Computational Diagnostics of Data, 5 op

Core content

• Classification of disease groups
• Business intelligence
• Survival analysis
• Genomics data
• Programming in R
• Quantitative assessment of results
• Predictive models

Complementary knowledge

• Computational implementation and interpretation; classification methods
• Data analysis methods for business processes
• Regression models for time-to event processes
• Preprocessing and normalization of gene expression data from microarray experiments
• Usage and programming in the statistical programming language R
• Statistical error measures; resampling techniques
• Linear regression, hypothesis testing; general models in data science