Machine Learning in Games (5 ECTS)

Learning outcomes

On completion of the course student knows foundations of machine learning. He/she is able to implement small-scale machine learning projects in practice, including data pre-processing, model selection, and validation. In particular, student knows how to apply machine learning in games and can develop machine learning applications with game engines.

Content

- supervised learning
- unsupervised learning
- reinforcement learning
- data preprocessing
- model selection and parametrization
- validation
- machine learning project with Unity game engine

Evaluation scale

0-5

Assessment criteria, satisfactory (1)

Students have achieved the course objectives fairly. Students will be able to identify, define and use the course subject area’s concepts and models. The student understands the criteria and principles of the expertise development.

Assessment criteria, good (3)

Students have achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Students are able to define the course concepts and models and are able to justify the analysis. The student is able to apply their knowledge in study and work situations. The student understands the importance of expertise in the field of information and communication technology and is able to analyze his/her own expertise.

Assessment criteria, excellent (5)

Students have achieved the objectives of the course with excellent marks. Students master commendably the course subject area’s concepts and models. Students are able to make justified and fluent analysis and to present concrete development measures. The students are well prepared to apply their knowledge in study and work situations. Students are able to analyze the information and communication technology sector expertise and the development of their own expertise.

Assessment criteria, approved/failed

Students have achieved the course objectives fairly. Students will be able to identify, define and use the course subject area’s concepts and models. The student understands the criteria and principles of the expertise development.