CRM: Centro De Giorgi
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Summer School of Mathematics for Economic and Social Sciences

Data Mining and Machine Learning for Business and Organizations

11 September 2017 - 15 September 2017

Planned Activities

Syllabus

  • Clustering models for customer segmentation. Discussion of real cases. Hands-on project: segmentation of a base of anonymized customers from the retail industry. Clustering models for competitive intelligence.
  • Patterns and association rule mining for market basket analysis. Hands-on project: mining association rules from sales data of the retail industry.
  • Prediction models for promotion performance and churn analysis. Discussion of real cases. Hands-on project: churn prediction from a base of anonymized customers from the retail industry.
  • Analysis of human mobility patterns by mobility data mining from big data. Mining official data for understanding of human behavior.
  • Social network analysis for undestanding diffusion phenomena. Viral marketing. Application of data mining to geo-marketing. Analysis of innovators. Predictive models for fraud detection.

Textbooks

  • Gordon S. Linoff e Michael J. Berry. Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management. Wiley, 2011.
  • Pang-Ning Tan, Michael Steinbach, Vipin Kumar. Introduction to Data Mining. Addison Wesley, ISBN 0-321-32136-7, 2006
  • http://www-users.cs.umn.edu/~kumar/dmbook/index.php

Reading about the "data analyst" job

  • Data, data everywhere. The Economist, Feb. 2010 download
  • Data scientist: The hot new gig in tech, CNN & Fortune, Sept. 2011 link
  • Welcome to the yotta world. The Economist, Sept. 2011 download