1.The first “Statistical Learning” module mainly concerns the fundamentals of two of the main methods used in unsupervised learning: principal component analysis and cluster analysis.
2.On completion, the student will be able: i) to implement the main methods used in unsupervised learning; ii) to summarize the main features of a dataset and extract knowledge from data properly.
3.On completion, the student will be able to choose a suitable statistical model, apply it, and perform the analysis using a statistical software.
4.On completion, the student will be able to present the results from the statistical analysis, and which conclusions can be drawn.
5.On completion, the student will be able to understand the structure of unsupervised learning.