Statistics: Machine Learning from a Regression Perspective

Education facts

Code: STAN51

<p>The digital revolution has made it possible to collect vast amounts of data - but how can we make sense of it and use it wisely? In this course, you’ll learn the fundamentals of machine learning, a powerful tool for analysing and drawing conclusions from large datasets.</p><p>Machine learning is about building models that improve as they receive more data - they learn from experience. This technology is used everywhere: from predicting customer behaviour in shops to optimising online advert pricing. In this course, you’ll get an introduction to machine learning, with a focus on methods based on regression analysis.</p><p>You’ll learn about:</p><ul><li>classification using logistic regression</li><li>model selection using information criteria and cross-validation</li><li>shrinkage methods such as lasso and ridge regression</li><li>dimensionality reduction using principal component analysis and partial regression</li><li>the basics of neural networks.</li></ul>

Entry requirements

90 credits in Statistics with at least 7.5 credits in Regression Analysis or Econometrics, or the 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.

• Statistics: Machine Learning from a Regression Perspective

  Lund University

  Start date: 31 August 2026

  End date: 1 November 2026

  Pace of study: 50 %