Curriculum

The programme runs over two years and encompasses 120 credits, including a thesis.

• Programme syllabus (pdf)

First year of studies

Mandatory courses:

• Data mining and Statistical learning, 15 credits
• Data mining – clustering and association analysis, 15 credits
• Introduction to advanced academic studies, 3 credits
• Philosophy of science, 3 credits

 Supporting courses:

• Linear statistical models, 12 credits
• Database technology, 6 credits
• R programming, 6 credits
• Probability and Statistics, 6 credits

Profile courses: 

• Probability theory , 6 credits
• Theory of statistics, 6 credits
• Computational Statistics, 6 credits
• Neural networks and learning systems, 6 credits
• Multivariate statistical methods, 6 credits
• Web programming and interactivity, 6 credits
• Advanced web programming, 6 credits

Second year of studies

Mandatory courses:

• Bayesian learning, 6 credits
• Visualization, 6 credits
• Master’s thesis, 30 credits

Profile courses:

• Survey sampling, 6 credits
• Time series analysis, 6 credits
• Data mining project, 6 credits;
• Health statistics, 6 credits
• Text mining, 6 credits
• Optimization, 6 credits

Page responsible: webbredaktoren@liu.se
Last updated: Tue Oct 09 15:22:26 CEST 2012