Students passing the course will be able to describe basic concepts of machine learning, including the main steps that are implemented in a typical Machine Learning project.
This course includes four practical sessions implemented in Python:
- Build an end-to-end ML framework
- Supervised learning: classification
- Supervised learning: regression
- Unsupervised learning: dimensionality reduction and clustering