Department of Statistics

Lund University School of Economics and Management

STAN45 Data Mining and Visualization

7,5 credits

Advanced course, prerequisites: Bachelor degree with at least 60 ECTS in statistics

This course covers methodology, major programming tools and applications of data mining and statistical learning. Considerable effort is put on computational aspects of algorithms that make them efficient for handling very large scale data sets. Data mining and learning techniques developed in fields other than statistics, e.g., machine learning and signal processing, will also be introduced.The course also explores the question of what visualization is, and why one should use visualizations for quantitative data.

Syllabus and Course Literature


Simon Reese
Associate senior lecturer

Simon Reese