PhD basic courses in transferable skills


Introduction to statistical learning

The objective of the course is to give an overview of statistical (machine) learning methods. On completion of the course, the student will be able to:

  • select an appropriate predictive model for a given problem
  • program prediction and classification models in the statistical software R
  • understand the role of model selection and assessment using cross-validation and randomization
  • interpret and evaluate results correctly and draw reasonable conclusions
  • clearly and concisely communicate results and conclusions

The course will give an introduction to the following topics:
  • Supervised learning
  • Predictive regression models: linear regression, regularization,
  • and shrinkage, non-linear regression, regression trees, random forests.
  • Predictive classification models: logistic regression, discriminant analysis, classification trees.
  • Crossvalidation and randomization
  • Unsupervised learning
  • PCA
  • Clustering

Statistics I: Basic Statistics and Statistics III: Regression analysis or equivalent

Admitted to a Ph.D. program.

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Introduction to statistical learning, Uppsala
Uppsala, Distance
Course date
Last application day