Biomedical Data Science
(formerly: Algorithmic Bioinformatics)
Teaching

Lecture: Biomedical Data Science & AI (summer semester)

NEWS: Due to the Corona crisis there will be NO repeat exam on 23 March!

Location: Please use this web link

Time: Tue, 11:00 - 12:30

Exercises: We, 9:30 - 11:00 Please use this web link

Prerequisites: Bachelor Computer Science or equivalent qualification

Content: This lecture gives a broad overview about data science methods, which are frequently used in biomedical applications. The goal is to understand the explained methods and being able to apply them correctly in the life science context. More detailed, the  the following topics are covered:

  • Statistical Basics of Data Mining
    • Descriptive statistics and statistical plots
    • Probability distributions
    • Statistical hypothesis testing
    • Linear models, logistic regression
    • Principal Component Analysis
  • Cluster Analysis
    • Basic methods: hierarchical clustering, k-means
    • Gaussian Mixture Models, consensus clustering, Non-negative matrix factorization
  • Classical Supervised Machine Learning Methods
    • Principles of supervised learning: bias-variance trade-off, regularized risk minimization
    • Penalized generalized linear models: lasso, ridge, elastic net
    • Random Forests
  • Deep Learning Approaches, e.g.:
    • (Convolutional) Deep Neural Networks, Recurrent Neural Networks
    • (Variational) Autoencoders
    • BERT language models

Prerequisites for getting credits are:

  • passing of exam
  • >50% of points from all homework assignments

Seminar: Machine Learning Methods in the Life Sciences / Advanced Methods in Biomedical Data Science & AI (summer semester)

Location: Please use this web link

Time: Mo, 9:30 - 11:00am

Prerequisites:

  • B.sc. Computer Science or equivalent qualification
  • Knowledge about basic supervised and unsupervised machine learning techniques, e.g. neural networks, Random Forests, SVMs, PCA

Credits:

  • presentation and discussion of one chosen topic
  • regular attendance

More specific requirements can be found here

Topics, presenters and dates

Lab Course: Machine Learning Hands-On (summer semester break)

Location: b-it, U1.105 / U1.108

Time: 3 - 7 August 2020, 9:00 - 17:00

Prerequisites: credits for lecture Biomedical Data Science & AI

Content: Attendees will work in small groups on real world machine learning tasks.

Prerequisite for getting credits is regular attendance and successful development of a solution to the given tasks.