Credits: 2

Schedule: 15.04.2019 - 15.06.2019

Contact information for the course (applies in this implementation): 

Assistant Professor Alex Jung (

Details on the course content (applies in this implementation): 

Most of us have their own personal "artificial intelligence assistent" 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 this abilities are obtained using machine learning (ML)

In this 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 Feature Learning. Each round covers a certain part of the course book and includes a Python notebook with the coding assignment.

The course is intended for students of Network university FITech.

Additional information for the course (applies in this implementation): 

Course workspace:


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