B0267 - WORKSHOP ON SKILLS DEVELOPMENT - DATA SCIENCE (ADVANCED) (A)

Learning outcomes

Workshops are designed to provide students with transversal and multidisciplinary skills that can prove useful in their future careers. At the end of the course, the student has deepened some Machine Learning algorithms for Data Mining and is able to use them for data analysis.

Course contents

This workshop covers the machine learning techniques for classification and clustering, with a final focus on their applications for Text Mining.

Topics will be introduced theoretically but also verified in R-based softwares during the laboratory hours.

More in details, the course contents are:

• Algorithms for classification (kNN, SVM, logistic regression);
• Algorithms for clustering (k-means, mean-shift clustering, hierarchical clustering);
• Techniques for pre-processing on textual data;
• Techniques and algorithms for Text Mining;
• Presentation of case studies and applications of Data Science and Text Mining.
  

IMPORTANT: in order to attend this workshop, it is necessary to have a basic knowledge of the core elements of Data Science and programming in R language. The course is designed for students that have previously attended one module (A or B or D) of the "WORKSHOP ON DATA SCIENCE" in their first year.

Readings/Bibliography

James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (Vol. 112, p. 18). New York: springer.

Slides by the teacher

Teaching methods

Frontal lessons

It is necessary to previously attend the online courses on health and safety for students of University of Bologna, "module 1" and "module 2", available at https://elearning-sicurezza.unibo.it/?lang=en

Assessment methods

Evaluation of a final project

Teaching tools

Slides by the teacher

Office hours

See the website of Elena Morotti