| Code |
Course Name |
Language |
Type |
| VBA 224E |
Stochastic Models in Data Science |
English |
Compulsory |
| Local Credits |
ECTS |
Theoretical |
Tutorial |
Laboratory |
| 3 |
6 |
3 |
0 |
0 |
| Course Prerequisites and Class Restriction |
| Prerequisites |
VBA 252E MIN DD
|
| Class Restriction |
None |
| Course Description |
| This course covers foundational and advanced topics in probability, stochastic processes, simulation, and
optimization techniques essential for modeling and analysis in various domains. Topics include Markov chains,
Poisson processes, queueing systems, Monte Carlo simulation, agent-based modeling, and heuristic
optimization methods like simulated annealing and genetic algorithms. Gain practical skills in analyzing
complex systems and optimizing decision-making processes through hands-on simulations and multi-criteria
optimization approaches. |
|
