The course aims to provide the student with the tools to extract relevant information from large amounts of data, with particular attention to statistical learning (statistical learning) both in a predictive and non-supervised context (supervised and non-supervised learning). Besides, this course introduces students to Text mining. Text mining is a recent field of research whose development is strictly linked to the increasing volume of online text data and the development of statistical methodologies and algorithms for information retrieval and automatic classification.
Analysis will be performed through the statistical language R.

LEARNING OUTCOMES
1. Understand the nature of multivariate and textual data and the statistical techniques exploited to analyse them.
2. Understanding and ability to explain the fundamentals of algorithms for extracting information from multivariate and textual databases
3. Ability to apply the principles of statistical reasoning in the preparation and interpretation of company reports
4. Ability to use the R software for statistical analysis

Making judgements
- To learn the logical and statistical concepts that are indispensable for working independently in the research, selection and processing of data relevant in the Data mining and Text mining context.
Communication skills
- Learn the terminology and statistical techniques to communicate or correctly discuss the results of the analysis of company data relevant in the Data mining and Text mining context.