Curriculum Structure

The MSc Computer Science and Engineering curriculum structure provides the following:

  • Foundation Knowledge: The foundation is intended to provide common knowledge that all graduates, regardless off their concentration and anticipated future role, should posses.  The courses selected are offered in the first year of graduate study to enable the student to get the familiarity level specified in Bloom’s Taxonomy.  Two elective courses are offered during the first year in order to allow the student flexibility in mastering further computer science and engineering knowledge in anticipation of the concentration in the following year. The first elective offers the student the opportunity to master computational science, human computer interaction, parallel and distributed systems, information security. Much of the elective courses set is treated horizontally as part of core courses, but the electives are offered to ensure that student has the opportunity to further specialise the topic. The second elective option is intended to provide the students the opportunity to master areas of importance to computer science and engineering profession namely project management, economics and finance, marketing,psychology etc.
  • Ethics and professional development: A core course on ethics, law and communication is intended to provide some of the fundamental social, ethical and legal rules and regulations that underpin the computer science and engineering discipline. The communication component of the core course is intended to enable the student to improve some of the essentials of communication in professional development.
  • Concentration knowledge: The program offers the flexibility for students to master a specific area of specialisation in computer science and engineering (domain or program).
  • Thesis/Capstone experience: This component introduces the student to two obligatory subjects:  research methods (third semester) and thesis/capstone project in the fourth semester. The component is intended to provide the student the opportunity to select a preferred mode of research and liasion with industry in the area of concentration.

 

 

YEAR 1: 60 ECTS
SEMESTER 1: 30 ECTS
No Type Subject ECTS
1 M Research Methods in Engineering 6
2 M Advanced Programming 6
3 M Computational Mathematics &

Statistics

 6
4 M Signals and Communication Systems 6
5 E Student pick one form list below     
  E ▪ Advanced Topics in Operating Systems

▪ Distributed Computing Systems

▪ Computer Science Theory

 6
STREAM
STREAMS
1   SOFTWARE SYSTEMS ENGINEERING  
2   COMMUNICATION ENGINEERING  
3   DATA SCIENCE AND ARTIFICIAL INTELLIGENCE  
SEMESTER 2 :  30 ECTS
No Type Subject  
6 M System Design using Agile Engineering Practices 6
7 M Design and Analysis of Algorithms 6
  E/M Student picks two courses form STREAMS lists  
8 E/M Course one 5
9 E/M Course two 5
10 E Student pick one elective course from list A  
  E ▪ Functional Programming

▪ Internet of Things (IoT)

▪ Human- AI Interaction  ▪ Advanced Data and Information Modelling

▪ Cyber and Security Engineering

 5
11   Student pick one course soft-skills  Group  
  Z ▪ Organization and Innovation

▪ Ethics and technology change 

▪ Project Management

▪ Engineering Economics

 3
    BELOW ARE LISTED COURSES RELATED TO EACH STREAM – SEMESTER TWO  
    SOFTWARE SYSTEMS  ENGINEERING

Stream mandatory courses

  
  E/M Functional Programming 5
  E/M Software Engineering for Scalable Applications 5
    COMMUNICATION ENGINEERING

Stream mandatory courses

  
  E/M Data communications and Networks 5
  E/M Internet of Things (ToT) 5
    DATA SCIENCE AND ARTIFICIAL INTELLIGENCE

Stream mandatory courses

  
  E/M Artificial Intelligence

Techniques

 5
  E/M Data Visualization and Data Analytics 5
YEAR 2: 60 ECTS  
SEMESTER 3: 30 ECTS  
No Type Subject ECTS
12 M Seminar & Lab në Aplikimi Multidisiplinare 7
  E/M Student picks three courses from streams lists 18
13 E/M Course one 6
14 E/M Course two 6
15 E/M Course tree  6
    Student pick one elective course from list B  
16   ▪ Complexity and Optimization of Algorithms

▪ Cloud Computing and Big Data  

▪ Data Engineering with Python

▪ Modelling and Simulation in Communication Architectural

▪ Styles and Design Patterns

▪ Requirements Engineering

▪ Complex communications engineering

 5
BLOW ARE LISTED COURSES RELATED TO EACH STREAM – SEMESTER TREE
  SSE SOFTWARE SYSTEMS ENGINEERING

Stream mandatory courses

  
  E/M Semantic Technologies 6
  E/M Architectural Styles and Design Patterns 6
  E/M Test Driven Development 6
  CE COMMUNICATION  ENGINEERING

Stream mandatory courses

 4
  E/M Advanced Computer Networks 6
  E/M Advanced Wireless Technologies and 5G. 6
  E/M Digital Signal Processing 6
  DSAI DATA SCIENCE AND ARTIFICIAL INELEGANCE

Stream mandatory courses

  
  E/M Adv Machine Learning 6
  E/M Deep Learning 6
  E/M Big Data 6
    SEMESTER 4: 30 ECTS
17 M Master Thesis (Stream field oriented) 30

 

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