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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.