Data Warehousing and Machine Learning (Data Mining)

Spring 2002

What is Data Mining ?

Together, data warehousing and machine learning comprise what is known as data mining or knowledge discovery in databases (KDD). Data warehousing can be briefly described as creating a copy of transaction data specifically structured for query and analysis. Machine learning is concerned with computer programs that automatically improve their performance through experience.

A more detailed description of data mining and the contents of this course can be found in a PDF document (also available as a PostScript document).


Michael O. Akinde, room no. E1-201b.
Uffe B. Kjśrulff, room no. E1-101a.

Data Warehousing Text

Machine Learning Textbook

Tom Mitchell (1997), Machine Learning, McGraw Hill.

Available at Aalborg Centerboghandel, Fredrik Bajers Vej 7B, at a price of DKK 470 (10% discount for students).

Errata for printings one and two available in PostScript and PDF formats.

Review of the book available in PostScript and PDF formats.

Lecture plan (and slides)


Date & time


Introduction to Data Warehousing Mon 25 Feb 10:15 E1-214

Introduction to Machine Learning Wed 27 Feb 10:15 E1-214

Advanced Multi-dimensional Modelling Thu 21 Mar 12:00-16:00 E1-212

Decision Trees Wed 6 Mar 10:15 E1-214

Building the Data Warehouse Thu 21 Mar 12:00-16:00 E1-212

Artificial Neural Networks Wed 13 Mar 10:15 E1-214

Complex OLAP Fri 22 Mar 8:00-16:00 E1-214

Bayesian Learning: MAP & ML Wed 3 Apr 8:30 E1-214

Data Mining - A Database Perspective Fri 5 Apr 9:30-16:00 E1-212


Bayesian Networks, EM Algorithm Wed 3 Apr 10:15 E1-214


Some Other Machine Learning Algorithms Wed 10 Apr 10:15 E1-214


DW Workshop Fri 17 May 8:30 E1-214


DW Workshop Fri 17 May 10:15 E1-214


ML Workshop Fri 17 May 12:30 E1-214


ML Workshop Fri 17 May 14:15 E1-214

Examination (in Danish)

Examination requirements (ps file or pdf file)

This page is maintained by Uffe Kjærulff.
Last updated 6 June 2002.