A Mathematical Introduction to Machine Learning

Education facts

Code: 5MA206

The course addresses the fundamental mathematical and statistical methods and models used within the field of machine learning. Its purpose is to provide a mathematical foundation for advanced level courses in machine learning and artificial intelligence, as well as to introduce machine learning applications within academia and industry. The course is comprised of two modules. Module 1 (4,5 hp): *Theory and problem solving* This module addresses fundamental statistical models, statistical learning and maximum likelihood estimation, with an emphasis on supervised learning. Several commonly used models are introduced, and their mathematical properties are discussed, for instance linear regression and classification models, neural networks, support vector machines, as well as models for unsupervised learning. Furthermore, evaluation and validation of models are addressed. Module 2 (3 hp): *Computer assignments* This module addresses the implementation of commonly occuring machine learning models, as well as investigating their properties.

Entry requirements

The course requires courses in Mathematics, minimum 60 ECTS or at least two years of university studies and both cases require courses in linear algebra, multivariate calculus, mathematical statistics and computer programming, or equivalent. Proficiency in English and Swedish equivalent to the level required for basic eligibility for higher studies.

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.

• A Mathematical Introduction to Machine Learning

  Umeå University

  Umeå

  Start date: 2 November 2026

  End date: 17 January 2027

  Pace of study: 50 %