In the last decades an unpredicted explosion in the amount of data collected by businesses has involved new opportunities to decision makers. Faced with new opportunities from emerging technologies strategic interests have evolved towards the extraction of valuable information from these large quantities of data, leading to the emergence of Data Mining and Artificial Intelligence Techniques.
Data Mining and Artificial Intelligence Techniques encompass a range of methodologies able to extract knowledge from large databases. They allow detecting “interesting" and “useful" patterns or relationships in datasets. The underlying idea is that computer's ability to process a large amount of information can help to analyze complex problems by using use human-like reasoning and intelligence.
Data Mining and Artificial Intelligence Techniques have been applied in many diverse areas. This course will provide an overview of some commonly used Data Mining and AI Techniques and relate them to Management and Business applications.
 

Learning objectives of this course are:

* to understand basic concepts and techniques of Data Mining.
* to develop skills of using recent data mining software
* to be able to approach practical problems by usig AI techniques.

 

• Introduction to Data Mining and Artidicial Intelligence techniques
• Data preprocessing (data normalization, discretization, feature and instance selection…)
• Association/ Sequences analysis/ Rules extraction
• Machine Learning (Decision Trees, Nearest Neighbors, Neural networks, Genetic Algorithms, …)
• Approximate Reasoning (Fuzzy logic, Qualitative Reasoninng, …)
• Succesful Data Mining & AI applications in Business
 

Lectures, class discussions, practical sessions and exercises using Data Mining software.
 

Class participation and Assignment (written individually), 2500 words.
 

WITTEN, I.A. & FRANK, E. (2005); DATA MINING. Second Edition. Morgan Kaufmann Publishers.

WEISS, S.M & INDURKHYA, N. (1998); Predictive Data Mining: A practical guide. Morgan Kaufmann Publishers.

PANG-NING TAN, MICHAEL STEINBACH & VIPIN KUMAR; (2006) Introduction to Data Mining, Ed. Addison-Wesley

JIAWEI HAN & MICHELINE KAMBER (2006); Data Mining: Concepts and Techniques, 2ed. The Morgan Kaufmann Series in Data Management Systems.
 

Wednesday 21/04/10
From 09:00 h. to 13:00 h.

Thursday 29/04/10
From 09:00 h. to 13:00 h.
Wednesday 12/05/10
From 09:00 h. to 13:00 h.
Thursday 13/05/10
From 09:00 h. to 13:00 h.
Wednesday 09/06/10
From 09:00 h. to 13:00 h.
Thursday 10/06/10
From 09:00 h. to 13:00 h.