In this online course, we will introduce some of the most widely used ML methods such as regression, classification, feature learning and clustering. We will discuss these methods in a hands-on fashion using coding assignments which include implementations of ML methods using the programming language Python.
The course is organized in six rounds: Introduction, Regression, Classification, Model Validation and Selection, Clustering and Dimensionality Reduction. Each round covers a certain part of the course book and includes a Python notebook with the coding assignment.
Teaching method: online
Prerequisites: This course requires only basic skills in mathematics (notion of a function , vectors and matrices ) and familiarity with at least one high-level programming language (Python, R, C ++, Matlab, Visual Basic,…).
Round 1 – Introduction. How to read in data from files and the internet and visualize it?
Round 2 – Regression. How to predict numerical quantities?
Round 3 – Classification. How to classify objects into different categories?
Round 4 – Model Validation and Selection. Which model is the best?
Round 5 – Clustering. How to group (segment) similar objects?
Round 6 – Dimensionality Reduction. How to make a long story short?