Acquiring basic knowledge about advanced algorithms and examples of their application. Understanding complexities of algorithms and learning numerous algorithms for common problems in software development.

Knowledge of advanced algorithms and examples of their application. These algorithms will be implemented and their complexities will be understand in real examples.

Advanced data structure (B trees, Fibonacci heap). Graph algorithms (network flow, minimum spanning trees, maximum flow, minimum cost, examples). Dynamic programming (principles, elements, optimal substructure, longest common subsequence, optimal binary search trees, examples). Parallel algorithms (dynamic parallel programming, examples). NP- Completeness (examples). Approximation algorithms (set-covering problem, randomization, subset-sum problem, bin packing, knapsack problem, min-cut, examples). Computational geometry. Nature-inspired algorithms (evolutionary algorithms, ant colony optimization, particle swarm optimization, etc.)

Lectures; Auditory and computer practice; Consultations.