Machine Learning

Education facts

Code: DT150G

Machine learning is a subfield of artificial intelligence within computer science and includes techniques that enable machines (robots or software) to learn how to perform specific tasks based on data, rather than through explicit programming. Applications include image classification, predictive maintenance, text analysis, speech recognition, and the generation of images and text. This course provides an introduction to machine learning with the aim of developing an understanding of fundamental concepts, methods, and algorithms. This is achieved through hands-on work in which algorithms are implemented and modified almost from scratch, as well as through the study of data analysis, data preprocessing, model evaluation, identification of potential issues and misleading results, and practical recommendations for applying machine learning techniques. The course also includes a literature study that provides insight into current research, as well as a practical classification task and a final project that offer practical experience and skills for further studies in academia or professional work in industry with machine learning.

Entry requirements

Object-Oriented Programming, 7.5 Credits from Programming, 15 credits, and Algebra and Calculus for Students in Engineering, 15 credits.

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

  Örebro University

  Örebro

  Start date: 18 January 2027

  End date: 28 March 2027

  Pace of study: 50 %