Mathematics for Machine Learning

Education facts

Code: MA4029

The course contains multiple topics in calculus and multivariate calculus which are utilized in and are fundamental to many machine learning methods as: functions, gradients, derivatives, derivation rules, functions of many variables, partial derivatives, the Jacobian, multivariate chain rule and application to neural networks, approximation of functions, power series, multivariate Taylor series, optimization, gradient descent and regression.

Entry requirements

The course Linear Algebra for Data Science 7.5 credits. 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.

• Mathematics for Machine Learning

  Halmstad University

  Halmstad

  Start date: 30 March 2026

  End date: 7 June 2026

  Pace of study: 50 %