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д-р Љупчо Антовски

Computer networks and e-technologies (3+1+1)

Computer networks and e-technologies (3+1+1)

1. General information 
 
The goal of the computer networks and e-technologies master studies is to provide top quality European education and training for ICT engineers. The studies offer deeper and specialized knowledge about computer networks and e-technologies. Upon completion of this master study programme the ICT engineers are expected to take up responsible higher level positions in the business and engineering processes of planning, design, managing and monitoring of computer networks. They are also expected to be able to efficiently and effectively employ various state of the art e-technologies and fully understand their business aspects.
  • Offered by: Ss. Cyril and Methodius University - Skopje, Faculty of Computer Science and Engineering – FCSE
  • Study programme: Computer networks and e-technologies master studies
  • Scientific-research field: Engineering and Technology
  • Category: Electrical engineering, Electronic engineering, Information engineering
  • Sub-category: Communication engineering and 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 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 computer networks and e-technologies
 
2.  Introductory courses
 
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. 
 
 
Table 1: List of introductory courses
 

Course

Semester

ECTS

Prerequisite
 1

 Probability and statistics

VII

 6 -
 2  Network operating systems VII 6 -
 3  Elective course 1 VII 6 -
 4  Elective course 2 VII 6 -
 5  Elective course 3 VII 6 -
 6

 WAN networks

VIII

6

-
 7

 Information systems

VIII

6

-
 8  Elective course 4 VIII 6 -
 9  Elective course 5 VIII 6 -
 10  Elective course from University list of available courses VIII 6 -
 
 
Table 2: List of elective introductory courses
 

Course

Semester

ECTS

Prerequisite
 1

 Modelling and simulation

VII

 6 -
 2  Artificial intelligence VII 6 -
 3

 Network programming

VII

6

-
 4

 Web-based systems

VII

6

Network programming
 5

 Advanced processor architectures

VII

6

-
 6  Embedded computer systems VII 6 -
 7  Network software VII 6 -
 8  Introduction to microprocessors VIII 6 -
 9  Wireless computer networks VIII 6 - 
10   Network standards and devices VIII 6 - 
11   Sensor systems VIII 6 - 
12   E-commerce and m-commerce VIII 6 - 
13   Design of embedded computer components VIII 6 - 
14   Public mobile networks VIII 6 - 
15   Computer network management VIII 6 - 
16   Computer security and protection VIII 6 - 
17  Mobile information systems VIII 6 - 
18  Geographic information systems VIII 6 -
19  Biocybernetics VIII 6 Artificial intelligence 
 
2.1 Studies
 
Courses for the Master studies for the study programme Computer networks and e-technologies can be found at this link.
12/06/2024
  
Python Developer 
 
Stonebranch builds dynamic IT automation solutions that transform business IT environments from simple IT task automation into sophisticated, real-time business service automation, helping organizations achieve the highest possible Return on Automation. No matter the degree of automation, Stonebranch software is simple, modern, and secure. Using its universal automation platform, enterprises can seamlessly orchestrate workloads and data across technology ecosystems and silos. Headquartered in Alpharetta, Georgia with points of contact and support throughout the Americas, Europe, and Asia, Stonebranch serves some of the world's largest financial, manufacturing, healthcare, travel, transportation, energy, and technology institutions. 
  
The candidate will join our Technology Business Unit in Skopje, contributing to the whole growth and adoption of our Universal Automation Platform by extending its integration capabilities and enabling our customers to automate “everything and everywhere”. 
  
 
Your Part in this Growth Story: 
 
Stonebranch Marketplace is evolving enabling our customers who build DevOps, DataOps, and any type of IT orchestration to integrate with any cloud services and cutting-edge applications such as GitHub, Kafka, Elastic, Terraform, Kubernetes, Docker, Databricks, Snowflake, Slack, Jenkins, etc. 
  
Stonebranch’s Solutions Extension Development team is searching for a Software Engineer who’s interested in designing and building amazing, impactful Universal Automation Connectors that will extend the integration capabilities of our Universal Automation Platform. 
  
The position is best suited for a professional interested in the automation or systems integration fields, who has a successful track record in building solutions through Python while being an organic member of an agile team. 
  
This will be a hybrid position – 3 days/wk onsite and 2 days/wk remote – and will report to the Manager for Solution Engineering. 
  
 
What you will be doing: 
 
• As a software engineer, you will design, build, test, document and maintain the next generation of universal automation platform connectors leveraging the Universal Extension capabilities. 
• You will maintain, support, and extend the rolled-out software components. Apply technical expertise to investigate and resolve software issues (troubleshooting & bug fixing). 
• You will work based on CI/CD DevOps practices and that involves testing automation and automated deployments. 
 
• You as well as the rest of the team are responsible for the team deliverables. You need to make sure your tasks are timely implemented and delivered with good quality following best practices. 
• You will be an organic agile team member. You will communicate efficiently with your peers to make sure that the work executed is aligned with the scope of the user stories and with the technological guidelines. 
• You will meet team and company targets, by working collaboratively and establishing fruitful and joyful communication with your peers. 
 
 
What You Will Bring to the Team: 
 
• Bachelor’s degree or higher in Computer Science 
• Good knowledge of Python. 
• Understanding and experience in Unit Testing, OOP, and design patterns. 
• Experience with basic programming concepts (IPC, Multithreading, Shared Memory, Network Programming, Filesystem) and good understanding of operating systems and how they interact with processes. 
• Experience with Windows & Linux platforms, and Unix Shell scripting. 
• Experience with Git. 
• Excellent written and verbal communication (English). 
• Demonstrating passion in excellence, determination, ownership of delivered work, and accountability. 
• A big appetite and curiosity for automation and learning new technologies. 
• Ego-free attitude — we are here for the success of the Team. 
 
  
Bonus Points: 
 
• Prior professional experience in Python and Python Unit Testing. 
• Prior participation in open-source projects. 
• Experience with SQL and relational databases. 
• Experience with test automation frameworks such as Robot. 
• Experience mentoring other engineers, conducting code reviews, pair programming, etc. 
  
  
Why You'll Love Stonebranch: 
 
• Competitive compensation 
• Health insurance and pension plan 
• Great company culture 
• Regular social events 
• Work in a motivated, experienced, and international team of top performers 
 
• Continuous professional development 
 
If you are interested in this position, please send your CV to hr@stonebranch.com. 
 
We are an Equal Opportunity Employer and do not discriminate against applicants due to race, ethnicity, gender, veteran status, or on the basis of disability or any other federal, state or local protected class. 
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Statistics for data analysis (3+1+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 120 ECTS credits.
  • Duration of studies: 4 semesters .
  • One academic year consists of two semesters lasting 30 weeks (1 semester = 15 weeks).
  • Requirements for enrollment : according to the competition announced by the university, completed undergraduate studies in information science, computer or related fields with a minimum of 180 credits.
  • Introductory Layer : The introductory layer is the first two semesters in which students are offered a set of differential introductory courses. After their successful realization, the student acquires the right to continue with the second year of postgraduate studies.
  • Third semester: 3 Mandatory courses and 2 electives, one of which may be from the University list.
  • Fourth semester : 1 Mandatory course and 1 elective course, the elective course can be from the University list (only if in the first semester the courses are selected at the Faculty level) and the final project - master's thesis from 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 Science in Information Science - Statistics for Data Analysis

                Master of Science in Informatics - Statistics for Data Analytics

 

2. Introductory layer

The first year of study is the introductory layer for students whose studies lasted less than four years, ie students who gained 180 credits from previous studies. Students must pass differential exams that will enable them to enter the basics of mathematics and computer science needed to successfully complete their studies.

Table 1: List of subjects in the first year of study

РБ CODE / Subject Semester M / E ECTS
1 Mandatory subject 1 from Table 2 VII M 6
2 Mandatory subject 2 from Table 2 VII M 6
3 Mandatory subject 3 from Table 2 VII M 6
4 Mandatory subject 4 from Table 2 VII M 6
5 Elective course 1 * VII E 6
6 Mandatory subject 5 from Table 2 VIII M 6
7 Mandatory subject 6 from Table 2 VIII M 6
8 Mandatory subject 6 from Table 2 VIII M 6
9 Elective course 5 * VIII E 6
10 Selection from the university list of free courses VIII E  

 

Elective courses can be selected from the proposed list of courses of the study program (Table 2), or from the proposed lists of courses from the introductory layer of other study programs of the Faculty of Information Sciences and Computer Engineering. The selection of courses should be made in accordance with the previous knowledge of the candidate and the necessary knowledge to continue with the postgraduate studies in statistics for data analysis. When choosing courses, the student should coordinate with the head of the study program. A free choice of subject is also allowed, which is on the university list of subjects for the first year of two-year postgraduate studies.

After the successful completion of all ten courses and 60 credits, the student with previously acquired 180 ECTS credits (or completed three-year studies) continues with the courses from the second academic year of postgraduate studies - Table 3 (III and IV semester).

  * Selection from the lists of subjects from the introductory layer of all master studies at the Faculty of Information Sciences and Computer Engineering

 

Table 2: List of recommended courses in the first year of study

РБ New code /   Subject Semester ECTS
1 F18L1W011 Discrete Mathematics VII / VIII 6
2 F18L1S013 Calculus VII 6
3 F18L2W006 Probability and statistics VII 6
4 F18L3W035 Linear Algebra and Applications VII 6
5 F18L3W008 Introduction to Data Science VII 6
6 F18L3W161 Social Networks and Media VII 6
7 F18L3W108 Internet of Things VII 6
8 F18L3W004 Databases VII 6
9 F18L3W068 Computing in the Cloud VII 6
10 F18L3S036 Machine learning VIII 6
11 F18L3S150 Data Mining VIII 6
12 F18L3S163 Statistical Modeling VIII 6
13 F18L3S157 Data warehousing and analytics VIII 6
14 F18L1S023 Business Statistics VIII 6
15 F18L3W076 Introduction to time series analysis VIII 6

 

Table 3: 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 Master Thesis X M 18

 

Table 3 lists the electives from the Statistics for Data Analysis 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 subject from the university list nand free electives.

 

 

Table 4: Optional list of offered items

РБ New code /   Subject Semester ECTS
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 .

Табови

д-р Димитар Трајанов

Табови

Dimitar Trajanov Ph.D.