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Medical Biometry Zertifikat Medical Data… Certificate Medical… Curriculum

Curriculum

The study program is structured according to the following curriculum. Further information can be found in the
 

module manual 2024/25

Module 1: Data Scientist’s Toolbox

Module ECTS Topics

Introduction into Data Science

1.5 days, 2 ECTS

Introduction into Data Science including an overview of all courses,
Introduction into R.

Data processing, visualisation, reproducibility and presentation

2.5 days, 4 ECTS Reading in and processing data in R, visualisation of data structures, setting up reproducible analyses.
     

Module 2: Statistical Modelling

Module ECTS Topics

Regression models

2.75 days, 4 ECTS Linear and non-linear regression, introduction into variable selection, introduction into regularised regression models, model goodness, re-sampling methods, implementation in R.

Generalisied additive models

2.75 days, 4 ECTS

Polynomial functions for modelling influence variables in regression models, splines, non-parametric models, implementation in R.

Bayesian statistics

2.75 days, 4 ECTS

Bayes theorem, Bayesian regression, Markov Chain Monte Carlo methods and Gibbs Sampling, implementation in R.

     

Module 3: Machine Learning

Module ECTS Topics

Supervised Learning

2.75 days, 4 ECTS

Regularised models, variable selection, neuronal nets, decision trees and random forests, bagging and boosting

Unsupervised Learning

2.00 days, 4 ECTS

Clustering, dimensionality reduction, introduction into deep learning, generative models

     

Module 4: Practical application

Module ECTS Topics

Applied Data Science

2.75 days, 4 ECTS

Practical application of the methods learned in the first three modules by analysing a data set in groups

Projekt work

3 months, 8 ECTS

Independent project work and evaluation of a data set including presentation and the creation of a statistical report.

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