Learning outcomes

After completing the course a student is expected to

- be able to design and implement efficiently basic algorithms related to dynamic programming, graphs, numeric algorithms, optimization and geometric algorithms.
- have a deepened understanding of the fundamental role that algorithm design and analysis have in solving real problems.
- be familiar with the most common programming contests, online practise environments and literature on algorithmic programming.

Contents

Programming contests, algorithmic programming, dynamic programming, graph algorithms, numeric algoritms, optimization, geometric algorithms.

Teaching methods

2 hours lectures, 4-8 hours seminar work, participation in a programming contest.

Evaluation

Study materials

See the course web page.

Belongs to following study modules

2018–2019

Teaching

Archived Teaching Schedule. Please refer to current Teaching Shedule.

TIETS09 Algorithmic Problem Solving