MAT-75006 Artificial Intelligence, 7 cr

Additional information

No lectures during academic year 2017-2018.
Suitable for postgraduate studies. The implementation will not be executed during the academic year 2017-2018.

Person responsible

Tapio Elomaa

Lessons

Learning Outcomes

After completing the course the student will have be familiar with different areas of artificial intelligence. In particular, the student is able to apply to problems arising in application fields the basic methods of solving problems by searching, informed search and exploration, inference in first-order logic, probabilistic reasoning, learning from observations, and statistical learning methods. The student will be able to identify the computational complexity of the used technique. The student will obtain a deeper knowledge on the topic of the chosen study and presentation. Also hands-on experience on some specific artificial intelligence technique will be gathered in a programming home work.

Content

Instructions for students on how to achieve the learning outcomes

The course grade will be based on the course exam, a study/presentation, and programming home work. Active participation to weekly exercises yields extra points. If the student demonstrates thorough understanding of the core content, s/he may pass the course with grade 3. In order to achieve grade 4, the student must also demonstrate competency in complementary knowledge. The student may achieve grade 5, if s/he also demonstrates good command of specialist knowledge. If there are minor shortcomings regarding the core content, the student may receive the grade 1 or 2, depending on the number of flaws. If there are significant shortcomings regarding core content, the student will not pass the course.

Assessment scale:

Numerical evaluation scale (0-5)

Partial passing:

Completion parts must belong to the same implementation

Study material

Prerequisites

Correspondence of content