MAT-75006 Artificial Intelligence, 7 cr
Lisätiedot
No lectures during academic year 2017-2018.
Suitable for postgraduate studies.
Ei toteuteta lukuvuonna 2017-2018.
Vastuuhenkilö
Tapio Elomaa
Opetus
Toteutuskerta | Periodi | Vastuuhenkilö | Suoritusvaatimukset |
MAT-75006 2017-01 | - |
Tapio Elomaa |
Osaamistavoitteet
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.
Sisältö
Sisältö | Ydinsisältö | Täydentävä tietämys | Erityistietämys |
1. | Logic, knowledge, and reasoning | propositional and first-order logic | knowledge bases |
2. | Problem solving and search | heuristic search | algorithm A* |
3. | Uncertain knowledge and reasoning | probabilistic reasoning | decision making |
4. | Machine learning | learning from observations | statistical learning |
Ohjeita opiskelijalle osaamisen tasojen saavuttamiseksi
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.
Arvosteluasteikko:
Numerical evaluation scale (0-5)
Osasuoritukset:
Oppimateriaali
Tyyppi | Nimi | Tekijä | ISBN | URL | Lisätiedot | Tenttimateriaali |
Book | Artificial Intelligence: A Modern Approach | Stuart Russell & Peter Norvig | Yes |
Esitietovaatimukset
Opintojakso | P/S | Selite |
MAT-02500 Todennäköisyyslaskenta | Advisable | |
MAT-02650 Algoritmimatematiikka | Advisable | |
TIE-02100 Johdatus ohjelmointiin | Mandatory | |
TIE-02200 Ohjelmoinnin peruskurssi | Advisable |
Vastaavuudet
Opintojakso | Vastaa opintojaksoa | Selite |
MAT-75006 Artificial Intelligence, 7 cr | OHJ-2556 Artificial Intelligence, 6 cr |