Artificial intelligence
Individual course
Max amount of FITech students: 30
Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course.
This course presents the student overview of some of the basic AI theories and applications with practicality in mind. In the course projects, students get some experience in programming AI based applications and using especially AI based search methods.
Course contents
Intelligent agent types, uninformed search methods, informed (heuristic) search, local search, constraint satisfaction problems, adversarial search, uncertainty handling, probabilistic reasoning, utility, machine learning, decision networks, Markov decision process, reinforcement learning, applications
Learning outcomes
After completing the course, students
- know the basic search strategies that can be applied in problem solving and optimization
- understand how search-based decisions are made in game-like competitive applications
- know the basic principles of probabilistic reasoning in artificial intelligence systems
- know how rational decision making under uncertainty can be formulated using utility theory
- understand the fundamentals of machine learning and how some of the established methods can be applied to problems in AI
- are familiar with advanced AI applications of perception and robotics and how probabilistic inference and machine learning can be used in these settings.
Teaching schedule
The course is organised online, but the exam needs to be done on campus.
- Lectures on Wed at 14-16 and Thu at 14-16 between 11.1.-23.2.2023 (lecture slides will be available in Moodle)
- Two compulsory projects (DL 10.2. and 10.3.)
- Six voluntary exercises (DL weekly)
- Exam on 3.3. or 21.4.
- All deadlines are confirmed in the beginning of the course
The projects and exercises give additional points for the exam.
More information in the University of Oulu study guide.
You can get a digital badge after completing this course.
AI tekoäly datankäsittely data-analyysi prosessointi koneoppiminen
Further information about the studies
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