Delivered at:: Department of Statistics and Data Analysis

Course type:: Elective course

When:: 4 year, 1 module

Instructor

Кузин Сергей Сергеевич

Full Syllabus

Abstract

Data Mining is the creation of new knowledge to solve business problems, by using business knowledge to discover and interpret patterns in data. The course contents both methodology of the data mining process and practical guide to data preparation, modeling, and deployment analytics into business processes. It covers the following main types of modelling techniques: classification, regression, clustering, anomaly detection and association rules. Special attention will be given to the hands-on data analysis using available software tools.

Learning Objectives

To introduce students to the concept of data mining process aimed at solving business problems. To provide knowledge of the basic data mining techniques. To gain practical skills in in data analysis, building models and evaluating their quality.

Expected Learning Outcomes

Mastering clustering methods
Mastering data preparation
Mastering Regression.....
Mastering the classification
Mastering the detection of outliers
Mastering the process of data mining
Mastering the rules of the association

Course Contents

1. Data Mining process
2. Data preparation
3. Classification
4. Regression
5. Clustering techniques
6. Outlier detection. Feature selection and dimensionality reduction
7. Association rules

Assessment Elements

Домашняя работа
Домашняя работа
Контрольная работа

Interim Assessment

2023/2024 учебный год 1 модуль
0.33 * Домашняя работа + 0.33 * Домашняя работа + 0.34 * Контрольная работа

Bibliography

Recommended Core Bibliography

Han, J., Kamber, M., Pei, J. Data Mining: Concepts and Techniques, Third Edition. – Morgan Kaufmann Publishers, 2011. – 740 pp.
Robert Nisbet, John Elder, & Gary D. Miner. (2009). Handbook of Statistical Analysis and Data Mining Applications. Academic Press.

Recommended Additional Bibliography

Toomey, D. (2014). R for Data Science. Birmingham, UK: Packt Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=933765

Bachelor’s Programme 'Economics and Statistics'

Contacts

Data Mining