Introduction to Machine Learning MethodsLaajuus (5 cr)
Course unit code: R504D123
General information
- Credits
- 5 cr
- Institution
- Peppi
Objective
- Knowledge and skills to understand basic machine learning (ML) models and methods, and to choose and apply them in a principled and sound way in basic tasks
- Abilities for computational thinking that utilizes machine learning, for problem solving
Content
- Theory and practice of basic ML models and methods for typical tasks encountered in at least unsupervised and supervised learning
- Use of suitable tools (e.g., a high-level ML application programming interface) for building solutions
Assessment criteria, satisfactory (1)
Grade 1: The student knows the theory on the considered ML models and methods. The student is able to solve basic ML problems, using the considered tools.
Assessment criteria, good (3)
Grade 3: The student understands the theory on the considered ML models and methods. The student is able to solve a variety of basic ML problems, using the considered tools, suitably.
Assessment criteria, excellent (5)
Grade 5: The student understands the theory on the considered ML models and methods. The student is able to solve a variety of basic ML problems, using the considered tools, most suitably.