologies. Moscow: Academia. 2.14. User behavior and interaction design Course structure Hours Classwork 50 Lectures 16 Workshop (webinar) 18 Project discussion 16 Independent work 100 Independent development of academic materials on topics 32 Project development 68 Expected academic result Master’s student is • Methodological basics of human-computer interaction and levels of its design in to know person-computer systems; • Methodological basics of user interface development in the context of human- computer interaction; • Main stages of interaction and interface process design, quality, and assessment criteria; • Major factors influencing human-computer interaction quality; and • Features of interaction and interface design in various information and communication environments. 45 Master’s student is • To perform interaction and user interface concept design for various system classes; to be able • To assess results of interaction and user interface design; and • To assess visual project solution, interface and navigation design, information elements arrangement. Course content Bases of human-computer interaction. Interaction as a scientific category. Essence, components and information exchange levels. Ergotic system and its components. Information model of the ergotic system. Classification of human-computer systems. Methodological problems of ergotic systems interface design. Classical, post-classical and post-nonclassical approaches to interface design. Levels of human-computer systems interaction design. Interaction design methodology. User interface design. User interface design as a factor influencing the quality of interaction. Forms of the simplest user interface. Natural user interfaces. Latest achievements in visualization technologies, in handwritten and voice input. Three-dimensional (spatial) interface. User interface assessment: general provisions. Interface quality criteria. Usability testing. User as an information management system. Psychophysiological basics of user activity as an operator. Storage and processing of information, decision-making, cognitive processes. Cognitive abilities of people. Mechanisms of activity mental regulation. User mistakes at interaction. Interaction design in various information and communication environments (web, built-in systems, games, and multimedia, virtual environments). Recommended literature: Cooper, A. 2009. The Essentials of Interaction Design. Moscow: The Symbol. 688 p. Sergeev, S.F., F. I. Paderno, and N. A. Nazarenko. 2011. Introduction to the Design of Intelligent Interfaces: Textbook. St. Petersburg: Publishing House SPbSU ITMO. 108 p. Ruskin, Jeff. 2013. Interface: New Directions in the Design of Computer Systems. Moscow: The Symbol. 272 p. 2.15. Business analysis basics in software development Course structure Hours Classwork 50 Lectures 16 Workshop (webinar) 18 Project discussion 16 Independent work 100 Independent development of academic materials on topics 32 Project development 68 Expected academic result Master’s students • BA methodological bases in software development and are to know • BA basic notions and stages. Master’s students • to carry out analysis of business processes at the enterprise; are to be able • to reveal demands and to set goals; • to develop and assess solutions (changes in the current state of the organization); and • to collect and analyze information, to define, analyze, and document requirements; Course content 46 Prerequisites for BA emerging. Key concepts in BA. Role of a ‘business analyst’. Competences and tools of a business analyst. BA in project life cycle. BA in product life cycle. Analysis of an enterprise. Introduction data, business processes, organizational structure. Concept and main characteristics of business processes. Analysis of enterprise business processes structure. Enterprise environment, market, industry. Detection of requirements and goal setting. Detection of requirements and problems. Analysis of requirements and identification of real problems. Goal setting. Decision development and their assessment. Approaching to definition of ways to achieve the goals and decision development. Decision description at the top level. Assessment of decisions. Information and requirements collection. Basic scheme of information collection. Information sources. Techniques of information collection. Communication within the project. Holding of productive meetings. Rules of effective communication. Information and requirements analysis. Basic scheme of information and requirements analysis. Concept of the requirement and their main properties. Analysis of requirements. Basics of requirements modeling. Basics of requirements prototyping. Requirements documenting. Documenting purposes. Types of documents within the project. Document about an image and borders: general information and document structure. User stories: concept and structure, grouping, and management. Recommended literature: Kornipaev I. 2013. Requirements for Software: Recommendations for Collection and Documentation. Moscow: Publishing House. "The Book on Demand."118 p. Barilenko V. 2013. Fundamentals of Business Analysis: a Tutorial. Moscow: Knorus. Paklin, N.B., and V. I. Oreshkov. 2013. Business Intelligence: from Data to Knowledge. St. Petersburg. 2.16. Internet of things Course structure Hours Classwork 38 Lectures 12 Workshop (webinar) 14 Project discussion 12 Independent work 80 Independent development of academic materials on topics 32 Project development 48 Expected academic result Master’s students • Functioning and architecture principles of ’Internet of things’ systems; are to know • ‘Internet of things’ application areas; • ‘Internet of things’ basic technologies; and • Security problems in ‘Internet of things’ systems and how to solve them. Master’s students • To design complex integrated systems using ‘Internet of things’ methodology and are to be able technology. Course content ‘Internet of things’ as one of the key technologies in the modern digital society and economy. Interrelation of people, processes, data, and things, ‘Internet of Everything’. 47 Architecture of ‘Internet of things’ systems. Main requirements to ‘Internet of things’ systems. Choosing the scenario for ‘Internet of things’ system functioning depending on the requirements, examples. Concept of ‘cross-machine interaction’. Leading players in the ‘Internet of things’ system market. Review of the existing platforms of ‘Internet of things’. Examples. Organizing of services based on ‘Internet of things’. Consumer and industrial ‘Internet of things’. Monetization of services based on ‘Internet of things’. Main business models. ‘Internet of things’ in automobile and transport sectors. Mojio platform. Case study of SAP, Hertz, and Nokia. Perspective directions of ‘Internet of things’ using in the automobile sector. ‘Internet of things’ in industry and production. ‘Industrial Internet of things’. Predictive service. Integration of ‘Internet of things’ systems with corporate enterprise resource planning (ERP) systems. ‘The clever city’. ‘The clever building’. ‘Internet of things’ in health care. ‘Internet of things’ in power industry. ‘Internet of things’ in retail trade. ‘Internet of things’ in agriculture. Other ‘Internet of things’ application areas. Technologies of ‘Internet of things’. Technologies of wireless networks with low energy consumption. Use of mobile communication networks for ‘Internet of things’. Wireless sensor networks. Protocols of applied level for ’Internet of things’. Protocols for ‘clever device’ control. Hardware maintenance of ‘Internet of things’. Technologies of ‘clever devices’. Specialized operating systems. Cloud computing in ‘Internet of things’. Concept of ‘fog computing’. Safety and standardization in the sphere of ‘Internet of things’. Analysis of threats for ‘Internet of things’ systems. Model of the malefactor. Classification of ‘Internet of things’ vulnerabilities. Security principles for ‘Internet of things’ systems. Standardization in the sphere of ‘Internet of things’. Existing working standards of the The Institute of Electrical and Electronics Engineers (IEEE), ISO/IEC organizations, and so on. Recommended literature: Geng, H. 2017. Internet of Things and Data Analytics Handbook. John Wiley and Sons. 800 p. Gringard, S. 2016. Internet of Things. The Future is Already Here. Moscow: Alpina Publisher. 188 p. Kranz, M. 2016. Building the Internet of Things: Implement New Business Models, Disrupt Competitors, Transform Your Industry. John Wiley and Sons. 272 p. Hussain, F. 2017. Internet of Things: Building Blocks and Business Models. Springer. 73 p. 48 Annex 2. Educational standards of higher education institutions. Major 1-31 81 14 Complex integrated system design 1. Application The standard is applied to educational and program documentation development of the postgraduate training program with profound training providing the master's training program), for methodical documentation, academic editions, information and analytical materials, and higher education quality control systems. The standard is compulsory for application in all higher education institutions of Belarus implementing master’s postgraduate training programs. 2. Legal references The references to the following legal acts are used to present educational standards: • ГОСТ 31279-2004 Innovation activity. Terms and definitions • СТБ ИСО 9000-2015 Quality management system. Basic provisions and vocabulary (henceforth СТБ ИСО 9000-2015) • ОКРБ 011-2009 the ‘Majors and Qualifications’ National Classifier of the Republic of Belarus • ОКРБ 005-2011 the ‘Types of Economic Activities’ National Classifier of the Republic of Belarus • The Code on Education of the Republic of Belarus (the National Registry of Legal Acts of the Republic of Belarus, 2011, No. 13, 2/1795) (henceforth the Code on Education of the Republic of Belarus); • The Law of the Republic of Belarus ‘On information, informatization and information security’ November 10, 2008, No. 455-З. Amendments and supplements: The Law of the Republic of Belarus of January 4, 2014, No. 102-З; The Law of the Republic of Belarus of May 11, 2016, No. 362 -З. (henceforth the Law of the Republic of Belarus ‘On information, informatization and information security’). 3. General terms and definitions The present educational standards employ the terms set in the Code on Education of the Republic of Belarus as well as the following terms with the appropriate definitions: Credit - the numerical way to express the labor input of the student’s study based on the training results. Innovations - new or advanced technologies, types of goods or services as well as organizational and technical solutions of production, administrative, commercial, or other character promoting technologies, products, and services to the market (ГОСТ 31279-2004). Innovation activities - activities that result in the innovations creation and implementation (ГОСТ 31279- 2004). Integrated system - a complex system with information, functional, and other interrelations between its subsystems and external objects. Information system - a set of databanks, information technologies, and a suit (suits) of program technical means (he Law of Republic of Belarus ‘On information, informatization and information security’). 49 Information technology - a set of processes, information search, receiving, transfer, collecting, processing, accumulation, storage, distribution and/or providing methods and use of information and information security (the Law of Republic of Belarus ‘On information, informatization, and information security’). Information - information about people, objects, facts, events, phenomena, and processes regardless of a form of their representation (the Law of Republic of Belarus ‘On information, informatization and information security’). Qualification - knowledge, abilities, and skills necessary for a particular profession and certified with a document (СТБ 22.0.1-96). Competency - the expressed ability to apply knowledge and skills (СТБ ИСО 9000-2006). Competence - knowledge, abilities, and skills necessary for solving theoretical and practical tasks. Conceptual design - the initial stage of design where basic principles of the created object’s organization and functioning are decided upon and where preliminary adjustment is made to the possible implementation of the developed solutions. Master’s graduate - a person who mastered the content of the postgraduate training program that imparts knowledge, abilities, and skills through scientific, pedagogical, research, and teaching activities providing the master’s degree, or the postgraduate training program with profound training providing the master’s degree. Master’s thesis - an independently performed scientific research work devoted to the solution of a theoretical, experimental, or application-oriented task of the appropriate field of professional activities verifying the personal contribution of the author to science and (or) practical knowledge. Quality is ensuring - the coordinated activity of the organization’s administrative board and the staff team aimed at implementation of requirements to СТБ ИСО 9000-2006 quality. Design - a part of a system life-cycle stage, the process of the system (or its part) architecture, components, interfaces, and other characteristics specification (ISO 24765). The project—an integral set of models, properties, or characteristics described in the form suitable for the system implementation — is the result of design. Complex system – a set of interacting units (subsystems) combined into a whole according to certain principles and/or interconnected with set relations as in the compound they gain new properties that are absent when separated and cannot be reduced to their original properties. Major - type of professional activities demanding particular knowledge, skills, and competences obtained through training and practical experience. 4. General provisions 4.1. General description of the major The ‘Complex Integrated System Design’ major 1-31 81 14 according to ОКРБ 011-2009 is a part of the ‘Natural sciences’ G education profile, the ‘Natural sciences’ 31 training direction, the ‘Innovation activity’ 31 81 group of majors (profound training) and provides the degree of ‘Master of System Analysis and Design’. 4.2. Educational requirements for applicants of the master’s postgraduate The required educational background of those applying for the master’s program is a bachelor’s degree in any of the following majors: • 25 Economy • 27 Economy and production organization 50 • 38 Appliances • 39 Radio-electronic equipment • 40 Informatics and computer hardware • 41 Equipment components • 43 Power • 45 Communications • 53 Automation • 55 Intellectual systems • 58 Ergonomics • 98 Information security Groups of majors: • 02 05 Teaching of physical and mathematical disciplines • 26 02 Business management • 26 03 Information resources management • 26 04 Innovative processes management • 31 03 Mathematical sciences • 95 02 Military and engineering activity Those graduating with a bachelor’s degree in other majors are also eligible for entry based on the results of supplementary examinations on academic disciplines; their list is created by a higher education institution based on the guidance of the academic association on training in natural sciences. 4.3. Master’s postgraduate forms of training A master’s postgraduate allows the following forms of training: full time (daytime, evening), part time. 4.4. Duration of master’s postgraduate training The prescriptive term for full-time master’s postgraduate training is two years. The term for the evening and part-time master’s postgraduate training is also two years. 5. Professional activities of the master 5.1. Area of the professional activities of the master Key areas of professional activities of the master are as follows: • 62 Computer coding, consulting and other adjacent services • 63 Activities in the field of information service • 721 Research and development in natural and technical science • 8542 Higher education 5.2. Objects of the professional activities of the master The objects of the professional activities of the master are as follows: 51 • Complex integrated systems intended to solve tasks from various subject areas within the development of an information society and digital economy (e-government, e-trading, electronic economy, electronic health care, and so on) • Processes of analysis and conceptual design of these systems 5.3. Types of the professional activities of the master The master shall have competences in the following types of activities: • Scientific research • Design and construction • Organizational and administrative • Engineering and innovative • Scientific, pedagogical, academic, and methodical activities 5.4. Tasks of the professional activities of the master A master shall be prepared to solve the following tasks through their professional activities: • Analysis of existing and designed systems and definition of structural links between elements of the studied systems on the basis of general scientific, experimental, natural science, mathematical, and statistical methods (research activities) • Construction and analysis of mathematical, information, and program models of complex integrated systems (research activities) • Predesign inspection of creating objects of complex integrated systems including analysis of the subject area, definition of the concept of its development, and development of offers on reengineering of business processes (design and construction activities) • Conceptual design of complex integrated systems: determination of main functional and architectural concepts, components, interfaces, and technologies considering social, economic, and ecological consequences of the designed systems’ implementation (design and construction activities) • Executive team organization and management (organizational and management activities) • Analysis of the business of the organization associated with complex integrated system design and development in various subject areas, development of proposals for efficiency increase of information technologies application (organizational and management activities) • Development of proposals on application and enhancement of information technologies and methods of conceptual design for the creation of complex integrated systems in new subject areas and applications arising during development of information society and digitalization of economy (engineering and innovative activities) • Development of plans and programs for the organization of innovative activities, the technical and economic reasoning of creative projects in professional activity (engineering and innovative activities) • Scientific research management of student work, development of academic and methodical facilities (scientific, pedagogical, academic, and methodical activities) 52 5.5. Options for the master to continue training The master shall be prepared to learn the training program of the further postgraduate studies mainly on the following majors: 01.01.09 Discrete mathematics and mathematical cybernetics 05.13.01 Systems analysis, information control, and processing (branches) 05.13.06 Technological processes and productions automation and control (branches) 05.13.10 Management in social and economic systems 05.13.11 Mathematical and software maintenance of computers, sets, and computer networks 05.13.12 Systems of design automation (branches) 05.13.18 Mathematical simulation/modeling, numerical methods and program sets 05.13.17 Theoretical fundamentals of informatics 6. Requirements for the master’s competence 6.1. Structure of the master’s competences Mastering of the master’s training program shall provide the following groups of competences: • Academic competences - profound scientific-theoretical, methodological knowledge and research skills providing development of research projects or solution of scientific research problems, innovative activity, and continuous self-education • Social and personal competences - personal qualities and abilities to adhere to social, cultural, and moral values; abilities for social, cross-cultural interaction, and critical thinking; social responsibility allowing to solve social and professional, organizational and administrative, and educational problems • Professional competences - profound knowledge of specific disciplines and ability to solve challenging professional tasks, problems of research activity, to develop and implement innovative projects, to carry out continuous professional self-improvement 6.2. Requirements for academic competences of the master The master shall have AC-1. Skills for dependent scientific research activity (analysis, comparison, systematization, abstraction, modeling, check of data reliability, decision making, and so on) and readiness to generate and use the new ideas; AC-2. Methodological knowledge and research abilities providing the solution of problems of research, administrative, technological, design, and innovative activity; and AC-3. The ability for independent acquisition of new knowledge and skills including in the fields of knowledge not directly connected to the area of activity. 6.3. Requirements for social and personal competences of the master The master shall SPC-1. Be able to consider social and moral-ethical standards in professional social activity; SPC-2. Be capable of cooperation and teamwork; SPC-3. Have communicative abilities for work in the cross-disciplinary and international environment; and 53 SPC-4. Develop a creative approach to professional and socially significant activity. 6.4. Requirements for the master’s professional competences The master shall have the following professional competences: Scientific and research activities PC-1. To competently conduct scientific research on system analysis, modeling, and conceptual design of complex integrated systems Design and construction activities PC-2. To carry out predesign inspection of the subject area of the complex integrated system creation, to formulate requirements for these systems PC-3. To carry out the conceptual design of complex integrated systems taking into account requirements of information security PC-4. To estimate the efficiency of the developed design decisions and possibility and consequences of their implementation Organizational and management activities PC-5. To take reasonable administrative decisions PC-6. To master and implement administrative innovations in professional activity PC-7. To develop technical documentation taking into account the established requirements and forms of reporting Engineering and innovative activities PC-8. To search, systematize, and analyze information in the promising directions of informatization in different fields of state and society activity PC-9. To define purposes of innovations and methods of their achievement PC-10. To choose reasonably the hardware, equipment, and application-oriented software for design, scientific, and research activities PC-11. To choose hardware-software platforms and architectural solutions for the designed systems Scientific, academic, and methodological activities PC-12. To lead the research work of students PC-13. To develop and apply modern educational and methodical facilities for organization of practical and research work of students 7. Requirements for the training program and content of the academic training documentation 7.1. Structure of the academic training documentation The higher education postgraduate training program with profound training providing the master’s degree includes the following academic training documentation: • The standard curriculum of the major • The curriculum of a higher education institution for the major • The training programs of a higher education institution on academic disciplines • The internship program 54 • The individual working plan of a master’s student 7.2. General requirements for the development of academic training documentation • The maximum amount of academic load for a master’s student shall not exceed 54 periods a week including all types of in-class and outdoor work. • A number of compulsory in-class activities set by the higher education institution considering the major shall not be more than 18 academic periods a week. For foreign master’s students, the higher education institution can increase the amount of in-class work. • Time to prepare for the examinations is included in the number of periods for individual work on the discipline. • For part-time training, the number of in-class activities shall be not less than 60 periods an academic year (including consultations and other forms of in-class activity). 7.3. Requirements for the schedule of the training process The approximate number of weeks on the activity types for the postgraduate training program with profound training providing the master’s degree in full-time higher education is set in accordance with Table 2.1. Table 2.1: Schedule of the training process Types of activity, set by the curriculum Duration of training (weeks) Theoretical studies and scientific research work 59 Exam sessions 9 Internship 10 Final certification 5 Vacations 13 Total 96 Source: BSU. 7.4. Requirements for the standard curriculum structure of the major The standard curriculum for master’s students in the postgraduate training program with profound practice providing the master’s degree is developed according to the structure provided in Table 2.2. Table 2.2: Standard curriculum structure of the major Amount of work (hours) Codes of Types of master’s activity, Including No. Credits competences discipline cycles, disciplines Total Individual cultivated Classwork work 1. Cycle of disciplines of special 2,712 894 1,818 72 AC-1 - 3; training SPC-1 - 4; PC-1 - 11 1.1 Governmental component 890 292 598 24 АC-1 - 3; PC-1 - 11 1.1.1 Modern theory of information 150 50 100 4 АC-1 - 3; PC-1, 3, 4, 10, 11 1.1.2 Software design and development 150 50 100 4 АC-1 - 3; technologies PC-1 - 4, 7 55 Amount of work (hours) Codes of Types of master’s activity, Including No. Credits competences discipline cycles, disciplines Total Individual cultivated Classwork work 1.1.3 Complex security of information 150 50 100 4 АC-3; technologies and systems PC-1, 3 - 11 1.1.4 Computer system architectures 150 50 100 4 АC-1-3; PC-1-4,8-11 1.1.5 Theory of complex systems and 150 50 100 4 АC-1 - 3; system analysis PC-1 - 4 1.1.5 Methodologies and technologies 140 42 98 4 АC-1 - 3; for conceptual design PC-1 - 11 1.2 Higher education institution 1,822 602 1,220 48 АC-1 - 3 component SPC-1 - 4 PC-1 - 11 2. Scientific research work 960 960 27 АC-1 - 3 PC-1, 13 3. Internship 540 540 14 SPC-1 - 4; PC-1 - 13 4. Final certification 270 270 7 PC-1 - 11 Total 4,482 894 3,588 120 Source: BSU. Remarks: 1. A set of disciplines of the governmental component is defined by the educational and methodical association on higher education in the amount of 30–35 percent of a specialized training discipline cycle. The higher education institution component makes up 65–70 percent. 2. The sum of credits for full-time higher education graduation shall be equal to 120 for two years of training. 3. Codes of the formed competences are specified according to Sections 6.2, 6.3, 6.4 of the present standard. • The curriculum of a higher education institution is developed on the basis of the major standard curriculum where the higher education institution is empowered to change the amount of the master’s student work on different types of activities, the amount of discipline cycles, the number of hours for mastering the academic disciplines (within 10 percent), not exceeding the maximum week load for the master’s student and regarding the requirements of the present standard for the contents of the postgraduate training program. • The optional disciplines of the master’s student choice are recommended in the amount of up to 50 percent of the number of the class periods/hours from a higher education institution component when developing the major curriculum of a higher education institution. • Training of foreign citizens and persons without citizenship who are constantly living in Belarus as well as foreigners and individuals without citizenship of the Belarussian nationality who are constantly living in the territory of foreign states and also foreign citizens and individuals without citizenship but with refugee status or with shelter in Belarus (henceforth, foreign citizens) who have graduated from foreign higher education institutions can be carried out by individual curricula. 56 • The necessity of different curricula for the citizens of Belarus who have graduated from foreign higher education institutions and the foreign citizens who have graduated from the higher education institutions of Belarus is defined by every higher education institution independently. • The head of a higher education institution approves the head of the scientific research work of a master’s student and the topic of the master’s thesis. 7.5. Requirements for the development of a master’s student’s individual working plan • The individual working plan of the master’s student is developed by the head of scientific research work of the student together with the student, is discussed at the meeting of the main (releasing) department/chamber, and is approved by the head of a higher education institution (the deputy head of academic work of a higher education institution). • The individual working plan of the master’s student is developed on the basis of the curriculum of a higher education institution on the corresponding postgraduate major, establishes the list and the sequence of the studied disciplines and the amount of the academic load, and includes the program of the master’s thesis preparation, practical training, scientific research work, forms, and terms of reporting. 7.6. Requirements for a compulsory minimum of training programs content and competences in academic disciplines The governmental component disciplines of a specialized training Applied theory of information As a result of teaching a discipline, the master’s student shall: know: • various approaches for defining the concept of information; • methods and for determining the amount of information; • methods of analog-to-digital transformation of signals; • ways of digital data transmission; • methods of data compression; and • primary methods of data encryption; be able to: • calculate the amount of information in messages; • apply Kotelnikov's theorem for solving of tasks on analog-to-digital and digital-to-analog conversion of signals; and • evaluate the required parameters of communication links, storage and data handling systems for solving of application-oriented tasks of information storage, transmission, and processing. Software design and development technologies As a result of taking a discipline, the master’s student shall: know: • software life-cycle models; • different design approaches of program systems; • main architectural styles; and 57 • application of design patterns; be able to: • build cascade, spiral, incremental and human resources (HR)-models of software; • put into practice an object-oriented paradigm and build UML charts of a software product; and • estimate need and efficiency of design patterns used in software products development. Integrated security of information technologies and systems As a result of taking a discipline, the master’s student shall: know: • basic concepts of computer security; • legal documents on computer security; • design and assessment methodologies of compliance with information security systems; and • standards of information security; be able to: • apply design and evaluation methods of compliance with information security systems at complex integrated system design; • develop tasks for security; • develop security policies; and • apply standards and standard and legal documents of information security in professional activity. Computer system architectures As a result of taking a discipline, the master’s student shall: know: • hardware and software components of computer systems and interfaces of their interaction; • basic approaches to the organization of computer system components; • main parallel architectures of computer systems; • levels and methods of the organization of interaction of computer system processes; • assessment of methods of computer system efficiency; and • methods to ensure the computer systems’ reliability and safety; be able to: • develop an architecture of a computer system; • manage computer system interaction; • assess the computer system efficiency; and • ensure the computer systems’ reliability and safety. Theory of complex systems and system analysis As a result of taking a discipline, the master’s student shall: know: • fundamental concepts of system analysis; 58 • methods of system modeling; • principles of functioning of automatic control systems; and • basics of the theory of dynamic systems; be able to: • investigate systems by system analysis methods • carry out modeling/simulation of complex systems; and • apply methods of the system analysis at information systems design and development in various subject areas. Methodologies and technologies of conceptual design As a result of taking a discipline, the master’s student shall: know: • the meaning of conceptual design and its place in the system life-cycle model; and • the methods of subject area modeling and concept synthesis of the designed system; be able to: • carry out predesign inspection of informatization objects; • build models of the subject area according to the IDEF0 and IDEF1 methodologies applying the corresponding tools; and • carry out the synthesis of complex systems conceptual solutions. Higher education institution training programs in the subjects set the content of disciplines of a higher education institution component and the requirements for competences on these disciplines. Training programs of a higher education institution on the disciplines according to the individual work plan of the master’s student set the content of optional disciplines for master’s students and the requirements for competences on these disciplines. Training programs of a higher education institution on the disciplines shall reflect the achievements of the institution’s scientific and pedagogical schools in particular sections of the relevant sciences. 7.7. Requirements for the research work contents of a master’s student The main (releasing) department develops requirements for the research work of the master’s student. 7.8. Requirements for internship contents and organization The higher education postgraduate program with profound training for a master's degree provides the organization of major internship in the divisions dealing with issues of ionizing and nonionizing radiation use. The internship is aimed at fixing knowledge and abilities obtained during theoretical training, at mastering skills of ionizing and nonionizing radiation use for implemetayion complex projects in medical sphere and at innovative projects implementation. For part-time master’s students, the major internship can be reduced to four weeks. 8. Requirements for organizing educational process 8.1. Requirements for educational process staff ensuring 59 The postgraduate research and pedagogical staff shall • Have higher education corresponding to the profile of the taught disciplines and the corresponding scientific qualification (an academic degree and/or an academic status)5; • Be engaged in scientific and/or research and methodical activity; • Undergo advance training at least once every five years; • Own modern educational, including information, technologies necessary for proper organizing of the educational and research processes; and • Have personal qualities and competences allowing efficient organization of educational and pedagogical work with master’s students. 8.2. Requirements for ensuring educational process resources The institution of higher education shall have • Material and technical resources necessary for organizing the educational and research processes, independent work, and personality development of a master’s student and • Means of education required for the postgraduate program implementation (devices, equipment, tools, educational visual aids, computers, computer networks, audiovisual means, and other material objects). 8.3. Requirements for ensuring scientific and methodical activities of the educational process Provision of scientific and methodical activities of the educational process has to conform to the following requirements: • Disciplines of the curriculum shall be equipped with modern educational, scientific, other literature, training programs, educational and methodical documentation, and educational and methodical information and analytical materials. • Access to library stocks, electronic tutorials, and electronic information resources (local access, remote access) on all disciplines shall be provided to each master’s student. Ensuring access to scientific and methodical activities shall be focused on development and deployment into the educational process of innovative educational technologies adequate to competency-based approaches (variable models of managed independent work of master’s students, educational and methodical complexes [including electronic], modular and rating systems of training, tests and other systems to assess the level of competences of master’s students, and so on). 8.4. Requirements for individual work organization Requirements for the organization of individual work are established by the legislation of Belarus. 8.5. Requirements for ideological and pedagogical work activity Requirements for the organization of ideological and pedagogical work are established according to the recommendations on organizing the ideological and pedagogical work in higher education institutions and the program planning pedagogical documentation. 8.6. General requirements for quality control of training and competence diagnostics means 5 The leading experts in the field without academic degree or any academic status but with practical experience not less than 10 years can also be employed for implementation of the educational process within the higher education postgraduate program with profound training providing the master's degree. 60 • Quality control of training is exercised by current and final certification of master’s students. • Diagnostic tools for assessing the level of competence formation are established by the central (releasing) department. 9. Requirements for the final certification 9.1. General requirements The final certification that master’s graduates receive on mastering contents of the higher education postgraduate program that provides profound training and the master's degree allows defining theoretical and practical readiness of the master’s graduate to perform scientific research, organizational and administrative, and engineering and innovative activities as well as physical and technical maintenance of health care organizations (as the first launch of the program is primarily aimed at implementation of the project in the healthcare). 9.2. Requirements for the master’s thesis • Requirements for structure, contents, volume, and order of the master’s thesis defense are defined by the higher education institution on the basis of the present standard and the rules of certification of students, cadets, and listeners who master contents of educational programs of higher education. • While preparing the master’s thesis, the master’s student is to show, relying on the gained knowledge and academic, social, personal, and professional competences, the ability to solve problems of professional activity and capacity to integrate scientific knowledge to scientifically reason their point of view in a modern way. • The master’s thesis shall be directed to solving any theoretical, experimental, or application- oriented tasks connected to increasing the efficiency of physical methods used in medicine. The master’s thesis shall contain an abstract and a scientific research part reflecting professional competences of the master’s graduate. The scientific research part shall constitute at least 70 percent of the volume of the thesis (as the first launch of the program is primarily aimed at implementation of the project in the healthcare). References 1. The Code on Education of the Republic of Belarus, Jan. 13, 2011, No. 243-3 // Nat. Registry of Legal Acts of the Rep. of Belarus. ― 2011. ― No. 13. ― 2/1795. 2. The National Classifier of the Republic of Belarus. Majors and qualifications: ОКРБ 011-2009. - Intro. 01.07.09. – Minsk: Мin. of Education of the Rep. of Belarus: RIHS, 2009. ― 418 p. 61 Annex 3. Curriculum APPROVED Rector of the Belarusian State University ________________________________S.V. Ablameyko «____» ____________2017. Registration No._______________________ CURRICULUM on major of postgraduate education (master’s degree) Major: 1-31 81 14 Complex Integrated System Design Degree: Master of System Analysis and Design Term of training ― 2 years (full-time form of education) І. Schedule of educational process Months Approximate amount of academic work No. of weeks Type of activity according to the curriculum (approximately) Total hours Classwork hoursa Independent work 01–18 September–January (18) Theoretical studies and practical research work 972 304 668 19–21 January (3) Exam session 162 162 22–23 February (2) Vacations 24–40 February–June (17) Theoretical studies and practical research work 918 286 632 41–43 June (3) Exam session 162 162 44–52 July–August (9) Vacations 53–70 September–January (18) Theoretical studies and practical research work 972 304 668 71–73 January (3) Exam session 162 162 74–75 January–February (2) Vacations 76–89 February–April (16) Practical training (internship) 540 540 76–89 February–May (16) Practical research work 324 324 90–96 May–June (6) Final certification 270 270 Total 4482 894 3588 62 Note: a. Higher education institutions are empowered to transfer up to 90 percent of classroom studies provided by the standard curriculum into the guided individual work of the master’s student as well as hold classroom studies in the mode of remote interaction between teachers and master’s students (online lecturing with Internet broadcasting, online workshops, consultations, and so on). ІІ. Plan of educational process Type of Distribution over Amount of work Distribution over semesters activity of the semesters (hours)6 master’s 4th semester 1st semester 2nd semester 3rd semester No. student, including 4 weeks Tota 18 weeks 18 weeks 18 weeks discipline Exam Credit l cycles, class ind class ind credit class ind credit class ind credit class ind credit disciplines . h. . w. . h. . w. s . h. . w. s . h. . w. s . h. . w. s 1. Cycle of 2712 894 1818 304 614 24 286 590 24 304 614 24 0 0 0 disciplines of special training 1.1 Governmental 1,1,2,2,2, 890 292 598 100 200 8 150 300 12 42 98 4 0 0 0 component 3 1.1.1 Applied 1 150 50 100 50 100 4 theory of information 1.1.2 Software 1 150 50 100 50 100 4 design and development technologies 1.1.3 Integrated 2 150 50 100 50 100 4 security of information technologies and systems 1.1.4 Computer 2 150 50 100 50 100 4 system architectures 1.1.5 Theory of 2 150 50 100 50 100 4 complex 6 Academic hours 63 Type of Distribution over Amount of work Distribution over semesters activity of the semesters (hours)6 master’s 4th semester 1st semester 2nd semester 3rd semester No. student, including 4 weeks Tota 18 weeks 18 weeks 18 weeks discipline Exam Credit l cycles, class ind class ind credit class ind credit class ind credit class ind credit disciplines . h. . w. . h. . w. s . h. . w. s . h. . w. s . h. . w. s systems and system analysis 1.1.6 Methodologie 3 140 42 98 42 98 4 s and technologies of conceptual design 1.2 Component of 1,1,2,3,3, 1,1,1,2,2,3,3, 1822 602 1220 204 414 16 136 290 12 262 516 20 0 0 0 the higher 3 3 education establishment 1.2.1 Applied 1 44 96 4 statistics and Big Data analysis 1.2.2 Project 1 36 62 2 management 1.2.3 Optional 1 40 80 3 course (Mathematics and Informatics) 1.2.4 Optional 1 40 80 3 course (Mathematics and Informatics) 1.2.4 Intelligent 1 44 96 4 systems and 64 Type of Distribution over Amount of work Distribution over semesters activity of the semesters (hours)6 master’s 4th semester 1st semester 2nd semester 3rd semester No. student, including 4 weeks Tota 18 weeks 18 weeks 18 weeks discipline Exam Credit l cycles, class ind class ind credit class ind credit class ind credit class ind credit disciplines . h. . w. . h. . w. s . h. . w. s . h. . w. s . h. . w. s machine learning 1.2.5 Program 2 48 102 4 oriented data storage systems and modern DBMS 1.2.6 Optional 2 44 94 4 course (Modern information technologies) 1.2.7 Optional 2 44 94 4 course (Modern information technologies) 1.2.8 Optional 3 42 78 3 course (Information security) 1.2.9 Technologies 3 44 78 3 and information system integration templates 1.2.10 Optional 3 50 100 4 course (Complex systems 65 Type of Distribution over Amount of work Distribution over semesters activity of the semesters (hours)6 master’s 4th semester 1st semester 2nd semester 3rd semester No. student, including 4 weeks Tota 18 weeks 18 weeks 18 weeks discipline Exam Credit l cycles, class ind class ind credit class ind credit class ind credit class ind credit disciplines . h. . w. . h. . w. s . h. . w. s . h. . w. s . h. . w. s analysis and design) 1.2.11 Optional 3 50 100 4 course (Complex systems analysis and design) 1.2.12 Optional 3 38 80 3 course (Applied information technologies and systems) 1.2.11 Optional 3 38 80 3 3 course (Applied information technologies and systems) 2. Practical 1,2,3,4 960 960 216 6 204 6 216 6 324 9 research work 3. Internship 4 540 540 540 14 4. Final 270 270 270 7 certification Total 4482 894 3588 304 830 30 286 794 30 304 830 30 0 1134 30 66 III. List of optional courses 1. Mathematics and 2. Modern information 3. Information security 4. Complex systems 5. Applied information informatics technologies analysis and design technologies and systems Discrete mathematics Open source platforms Applied cryptography and hardware- System engineering Bank and insurance systems software information protection facilities Data structure and Cloud technologies Information technologies and IT risk Systems of systems Public administration and e- algorithms management government Applied methods of Deep learning User behavior and Internet of things optimal design interaction design Object-oriented Technical documentation and Cyber-physical systems Electronic economy and e- analysis and design presentations development commerce APPROVED APPROVED APPROVED Vice-rector on Academic Affairs Chief of Head Department of Academic and Scientific Methodological Director of State Institute of Management and Social Work of BSU technologies ______________. __ A.L. Tolstik _____________________ L.М. Huhlyndina _____________________ P.I. Brigadin «____» ______________ 2017. «____» ______________ 2017. «____» ______________ 2017. 67