In this course you will be taught the basics of machine learning, its main approaches and usable algorithms. The course will provide examples of basic applied ML problems and how they can be solved with related models. We will help you start thinking about how machine learning can solve different problems.
The course will consist of 8 online lectures and 4 scheduled online sessions for group discussions and Q&A. There will also be weekly exercises to help test your knowledge progression. The lectures, exercises and sessions for discussions will together address and mediate knowledge in the following areas:
- Introduction to ML
- Data preparation and feature engineering
- Supervised learning
- Unsupervised learning
- Reinforcement learning
- Neural networks