Year 1
Code | Course | L+E+S ~ ECTS | |
---|---|---|---|
Winter | Summer | ||
M118 | Probability | 4+3+0 ~ 9 | |
I066 | Intelligent Robotic Systems | 3+2+1 ~ 8 | |
MI008 | Semantics of programming languages | 2+2+0 ~ 6 | |
MI009 | Applied linear algebra and scientific computing | 4+2+1 ~ 9 | |
Total | 13 ~ 17 | 11 ~ 15 |
In order to earn the mandatory academic year study workload of 60 ECTS credits, students shall choose elective courses from the list below.
Criteria for enrolment in Year 2: a minimum of 40 ECTS credits which must obligatorily include ECTS credits allocated to the following courses: Intelligent Robotic Systems.
Year 2
Code | Course | L+E+S ~ ECTS | |
---|---|---|---|
Winter | Summer | ||
I067 | Operating systems | 3+2+1 ~ 8 | |
M128 | Linear optimization | 3+2+1 ~ 8 | |
M129 | Nonlinear optimization | 3+2+0 ~ 7 | |
I068 | Advanced programming techniques | 2+2+1 ~ 7 | |
MIP001 | Master Thesis | 0+0+0 ~ 8 | |
Total | 12 ~ 16 | 10 ~ 22 |
In order to earn the mandatory academic year study workload of 60 ECTS credits, students shall choose elective courses from the list below.
Elective courses
A: recommended for students who want to focus on computer science
Code | Course | L+E+S ~ ECTS |
---|---|---|
I069 | Natural Language Processing with Deep Learning | 3+2+1 ~ 8 |
MI006 | Cryptography | 2+2+0 ~ 6 |
M124 | Advanced concepts in machine learning | 3+2+1 ~ 8 |
I033 | Parallel Programming | 2+2+0 ~ 6 |
I070 | Computer Vision | 2+2+0 ~ 6 |
I064 | Contemporary topics in computer science | 2+2+0 ~ 6 |
I071 | Approximation algorithms | 2+2+0 ~ 6 |
I072 | Heuristic algorithms | 2+2+0 ~ 6 |
I073 | Static program analysis | 2+1+1 ~ 6 |
I074 | Distributed Systems | 2+1+1 ~ 6 |
I065 | Randomized algorithms | 2+2+0 ~ 6 |
I075 | Compiler construction | 2+1+1 ~ 6 |
I076 | Linux operating system | 1+1+0 ~ 3 |
B: recommended for students who want to focus on data science
Code | Course | L+E+S ~ ECTS |
---|---|---|
M003 | Time Series | 2+0+2 ~ 6 |
M119 | Stochastic Processes I | 2+2+0 ~ 6 |
M121 | Stochastic Processes II | 2+2+0 ~ 6 |
M122 | Multivariate analysis | 2+1+1 ~ 7 |
M095 | Statistical Practice | 1+2+1 ~ 6 |
C: recommended for students who want to focus on applied mathematics
Code | Course | L+E+S ~ ECTS |
---|---|---|
M130 | Control Theory | 3+2+1 ~ 8 |
M131 | Dynamic systems | 2+2+0 ~ 6 |
M132 | Model reduction and approximation methods | 2+1+1 ~ 6 |
M111 | Normed spaces | 2+2+0 ~ 6 |
M133 | Partial differential equations | 4+2+0 ~ 8 |
M134 | Numerical Methods for Partial Differential Equations | 3+2+0 ~ 7 |
M135 | Continuum mechanics | 3+2+0 ~ 7 |
M136 | Fourier analysis and applications | 2+2+0 ~ 6 |
MI005 | Mathematical aspects of electoral systems | 1+0+1 ~ 3 |
M048 | Decision Theory | 1+0+1 ~ 4 |
MI001 | Graphs and Applications | 2+2+0 ~ 6 |
MI007 | Complex Networks | 2+2+0 ~ 6 |
MI002 | Data Clustering and Applications | 2+1+1 ~ 5 |
M109 | Convex Functions | 1+1+0 ~ 3 |
D: other elective courses
Code | Course | L+E+S ~ ECTS |
---|---|---|
I040 | Project Management Basics | 1+1+0 ~ 4 |
Z013 | Internship | 0+0+2 ~ 4 |