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Georgina Mircheva Ph.D.

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Address
Faculty of Computer Science and Engineering
"Rugjer Boshkovikj" 16
P.O. Box 393
1000 Skopje, Republic of Macedonia
 
 
Phone
+389 2/ 3070-377, Dean's office
+389 2/ 3088-292, Student affairs office 
+389 2/ 3088-222, Fax number 
 
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You can also use the contact form to contact us.
 
 

Гости од компанијата KIWI на ден 12.09.2018 во Амфитеатарот на ФИНКИ од 16 часот ќе одржат гостинско предавање на тема: Data engineering showcase: delivering clean and reliable data.

Ги покануваме студентите на ФИНКИ да земат активно учество во настанот и објавуваме дека дружењето на темите од областа на Data Science ќе продолжи на meetup настанот во Cineplexx за кои повеќе информации можете да најдете тука.

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Табови

Andreja Naumoski Ph.D.

Табови

Bojan Ilijoski M.Sc.

Табови

Nevena Ackovska Ph.D.

Табови

Natasha Ilievska Ph.D.

Табови

Andrea Kulakov Ph.D.

Intelligent Systems Engineering (4+1)

Intelligent Systems Engineering (4+1)

1. General information
The science of building artificial intelligent systems takes the central place in the engineering sciences. There are two main approaches in developing artificial intelligent systems: machines that incorporate intelligence – robots, and one that starts with biological systems and leads towards artificial being – bioinformatics and bioengineering. The Intelligent System Engineering is the place where students can understand and develop intelligent systems in solving real-life problems. 
  • Offered by: Ss. Cyril and Methodius University - Skopje, Faculty of Computer Science and Engineering – FCSE
  • Study programme: Intelligent Systems Engineering – bioinformatics / robotics
  • Scientific-research field: Engineering, Natural sciences and applied mathematics
  • Category: Informatics
  • Sub-category: Other
  • 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)
  • 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 Intelligent Systems Engineering, module Bioinformatics or Master of Intelligent Systems Engineering, module Robotics
 

2. Studies

Table 1: List of courses for master studies in Bioinformatics module.
  Professor Course

Semester

 ECTS

 1   prof. Smile Markovski, assoc. prof. Ana Madevska Bogdanova

 Computer science for Intelligent Systems

IX

6
 2  assist. prof. Nevena Ackovska , assoc. prof. Marija Mihova  Information processing in biological systems IX 6
 3  prof. Sasho Panov  Molecular biology of the cell

IX

6

 4  

 Elective course

IX

6

 5    Elective course

IX

6

 6  assoc. prof. Ana Madevska Bogdanova, prof. Zaneta Popeska  Data mining for bioinformatics X 6
 7    Elective course X 6
 
Table 2: List of courses for master studies in Robotics module.
   Professor

Course

Semester

 ECTS

 1  prof. Smile Markoski, assoc. prof Ana Madevska Bogdanova

 Computer science for Intelligent Systems

IX

6
 2 assist. prof. Nevena Ackovska, assoc.  prof. Marija Mihova  Information processing in biological systems IX 6
 3 assoc. prof. Andrea Kulakov, assist. prof. Nevena Ackovska

 Introduction to robotics

IX

6

 4  

 Elective course

IX

6

 5  

 Elective course

IX

6

 6  assoc. prof. Ana Madevska Bogdanova, assist. prof. Gjorgji Madzarov  Machine learning X 6
 7    Elective course X 6
 

Statistics for data analysis (4+1)

1. General Information

This program is designed to train staff with solid statistical knowledge with a focus on the newly recognized field of data science. The curriculum combines rigorous statistical theory with broader practical experience in applying statistical models to data work. Graduates will be in high demand. Most students are expected to be employed as statisticians, analysts and data experts within private and public institutions providing statistical consultations.

  • Name of the proposer: University "Ss. Cyril and Methodius University in Skopje, Faculty of Information Sciences and Computer Engineering - FINKI
  • Title of the study program: Second cycle academic studies in Statistics for Data Analysis
  • Scientific-research area: technical-technological / natural mathematical
  • Field: Informatics / Mathematics
  • Areas: Mathematical Statistics and Operations Research, Data Processing, Applied Mathematics and Mathematical Modeling, Programming, Artificial Intelligence, Algorithms, Information Processing .
  • 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).
  • Conditions for enrollment : according to the competition announced by the university, completed undergraduate studies in information science, computer or related fields with a minimum of 240 credits.
  • First semester: 3 compulsory courses and 2 electives, one of which may be from the University list.
  • Second semester : 1 compulsory and 1 elective course and completed project - master's thesis of 18 ECTS.
  • 1 ECTS credit corresponds to 30 hours of total work engagement.
  • The number of contact hours is 4.
  • The academic title or degree obtained upon completion of the studies is Master of Information Science - Statistics in Data Analysis

                Master of Science in Informatics - Statistics for Data Analytics

 

2. Studies

Table 2: List of Postgraduate Courses in Statistics for Data Analysis

РБ CODE / Subject Semester M / E ECTS
1 SNP-Z-1 Data analysis with statistical packages IX M 6
2 SDP-Z-3 Bayesian data analysis IX M 6
3 SDP-Z-4 Data preparation and research IX M 6
4 Elective item from Table 4 IX E 6
5 Elective item from Table 4 IX E 6
6 SNP-Z-2 Regression Models X M 6
7 Elective item from Table 4 X E 6
8 Masterrska topic X M 18

 

Table 3 shows the electives from the study program Statistics for Data Analysis. 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 3: Optional list of offered items

РБ New code /   Subject Semester ЕКТС
1 Methods of statistical locking IX 6
2 Concepts and application of big data IX 6
3 Analysis and forecasting time series IX 6
4 Advanced Algorithms IX 6
5 Modeling and fusing IX 6
6 Information Processing in Biological Systems IX 6
7 Analysis of data from related systems IX 6
8 Text Data Processing IX 6
9 Optimization methods IX 6
10 Data processing in bioinformatics IX 6
11 Network Analysis IX 6
12 Ambiental intelligence IX 6
13 Web of the Future IX 6
14 Statistical programming X 6
15 Statistical Learning X 6
16 Multidimensional statistical analysis X 6
17 Numerical methods for data science X 6
18 Statistical research skills: editing , reporting and visualization of data X 6
19 Business Analytics X 6
20 Random processes X 6
21 Big Data Modeling and Management X 6
22 Discovering knowledge in big graph data X 6
23 Open and related data X 6
24 Modern Simulations and Modeling X 6
25 Computational paradigms in the Internet of Things X 6
26 Data analysis from mobile sensors / sources X 6
27 Intelligent mobile applications X 6

 

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 .