Machine Learning

Education facts

Code: DT8052

The course is part of the programme MAISTR (hh.se/maistr) where participants can take the entire programme or individual courses. The course is for professionals and is held online in English. The courses qualify for credits and are free of charge for participants who are citizens of any EU or EEA country, or Switzerland, or are permanent residents in Sweden. More information can be found at antagning.se. <br> The course covers the following topics: - Introduction to machine learning, including basics and prerequisites. - Basic aspects of supervised machine learning, including basic regression and classification algorithms. - Overfitting and generalization, the bias/variance trade-off, and methods for avoiding overfitting, including regularization. Explanation of how these problems are addressed in various methods, including Support Vector Machines (SVMs), and ensemble methods. - Introduction to Neural Networks for supervised learning, as well as an overview of deep neural networks and unsupervised feature extraction with autoencoders. - Overview of unsupervised data clustering methods and their applications.

Entry requirements

Degree of Bachelor in Computer science or Degree of Bachelor of Science in Engineering or the equivalent of 180 Swedish credit points or 180 ECTS credits at an accredited university. Programming 7.5 credits and Mathemathics 7.5 credits including Linear Algebra. English 6 or English level 2. Exemption of the requirement in Swedish is granted for those with foreign grades.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Machine Learning

  Halmstad University

  Ortsoberoende

  Start date: 18 January 2027

  End date: 28 March 2027

  Pace of study: 33 %