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Software Engineering TEMPUS (4+1)

1. General information

The MSc curriculum in software engineering is committed to excellence in European-wide software education and training of engineers to deliver high quality and trustworthy software systems that meet the local industrial needs.

General competencies

Ability to work in an interdisciplinary team
Capacity for critical analysis and synthesis
Capacity for applying knowledge in practice
Capacity for generating new ideas (creativity)
Capacity to learn
Decision-making
Knowledge of a second language
Research skills

Specific learning outcomes

Show mastery and critical thinking of the software engineering (SE) knowledge and skills and professional issues necessary to begin practice/research as a software engineer.
Work as individual or as part of a team to develop and deliver high quality software artefacts, being able to analyze its level of quality.
Identify, analyse, and reconcile conflicting project objectives, finding acceptable compromises within limitations of cost, time, knowledge, existing systems and organizations.
Analyze, design and document appropriate solutions in more than one application domains using SE approaches that integrate ethical, social, legal and economic concerns.
Demonstrate an understanding of and critically analyze and apply current theories, models and techniques that provide a basis for problem identification and analysis, software design, development, implementation, verification and documentation.
Demonstrate an appreciation and understanding for the importance of negotiation, effective work habits, leadership and good communication with stakeholders in a typical, industry-strength software environment.
Learn new theories, models, techniques and technologies as they emerge and appreciate the necessity of such continuing professional development.

Offered by: Sts. Cyril and Methodius University - Skopje, Faculty of Computer Science and Engineering – FCSE in collaboration with the University of Novi Sad, Faculty of Natural Sciences and Mathematics, Department of Mathematics and Computer Science
Study programme: Joint MSc curricula in Software Engineering / Tempus JEP 18035
Scientific-research field: Computer Science
Category: Computing
Sub-category: Software and its Engineering, Theory of Computation, Information Systems
The master studies cycle consists of 60 ECTS.
Study duration: 2 semesters
One academic year is divided into two semesters with 30 weeks each (1 semester = 15 weeks)
The first semester is comprised of courses only, while the second semester there is devoted to the final project, i.e. master thesis.
Enrollment requisites: fully completed undergraduate study cycle with a minimum of 240 ECTS with a degree in the fields of computer science and/or computer engineering.
First semester: 5 elective courses divided into two groups: general SE competence and specific SE competence. Student can select at most two from the general SE courses, and at leas from the specific SE courses
Second semester: Final master thesis project that equals 30 ECTS.
1 ECTS = 30 hours of work load.
Contact hours per week is 4.

Degree: Master of computer science in the area of software engineering.

System on chip TEMPUS (4+1)

1. General information

The goal of the system on chip master study programme is to provide top quality European education and training for the ICT engineers. The study programme provides deeper and specialized understanding of the embedded systems and the methodologies for system on chip design. Upon completion of the studies, the engineers are expected to take up responsible business positions in the processes of planning, design and management of embedded systems implemented with various state of the art technologies.

Offered by: Ss. Cyril and Methodius University - Skopje, Faculty of Computer Science and Engineering – FCSE
Study programme: System on chip master studies
Scientific-research field: Engineering and Technology
Category: Electrical engineering, Electronic engineering, Information engineering
Sub-category:Computer hardware andarchitecture
The master studies cycle consists of 60 ECTS.
Study duration: 2 semesters
One academic year is divided into two semesters with 30 weeks each (1 semester = 15 weeks)
The first semester is comprised of courses only, while in the second semester there are fewer courses and the rest of the time is devoted to the final project, i.e. master thesis.
Enrollment requisites: fully completed undergraduate study cycle with a minimum of 240 ECTS with a degree in the fields of computer science and/or computer engineering. In the case of having an appropriate degree with less than 240 ECTS, the student has to enroll the introductory courses first.
Introductory courses: only for students that have obtained less than 240 ECTS. A number of differential introductory courses are offered in order to level up the required competences. Upon successful completion of the introductory courses, the student has the right to continue with the formal master study programme courses in the second year of studies.
First semester: 3 compulsory courses + 2 elective courses (one of the elective courses can be chosen from the courses list offered by the University)
Second semester: 1 compulsory course + 1 elective course (can be chosen from the courses list offered by the University only in the event that this opportunity has not been used in the previous semester) + final master thesis project that equals 18 ECTS.
1 ECTS = 30 hours of work load.
Contact hours per week is 4.

Degree: Master of computer science and engineering in the field of system on chip

2. Studies

Table 1: List of courses for master studies

	Professor	Course	Semester	ECTS
1	assist. prof. Igor Mishkovski	System on chip design techniques	IX	6
2	assoc. prof. Vladimir Trajkovikj	Mobile and embedded systems	IX	6
3		Mandatory general-education course	IX	6
4		Elective course	IX	6
5		Elective course	IX	6
6	assoc. prof. Dimitar Trajanov	Developing software for mobile and embedded systems	X	6
7		Elective course	X	6
General-education courses
1		Research methods and writing techniques	IX	6
2		Project management	IX	6

IT Management (3 +1+1)

IT Management (3 + 1 + 1)

1. General Information

Postgraduate studies in Information Technology Management aim to provide quality and top European education and training of highly educated staff with in-depth knowledge of methods and techniques for managing ICT projects and systems. Upon completion of their studies, these staff will be able to take responsible positions in the processes of planning, design, management and monitoring of ICT projects and systems, including their business aspects.

The program in Management Studies in Information Technology is compatible with the relevant studies offered at most of the world's universities that support this topic and enable student mobility.

Name of the proposer: University "Ss. Cyril and Methodius University in Skopje, Faculty of Information Sciences and Computer Engineering - FINKI
Study Program Name: Information Technology Management
Scientific-research area: 2 technical-technological
Field
The value of postgraduate studies is 60 ECTS credits .
Duration of studies: 2 semesters .
One academic year consists of two semesters lasting 30 weeks (1 semester = 15 weeks).
Admission Requirements : Students in Information Technology Management can enroll in graduate students who have 240 or 180 undergraduate credits.
Introductory layer : Students who have earned less than 240 credits during their studies are offered a set of differential introductory courses. After their successful realization, the student acquires the right to continue with the first semester of postgraduate studies.
First semester: 2 mandatory courses, 2 elective courses in the field.
Second semester: 1 mandatory subject in the field, 1 elective subject in the field and 1 elective subject from the list of UKIM and final project - master's thesis (18 ECTS)
1 ECTS credit corresponds to 30 hours of total work engagement
The number of contact hours is 4

Upon successful completion of the postgraduate studies in Information Technology Management, the successful student will possess the following general abilities and qualifications:

Ability to work in interdisciplinary teams
Power of analysis and synthesis
Power to apply knowledge in practice
Power to generate new ideas (creativity)
Power of learning
Ability to critique and self-critique
Ability to make decisions
Knowledge of English
Research skills

Upon successful completion of the postgraduate studies in Information Technology Management, the successful student will possess the following specific abilities and qualifications:

Knowledge and Understanding

Provides in-depth knowledge and understanding of the theoretical foundations of software and innovation project management, information systems and risk management and other disciplines.

Acquiring the necessary knowledge in the field of management with ICT systems and projects.

Development of advanced skills in planning, design, design, management, testing, and implementation of ICT systems and projects.

Demonstrates a high level of professional competence in the analysis of empirical data in the fields of business, industry, economics and government.

Work with applied projects to manage projects, resources, money and people.

Governs the latest industry standards and best practices, as well as opportunities for improvement and future development in the area.

Applying knowledge and understanding

Can apply knowledge and understanding for professional development in a narrower area of Information Technology Management.

Demonstrates skills and knowledge necessary for the individual to be competent in managing IT systems and projects at a high level.

The competenciesQualify with solid management and technical foundation with the ability to include a selected range of broader aspects of Management in Information Technology and the like that will meet the needs of the professional in this field with constant and rapid development.

In-depth management knowledge required for effective work of ICT manager, independent specialist or member of specialized team.

Ability to evaluate

Demonstrates a commitment to self-improvement and continuous professional development

Demonstrates in-depth knowledge of advanced analysis and design techniques in the fields of Information Technology Management.

Demonstrates knowledge of best practices for improving productivity and mutual understanding in business organizations taking into account personal, social, scientific and ethical aspects.

Demonstrates the ability to make managerial decisions independently and link business practice with application solutions.

Communication Skills

Demonstrates the ability to communicate with colleagues and work in a team through a high level of awareness of the importance and power of communication.

Illustrates effective exchange of information, ideas and reasoned proposals.

Demonstrates high ability to work and lead multidisciplinary teams

Demonstrates ability to plan and manage time at managerial level and professional socialization and conflict resolution.

Recognizes complex organizational structures and the need to restructure them, understands their impact on effectiveness and efficiency in combination with modern technologies.

Learning Skills

Demonstrates an understanding of the basics of research methodology, with the ability to evaluate, design and conduct research in the field, formulate, plan a research project and communicate in depth on a topic.

Demonstrates the ability to reasonably evaluate and generate ideas with creative and critical thinking, mastering new theories, models, techniques and technologies, while appreciating the need for continuous professional development.

Able to select and understand procedures and methods for structuring, consolidating, and handling information and data in an environment.

Has high self-confidence and independence, proactivity and self-awareness to perform and delegate tasks and manage further career.

Acquired title: Master of Information Science and Computer Engineering in Information Technology Management. & Nbsp;

2. Introductory layer

The introductory layer is intended for students who study for less than four years or have earned less than 240 credits from previous studies.

Table 1: List of introductory layer items

	Code	Subject	Weekly fund	Semester	ECTS
1	CSEW501	Management Information Systems *	2 + 2 + 1	winter	6
2	CSEW705	Innovation in ICT *	2 + 1 + 2	winter	6
3		Selected from Table 2		winter	6
4		Selected from Table 2		winter	6
5		Selected from Table 2		winter	6
6	CSES811	Entrepreneurship *	2 + 1 + 2	summer	6
7	CSES634	ICT Project Management *	2 + 2 + 1	summer	6
8		Selected from Table 2		summer	6
9		Selected from Table 2		summer	6
10		Elective **		summer	6

* If the student has passed the course in his / her undergraduate studies, he / she will have to choose another course from the list of elective courses from the introductory layer (Table 2).

** The course can be selected from the list of electives from Table 2 or from the university list of free electives

Table 2: List of introductory electives

	Code	Subject	Weekly fund	Semester	ECTS
1	CSEW528	User support	2 + 1 + 2	winter	6
2	CSEW505	Software requirements analysis	2 + 2 + 1	winter	6
3	CSEW701	Information Systems Analysis and Design	2 + 2 + 2	winter	6
4	CSEW704	Design of integrated systems	2 + 1 + 2	winter	6
5	CSEW511	Software design and architecture	2 + 1 + 2	winter	6
6	CSEW514	Implementation of Free and Open Source Systems	2 + 1 + 2	winter	6
7	CSEW515	Computer Ethics	4 + 0 + 0	winter	6
8	CSEW310	Marketing	2 + 2 + 1	winter	6
9	CSES631	Software quality and testing	2 + 1 + 2	summer	6
10	CSES625	IS development process	2 + 2 + 2	summer	6
11	CSES612	Electronic & Mobile Commerce	2 + 2 + 2	summer	6
12	CSES610	e-Government	2 + 1 + 2	summer	6
13	CSES617	Business Process Modeling	2 + 1 + 2	summer	6
14	CSES606	Geographic Information Systems	2 + 1 + 2	summer	6
15	CSES205	Business and Management	2 + 2 + 1	summer	6
16	CSES628	Service Oriented Architectures	2 + 2 + 2	summer	6
17	UKIM-I	Selection from University list of free courses

After successfully completing all ten courses and achieving 60 credits, the student with previously acquired 180 ECTS credits (or completed three-year studies) continues with the subjects from the second academic year of postgraduate studies.

3. Studies

Table 1: List of Postgraduate Courses

	Code	Item name	Status	Semester	ECTS	П	А	Л
1	ITMW01	Advanced software project management	M	winter	6	2	1	0
2	ITMW02	Advanced ICT Innovation and Entrepreneurship	M	winter	6	2	1	0
3		Elective	E	winter	6
4		Elective	E	winter	6
5		Elective	E	winter	6
6	ITMS01	Advanced Software Requirements Engineering	M	summer	6	2	1	0
7		Elective	E	summer	6
8		Master Thesis	M	summer	18

3.1 Elective Courses

Configure

The student can choose a subject from the list of offered elective subjects from all study programs of the second cycle of studies. The list of offered elective courses can be found at this link.

Табови

Summary

andrea.kulakov@finki.ukim.mk

Summary

(Октомври 2011) Андреа Кулаков заврши гимназија во 1990, на возраст од 16 години, откако успеа на два пати да зема по две школски години во една (7 и 8 одд. и III и IV год. во средно). Потоа се запиша на Електротехнички факултет Скопје и во 1995 година дипломира со највисок просек 9,91 во својата генерација 1990-95. Во 1995 ги почна постдипломските студии по Когнитивни науки на Нов бугарски универзитет во Софија, Бугарија, во мала меѓународна група на студенти со настава на англиски јазик. Студиите ги заврши со одличен успех (5,71 од макс. 6,00). Во јули 1998 ја одбрани својата магистерска теза “Vygovorotsky – An Anticipative and Analogy-making Actor” со одличен успех (5,50), пред пет-члена меѓународна комисија (без менторот). Во 1999 магистерската диплома беше нострифицирана на Електротехнички факултет Скопје. Во текот на 9 месечниот воен рок во 1999 г. беше и демонстратор на Воената академија по предметот „Информатика“. Потоа шест месеци работеше во меѓународната софтверска компанија Мак-Систем, од кои месец и пол беше на обука во Париз, Франција. Од април 2000 г. до септември 2011 г., Андреа Кулаков беше вработен на Институтот за Компјутерска техника и информатика при Електротехнички факултет (подоцна Факултет за електротехника и информациски технологии) Скопје, прво како асистент, а од 2007 г. како доцент. Има предавано повеќе предмети од областите на Вештачка интелигенција, Роботика и Бази на податоци и во прв и во втор циклус на студии. Во јуни 2005 година ја освои наградата за истражувања кои водат до одбрана на докторска дисертација од најголемото друштво на електро инженери ИЕЕЕ, поточно од нивното Друштво за Компјутерска интелигенција (http://ieee-cis.org/edu/research/ подолу, во делот за 2005). Во декември 2006 година ја одбрани својата докторска теза “Управување со податоци кај безжични сензорски мрежи” на Факултетот за електротехника и информациски технологии. Бил истражувач и главен истражувач на неколку домашни и меѓународни проекти, финансирани од МОН, од програмите ТЕМПУС и од Рамковната програма 6 на Европската Унија. Во 2008 го основа напредното технолошко Друштво за истражување и развој НИ ТЕКНА – Интелигентни технологии (www.ni-tekna.com), кое работи на развој на напредни решенија каде е неопходна примената на техниките од Вештачката интелигенција. Во март 2011 беше еден од основачите на Факултетот за информатички науки и компјутерско инженерство Скопје. Во Август 2011 беше избран за раководител на Институтот за интелигентни системи при Факултетот за информатички науки и компјутерско инженерство. Одговорен е за неколку предмети на додипломски и магистерски студии од областите вештачка интелигенција, анализа на податоци, роботика и безжични сензорски мрежи. Има објавено преку 60 научни труда на меѓународни конференции и во меѓународни списанија, како и поглавје во книга. Неговите истражувања се фокусирани на областите: роботика, деловна интелигенција, обработка на слика и звук и други подобласти на когнитивни науки и вештачка интелигенција. Покрај мајчиниот македонски, зборува течно и англиски, српски и бугарски, а се служи и со германски, француски, руски и словенечки јазик.

Рецензија - ЛИНК.
Одлука за избор - ЛИНК

Publications

Име на трудот	Место	Држава
A Kind of Mind: Consciousness and AI	in Consciousness Research Abstracts Book, Tucson III, Arizona, 50
A Model for Agile Computer – Integrated Business Systems, Manufacturing Agility and Hybrid Automation-II	of The Sixth International Conference on Human Aspects of Advanced Manufacturing: Agility and Hybrid Automation, IEA Press	Hong Kong
Investigating Perception in Humans Inhabiting Simple Virtual Environments: An Enactivist View	Cognitive Science Conference on Perception, Consciousness and Art, Vrije Universitaet in Bruxelles
Virtual Classroom and Virtual Laboratory	Proceedings of 20th World Congress on Open Learning and Distance Education	Germany
An agent based model as a marketing consultant of companies	IEEE International Conference on Systems, Man, and Cybernetics (SMC2001), pp. 3113-3117	Arizona
Structure, Inner Values, Hierarchies, and Stages: Essentials for Developmental Robot Architecture	in Proceedings of the 2nd International Workshop on Epigenetic Robotics, pp. 63-70	Sweden
A Model of an Expectancy-Driven and Analogy-Making Actor	Proceedings of the IEEE, Computer Society, 2nd International Conference on Development and Learning	Massachusetts
Incorporating ICT into Education in Macedonia	Proceedings of the UNESCO International Sub-Regional Seminar: The Use of Distance Education and Information and Communication Technologies in Teacher Education: Trends, Policy and Strategy Considerations	Ukraine
Interactivist approach to representation in epigenetic agents	Proceedings of the 3rd International Workshop on Epigenetic Robotics	Sweden
Web-access to the Library IT System at ETF (FEI) and MF (FMI)	Proceedings of ETAI 2003	Macedonia
MapInfo Based Infrastructure - presentation and updating	Proceedings of the ICEST 2004	Macedonia
Single Exponential Smoothing Method and Neural Network in One Method for Time Series Prediction	Proc. of IEEE Int. Conf. on Cybernetics and Intelligent Systems	Singapore
Tracking of unusual events in wireless sensor networks based on artificial neural-networks algorithms	Proceedings of International Conference on Information Technology: Coding and Computing	USA
Distributed Algorithm for a Mobile Wireless Sensor Network for Optimal Coverage of Non-stationary Signals	Web Proceedings of the First Workshop on Spatial Stochastic Modeling of Wireless Networks held in conjunction with IEEE WiOpt 2005	Italy
Implementing artificial neural-networks in wireless sensor networks, Proceedings of IEEE Sarnoff Symposium on Advances in Wired and Wireless Communications	Proceedings of IEEE Sarnoff Symposium on Advances in Wired and Wireless Communications	USA
Data mining in wireless sensor networks based on artificial neural-networks algorithms	Proceedings of Workshop on Data Mining in Sensor Networks in conjunction with 2005 SIAM International Conference on Data-Mining	USA
Intelligent data aggregation in sensor networks using artificial neural-networks algorithms	Technical Proceedings of the 2005 NSTI Nanotechnology Conference and Trade Show, Volume 3, pp. 427 – 430, Nanotech 2005	USA
Application of wavelet neural-networks in wireless sensor networks	Proceedings of 6th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing	USA
Distributed data processing in wireless sensor networks based on artificial neural-networks algorithms	Proceedings of The 10th IEEE Symposium on Computers and Communications	Spain
Pocket PC Web – Access to the Library IT System	Proceedings of 27th International Conference on Information Technology Interfaces - ITI 2005	Croatia
Learning patterns in wireless sensor networks based on wavelet neural-networks,	Proceedings of the First International Workshop on Heterogeneous Wireless Sensor Networks, held in conjunction with the 11th IEEE International Conference on Parallel and Distributed Systems	Japan
Modelling cortical plasticity in natural sensory systems	Epigenetic Robotics Conference	Japan
Integrating ART into scalable cognitive architecture	Poster at Epigenetic Robotics Conference	Japan
Mobile and Pocket Pc Web-Access to the Library IS as a Part of the Advanced Education	Proceedings of the Eigth IASTED International Conference Computers and Advanced Technology in Education	Aruba
Intelligent Data Acquisition and Processing Using Wavelet Neural-Networks	Proceedings of the 3rd IEEE Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications	Bulgaria
GPRS and WAP–Access to the Library IT System	Proceedings of ETAI 2005	Macedonia
A Robust Platform Supporting Interactivist Agent Architecture: Progress Report	Interactivist Summer Institute	South Carolina
Mobile Multimedia for Engineering Education in Signal Processing	Proceedings of the 9th UICEE Annual Conference on Engineering Education	Oman
Efficient Data Management in Wireless Sensor Networks using Artificial Neural Networks	Final report for the 2005 Walter Karplus Summer Research Grant by the IEEE Computation Intelligence Society
Interactivism in artificial intelligence (AI) and intelligent robotics	New Ideas in Psychology, Elsevier
On Curiosity in Intelligent Robotic Systems	AAAI Fall Symposia	USA
Emergence of Higher Order Motivational Systems in Artificial Agents	Book of Abstracts, Interactivist Summer Institute	France
An Autonomous Mental Development Architecture Implemented in a Scalable Database System	Book of Abstracts, Interactivist Summer Institute	France
Intelligent Wireless Sensor Networks Using FuzzyART Neural-Networks	of the IEEE Symposium on Computers and Communications	Portugal
HCI for m-Learning in Image Processing by Handhelds, Human Interface and the Management of Information	Interacting in Information Environments, Lecture Notes in Computer Science, Springer, Volume 4558, pp. 299-308
A System for Data Management in Wireless Sensor Networks	ETAI 2007	Macedonia
Inductive Logic Programming and Embodied Agents: Possibilities and Limitations	International Journal of Agent Technologies and Systems (IJATS), IGI Publishing, Inaugural Issue, pp 34-49
Experiments in Data Management for Wireless Sensor Networks	Second International Conference on Sensor Technologies and Applications, pp 191-195, SENSORCOMM	France
K. Trivodaliev, S. Kalajdziski, A. Kulakov, D. Davcev, G. Mirceva	Proceedings of IASTED International Conference on Artificial Intelligence and Soft Computing	Spain
Stojkoska B., Davcev D., Kulakov A.	Proceedings of The Fifth International Conference on Soft Computing as Transdisciplinary Science and Technology	France
SGNG Protein Classifier by matching 3D structures	Proceedings of The 4th International Workshop on Hybrid Artificial Intelligence Systems,	Spain
Learning and Position Estimation of a Mobile Robot in an Indoor Environment using FuzzyART Neural Network	IEEE/ASME International Conference on Advanced Intelligent Mechatronics
Inductive Logic Programming (ILP) and Reasoning by Analogy in Context of Embodied Robot Learning	Proceedings of ICT Innovations Conference,	Macedonia
System for Integrated Financial Data Based on Data Services	Proceedings of ICT Innovations Conference	Macedonia
Credit Risk Management through Client Classification by using K-Means and the Decision Tree	Proceedings of ICT Innovations Conference	Macedonia
The Role of Artificial Neural Networks in Detection of Pulmonary Functional Abnormalities	Engineering Review, Vol. 29 No. 2, pp. 1-11
Modified Growing Neural Gas Algorithm for Faster Convergence on Signal Distribution Sudden Change,	Procedings of XXII International Symposium on Information, Communication and Automation Technologies
Position estimation of mobile robots using unsupervised learning algorithms	Proceedings of ICT Innovations Conference	Macedonia
System for prediction of the winner in a sports game	Proceedings of ICT Innovations Conference	Macedonia
Modeling attention within a complete cognitive architecture	Book Chapter in Roda C., Ed., Attention Support in Digital Environments, Cambridge University Press,

Intelligent systems (4+1)

1. General Information

Postgraduate studies in intelligent systems aim to provide top scientific and research staff to meet the growing demand for highly qualified engineers capable of overcoming the most challenging development, research and process problems. Students in this study program gain knowledge that provides them with great professional flexibility and a wide selection of jobs wherever there is a need to apply problem-solving skills, as well as critical thinking skills, which they will use to solve complex problems. which are in the domain of intelligent systems. Students enrolling and graduating in this field are highly sought after in companies and research centers. In addition to being trained to participate in the development, implementation and maintenance of a variety of applications in the field of intelligent systems, including the business domain, they will have the necessary basis to pursue doctoral studies, as well as to participate in interdisciplinary science projects. and technology.

Name of the proposer: University "Ss. Cyril and Methodius University in Skopje, Faculty of Information Sciences and Computer Engineering - FINKI
Course Title: Second Cycle Academic Studies in Intelligent Systems
Scientific-research area: technical-technological / natural mathematical
Field: Computer Science and Informatics / Informatics
Areas: Artificial Intelligence , Intelligent Systems, Databases, Numerical Analysis , < / Algorithms , Information Processing, Data Processing, Robotics, Other .
The value of postgraduate studies is 60 ECTS or 120 ECTS credits.
Duration of studies: 2 or 4 semesters .
One academic year consists of two semesters lasting 30 weeks (1 semester = 15 weeks).
Admission Requirements : According to the competition announced by the university, completed undergraduate studies in information science, computer or related fields with a minimum of 240 credits. For study directions that carry less than 240 credits, exams offered in the introductory layer are added.
Introductory layer : Students who have earned less than 240 credits during their studies are offered a set of differential introductory courses. After their successful realization, the student acquires the right to continue with the first semester of postgraduate studies.
First semester: 3 Mandatory courses and 2 electives, one of which may be from the University list.
Second semester : 2 electives, one of which can be from the University list (only if in the first semester the subjects are selected at the Faculty level) and a final project - a master's thesis of 18 ECTS. / li>
1 ECTS credit corresponds to 30 hours of total employment.
The number of contact hours is 4.
The academic title or degree obtained after graduation is

-Master of Information Science and Computer Engineering in Intelligent Systems

2. Studies

Table 3: List of Postgraduate Courses

РБ	Subject	Semester	M / E	ECTS
1	Modeling and fusing unstructured data	IX	M	6
2	Advanced Artificial Intelligence and Machine Learning Topics	IX	M	6
3	Modern intelligent systems	IX	M	6
4	Selected from Table 4	IX	E	6
5	Selected from Table 4	IX	E	6
6	Selected from Table 4	X	E	6
7	Selected from Table 4	X	E	6
8	Master Thesis	X	M	18

Table 4 shows the electives from the Intelligent Systems study program. In addition to these courses, the student can choose from all elective courses, defined for all study programs, from the second cycle that are serviced by the faculty. It is allowed to choose one elective course from the university list of free elective courses.

Table 4: Electives

РБ	Subject	Semester	ECTS	Fund hours
1	Analysis and design of information systems	IX	6	4 + 0 + 0 + 0
2	Mobile web services	IX	6	4 + 0 + 0 + 0
3	Algorithms and programming in robotics	IX	6	4 + 0 + 0 + 0
4	Collective Intelligence	IX	6	4 + 0 + 0 + 0
5	Intelligent user interfaces	IX	6	4 + 0 + 0 + 0
6	Introduction to Financial Engineering	IX	6	4 + 0 + 0 + 0
7	Ambient intelligence	IX	6	4 + 0 + 0 + 0
8	Data-based business decision-making systems	IX	6	4 + 0 + 0 + 0
9	Robot systems	IX	6	4 + 0 + 0 + 0
10	Content based indexing and search	IX	6	4 + 0 + 0 + 0
11	Evolutionary calculation	X	6	4 + 0 + 0 + 0
12	Agent-based modeling	X	6	4 + 0 + 0 + 0
13	Knowledge-based information systems	X	6	4 + 0 + 0 + 0
14	Computational game theory	X	6	4 + 0 + 0 + 0
15	Representation and approximate knowledge discovery	X	6	4 + 0 + 0 + 0
16	Human-robot interaction	X	6	4 + 0 + 0 + 0
17	Computationalparadigms in the Internet of Things	X	6	4 + 0 + 0 + 0
18	Mathematical methods in robotics	X	6	4 + 0 + 0 + 0
19	Collaborative computer systems	X	6	4 + 0 + 0 + 0
20	Sensor-robotic systems	X	6	4 + 0 + 0 + 0
21	Intelligent mobile applications	X	6	4 + 0 + 0 + 0
22	Multimodal interaction	X	6	4 + 0 + 0 + 0
23	Discovering knowledge in big graph data	X	6	4 + 0 + 0 + 0

The student can choose a subject from the list of offered elective courses from all study programs of the second cycle of studies. The list of offered electives can be found on this link .

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Software Engineering TEMPUS (4+1)

System on chip TEMPUS (4+1)

System on chip TEMPUS (4+1)

Open Call for Deep Tech Startups - Join the TECHSIGHT Support Program!

What does the TECHSIGHT support program offer?

1.Experts and knowledge

2.Collaborative learning

3.Targeted information and opportunities

4.Investment readiness and market integration

When and how?

Who are we looking for?

How to apply?

Be part of the European deep tech community!

About the TECHSIGHT Project

AI Instructor

About TeamLift

About the Role

What You’ll Do

What You Bring

Why Join TeamLift

IT Management (3 +1+1)

IT Management (3 + 1 + 1)

3.1 Elective Courses

Табови

Summary

д-р Андреа Кулаков

Intelligent systems (4+1)

ЛОКАЦИЈА

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Languages

Search results

System on chip TEMPUS (4+1)

Open Call for Deep Tech Startups - Join the TECHSIGHT Support Program!

What does the TECHSIGHT support program offer?

1.Experts and knowledge

2.Collaborative learning

3.Targeted information and opportunities

4.Investment readiness and market integration

When and how?

Who are we looking for?

How to apply?

Be part of the European deep tech community!

About the TECHSIGHT Project

AI Instructor

About TeamLift

About the Role

What You’ll Do

What You Bring

Why Join TeamLift

IT Management (3 + 1 + 1)

3.1 Elective Courses

Табови

Summary

д-р Андреа Кулаков