60 credits of which 15 credits in mathematics and 15 credits in computer science. Probability and Statistics or Probability and Statistics DV. Algebra and Geometry or Linear Algebra and Geometry I. Participation in a second course in programming.
This is a practical introduction to machine learning: its terminology, an overview of basic supervised and unsupervised methods (for example, regression, classification trees, an introduction to neural networks and deep learning, and clustering), use of established tools for machine learning and practical aspects such as dimensionality reduction and cross-validation.
