These courses are particularly recommended for students who have not attended, during the bachelor degree, courses in horticulture, genetics, systematic botany and agronomy but can also be taken just for a review of these topics


Statistical Learning (Educational Seminars)

University of Pavia


Instructor Daniel Felix Ahelegbey



Class Meetings Fridays (9:00 – 11:00 am)

Classroom Room 15

The general purpose of the proposed educational seminars is to introduce students to the discovery of the most popular statistical learning methods, both on the theoretical and practical sides.

The cycle of seminars is organized in 16 hours of lectures (8 lectures). Specifically: the first part presents the basic statistical learning models (linear and logistic regression models) and an overview of the main metrics used for comparing different models and selecting the best one; the second part of the course is addressed to the introduction of a set of more complex statistical learning models and classification techniques (cluster analysis, neural network and tree models).

The statistical software R is used throughout. Case studies and dataset examples will be used extensively to give students an appreciation for the application of statistical and computer science methodologies to the financial and credit scoring settings.

At the end of the cycle of seminars, students have to describe and discuss in a written report the results provided by the analysis of a real dataset implemented in R.

The detailed program and the related schedule is reported below.

1. Introduction to R Programming

2. Linear Regression

3. Logistic Regression

4. Model Selection

5. Networks

6. Cluster Analysis

7. Tree Models

8. Neural Networks

In questo tutorato verranno trattati alcuni argomenti di base di Analisi Matematica che non trovano spazio nei corsi di Analisi 1 e 2.