Introduction to Machine Learning MethodsLaajuus (5 cr)

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.