Course: Machine Learning and Data Science

Lecturer: Dr Jens Trilling

Contents:

The course begins with a series of lectures introducing the possibilities and limitations of data analysis and machine learning. The limitations of these methods will also be explained:

• Preparation of the data used

• Generating missing data

• Working with uncertain data

• Approaches to building meta-models

• Components of an artificial neural network

• Supervised learning

• Unsupervised learning (dimension reduction methods, pattern recognition, interpretation and visualisation)