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Introduction to Machine Learning

Machine learning and artificial intelligence has a strong influence on society today, both in practice and in people's minds. Many organisations, both in the public sector and in business, are trying to take advantage of the new technology.

In this course you will be introduced to basic principles in the field of machine learning, good practice, as well as some important and easily accessible methods. In exercises you get to experiment with these methods and learn how to use them in practice.

Course contents

The course addresses the question how to enable computers to learn from past experiences. It introduces the field of machine learning describing a variety of learning paradigms, algorithms, theoretical results and applications. Ethical and societal aspects of machine learning are discussed. The course covers basic concepts in machine learning and methods such as: nearest neighbour classifier, decision trees, bias and the trade-off of variance, regression, support vector machines, artificial neural networks, ensemble methods, dimensionality reduction, and subspace methods.