Fall 2026, September 08 to October 15.
Instructor: Vassilis Athitsos
Lectures: Tuesdays, Thursdays, and one Friday, 9:25am-12:10pm China Time
Classrooms for lectures:
This course offers an introduction to data mining. Topics include data preprocessing, data cleaning, data visualization, types of data, similarity measures, regression analysis, dimensionality reduction, model evaluation, clustering analysis, and association rule mining. A strong programming and algorithmic background is assumed, as well as familiarity with linear algebra (vector and matrix operations).
Prerequisites: Familiarity with linear algebra, probability and statistics, algorithms, programming in Python.