Linear algebra Probability and Data Analysis Introduction to Statistical Modeling

Become familiar with different analytical tools, based on data, to make business decisions Capacity to develop skills to analyze and find relationships between many variables/features Know how to evaluate supervised-learning models Develop skills to classify observations based on probabilistic learning and machine learning tools Handle the R language for statistical-learning tools

1. Introduction to the statistical learning 2. Evaluation of learning methods 3. Unsupervised learning 3a. Clustering 3b. Dimension reduction 4. Probabilistic learning 4a. Statistical classification 4b. Regression and prediction 5. Case studies

Theory (3 ECTS), Practice (3 ECTS). 50% lectures with teaching materials available on the Web. The other 50% practical sessions (computer labs).