Machine learning with Python 2 ECTS

Application time has expired! ***Most of us have their own personal “artificial intelligence assistant” which is implemented on her smartphone. This assistant helps us to find the next supermarket, to translate information in foreign languages or to spot the best Italian restaurant in town. Many of these abilities are obtained using machine learning (ML).

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

Duration: 15.4.2019–15.6.2019

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?

 

Interested? Apply now!