Our aim is proving theoretical and practical knowledge useful in modelling designing and implementing systems based on artificial intelligence methods and parallel and distributed approaches.
Topics:
- Cloud computing, high performance computing;
- Multi-agent systems;
- Machine learning, deep learning models.
Skills:
- Informatics/Computer Science, Mathematics and informatics, Mathematics, Applied Mathematics, Economics;
- Computer Engineering, Information Technologies;
- Other programs on scientific or engineering fields.
Career opportunities:
- Cloud computing;
- Artificial intelligence;
- Data analyst;
- Researcher in the field of artificial intelligence, machine learning, cloud computing, high performance computing.
Year I Semester I
| Topics |
Nr. Credits |
Lectures / week |
Seminaries or Laboratories / week |
| Distributed Systems |
6 |
2 |
1 |
| Advanced Logical and Funcitonal Programming |
6 |
2 |
1 |
| Operatinal Research and Optimization |
6 |
2 |
1 |
| Data analysis in R |
6 |
2 |
1 |
| Systolic Algorithms |
5 |
2 |
1 |
| Ethics and Academic Integrity |
2 |
1 |
– |
| Optional Courses |
| Network security models and arhitectures |
|
|
|
| Data Mining |
|
|
|
| Modelling and Verifying Algorithms in Coq |
|
|
|
| TOTAL |
30 |
10 |
5 |
| Facutlive Courses |
| Programming I |
5 |
2 |
2 |
| Logical and Functional Programming |
5 |
2 |
2 |
Year I Semester II
| Topics |
Nr. Credits |
Lectures / week |
Seminaries or Laboratories / week |
| Parallel Computing |
6 |
2 |
1 |
| Term Rewriting |
6 |
2 |
1 |
| Multi-agent Systems |
6 |
2 |
1 |
| Automated Theorem Proving |
6 |
2 |
1 |
| Elective Course |
6 |
2 |
1 |
| Optional Courses |
| Network security models and arhitectures |
|
|
|
| Data Mining |
|
|
|
| Modelling and Verifying Algorithms in Coq |
|
|
|
| TOTAL |
30 |
10 |
5 |
| Facutlive Courses |
| Operating Systems |
5 |
2 |
2 |
| Programming II |
5 |
2 |
2 |
Year II Semester I
| Topics |
Nr. Credits |
Lectures / week |
Seminaries or Laboratories / week |
| Machine Learning |
5 |
2 |
1 |
| Resource Management in Distributed and Parallel Systems |
5 |
2 |
1 |
| Techniques for Scientific Work |
5 |
2 |
1 |
| Distributed Methods and Technologies based on XML |
5 |
2 |
1 |
| Metahearistic Algorithms |
5 |
2 |
1 |
| Research practice |
5 |
– |
3 |
| TOTAL |
30 |
10 |
8 |
Year II Semester II
| Topics |
Nr. Credits |
Lectures / week |
Seminaries or Laboratories / week |
| Research practice |
8 |
– |
3 |
| Thesis Preparation |
15 |
– |
8 |
| Sciencific Seminar |
7 |
– |
3 |
| TOTAL |
30 |
– |
14 |
| Facutlive Courses |
| Intelligent Systems |
5 |
2 |
1 |
