Reinforcement LearningLaajuus (5 cr)
Code: R504D121
Credits
5 op
Enrollment
01.10.2024 - 31.12.2024
Timing
17.02.2025 - 02.05.2025
Credits
5 op
Mode of delivery
Contact teaching
Unit
Bachelor of Engineering, Information Technology
Teaching languages
- English
Seats
0 - 30
Teachers
- Tuomas Valtanen
Responsible person
Tuomas Valtanen
Student groups
-
R54D22S
Location and time
Lapland University of Applied Sciences, Rantavitikka Campus, 13.1.2025 - 15.5.2025.
Teaching methods
Lectures, workshops, examples, exercises and self-supervised work.
Exam schedules
The course will be graded based on personal work and exercises.
Content scheduling
Basics of reinforcement learning concepts (including exploration and exploitation)
Common reinforcement learning methods and processes
Policies: evaluation, improvement, iteration
Conventional Reinforcement learning
Deep Reinforcement Learning
Evaluation scale
H-5
Assessment methods and criteria
The course will be graded on the scale of 1 - 5 and failed (0). The grading will be based on the submitted exercises/assignments.