Problems and algorithms. Basic computational models and complexity measures. Complexity classes, their fundamental characteristics and hierarchies. Reduction and completeness in the complexity classes. NP-complete problems. Methods of solving (computationally) hard problems – deterministic methods, heuristics, approximation algorithms, probabilistic algorithms. 

Type of methodology: Combination of lecture and hands-on

Participants receive the certificate of attendance: Yes

Paid training activity for participants: Yes, for all

Participants prerequisite knowledge: Numerical methods (linear algebra, statistics); Domain-specific background knowledge