Study Guide

Objective

After completing the course, the student will master the basics of tree and network structures and the algorithms used in connection with them. In addition to theoretical understanding, the student is able to apply tree and network structures to solve practical problems.

Content

- Review: Search algorithms in trees and networks
- Game theory
- Design Algorithms
- Reinforcement learning

Evaluation scale

0 - 5

Assessment criteria, excellent (5)

The student controls and understands the theoretical basis of all the methods covered in the course, in addition to fluently applying the techniques to solve practical problems. The student has also returned the required assignments on time.

Assessment criteria, good (3)

The student understands the main features of the theoretical basis of the methods covered in the course and is able to apply most of them to solving practical problems. The student has returned the majority (70%) of the required assignments on time.

Assessment criteria, satisfactory (1)

The student has a superficial knowledge of the theoretical basis of the methods covered in the course and is able to apply some of the techniques to solving practical problems. The student has returned part (50%) of the required assignments on time.

Prerequisites

Data structures and algorithms