Intelligent Systems
Course code
old course code
Course title in Estonian
Intelligentsed süsteemid
Course title in English
Intelligent Systems
ECTS credits
approximate amount of contact lessons
Teaching semester
Assessment form
lecturer of 2019/2020  Autumn semester
Jaagup Kippar (eesti keel) e-toega kursus
lecturer of 2019/2020  Spring semester
lecturer not assigned
Course aims
The course gives practical knowledge about the algorithms used in the field of artificial intelligence and the skills to deploy them.
Brief description of the course
Introduction to the principles and algorithms used in the field of artificial intelligence. Solving problems by searching. Heuristics. Fundamentals of logical and probabilistic reasoning. Bayes' rule. Machine learning: supervised learning, decision tress, classifying with linear models and reinforcement learning. Neural networks. Ethics of artificial intelligence.
Independent work
Homework (programming and individual study)
Learning outcomes in the course
The student:
- is capable of formulating artificial intelligence problems as state space search
- knows tree search and local search algorithms and can apply them; including BFS, DFS, A* and hill climbing.
- Can describe the behaviour and parameters of tree search and local search
- is familiar with modern approaches to combinatorial search (metaheuristics)
- is knowledgeable about the principles of logical and probabilistic reasoning
- can solve problems involving propositional logic and Bayesian probability
- is familiar with some problems in machine learning (classification, learning behaviour) and approach methods (decision tree, linear classifiers, neural networks, reinforcement learning)
- can select and apply a suitable machine learning method
- can use a modern machine learning package to solve machine learning tasks (scikit-learn or weka).
Assessment methods
Grading is done using points system.

Participation and solving problems in labs: up to 25 points.

Homework assignment: up to 15 points.

Written examconsisting of problems and questions (variable weight): up to 70 points.

Final grade:

0-49 points- F

50-59 points- E

60-69 points- D

70-79 points- C

80-89 points- B

90 or more points- A
Jaagup Kippar
Replacement literature
M. Koit, T. Roosmaa. Tehisintellekt. Tartu, TÜ Kirjastus, 2011. (

Russell, S.J and Norvig, P. Artificial intelligence: a modern approach, third edition, Prentice Hall. 2009.

Algorithms and Architectures of Artificial Intelligence, IOS Press, 2007.