Machine learning

Education facts

Code: ST5401

Machine Learning is methodologically based on statistical theory, but instead of fociusing on inference about unknown population- and model parameters based on sampling, machine learning aims to find general patterns, mainly to make predictions. Among the areas of applications for machine learning, are marketing, finance, economics, and textual analysis within digital humanities and social scienses.

Entry requirements

90 ECTS credits first-cycle (basic level) courses, of which 60 ECTS credits in Statistics and 15 ECTS credits bachelor’s thesis in Statistics or other subject with quantitative focus, and Statistical Theory with Applications, first-cycle, 15 ECTS or equivalent. R programming, second-cycle (advanced level), 7.5 ECTS or equivalent. English 6 or equivalent.

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

  Stockholm University

  Start date: 1 September 2025

  End date: 2 November 2025

  Pace of study: 50 %