- Docente: Elena Morotti
- Credits: 4
- Language: English
- Teaching Mode: Traditional lectures
- Campus: Bologna
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Corso:
Second cycle degree programme (LM) in
Politics Administration and Organization (cod. 9085)
Also valid for Second cycle degree programme (LM) in International Relations (cod. 9084)
Learning outcomes
The course aims at introducing students to the utilization of one of the main statistical packages for data analysis and presenting to them the basic elements of micro-data management and analysis. By the end of the course students will be familiar with the statistical package interface and be able to: load different types of data and different file formats into the statistical package, perform basic data management operations and conduct monovariate and multivariate statistical analyses using the software introduced during the course.
Course contents
WS4 - BIG DATA
1) Introduction to Data Mining (main applications, basic algorithms)
2) Data Preparation (feature extraction, data cleaning, data reduction and transformation)
3) Similarity and distances (multidimensional data, text/temporal/graph similarity measures, supervised similarity functions)
4) Association Pattern Mining (association rules, frequent itemset mining algorithms and alternative models)
Readings/Bibliography
1) Notes from the teacher
2) Aggarwal, C. C. (2015). Data mining: the textbook. Springer.
3) Zaki, M. J., Meira Jr, W., & Meira, W. (2014). Data mining and analysis: fundamental concepts and algorithms. Cambridge University Press.
Teaching methods
Lectures and exercises.
The class attendance is mandatory.
Assessment methods
Students are asked to write a report about the exercises assigned during the course.
Teaching tools
Slides from the teacher.
Office hours
See the website of Elena Morotti