RENPRO Method Course: Machine learning for beginners

Target group: PhD students of theTRR 374, open for medicaldoctoralstudents, PostDocs and Clinician Scientistsin the TRR 374, and for interested doctoral students (via the graduate schools)

Credit Points: Full participation can be counted as a method course with 0.6CPs within the Curriculumof the Graduate Schools (RIGel, BioMediGS, life@FAU)

Registration and contact: michaela.kritzenberger@ur.de

Registrationof TRR members requested by April 15, 2024
Registration for those interested via the graduate schools: April 16-22, 2024

Maximum number of participants: 20 (first come first serve)

Contents:

Join us for a beginner-friendly short course on machine learning. This course will cover fundamentalconcepts of regression and classification in supervised learning, including multiple regression and k-nearest neighbors, along with key principles such as training-testing split, bias-variance trade-off, leastsquares optimization, and numerical minimization using gradient descent.Through hands-on sessionsusing Jupyter Notebooks, participants will gain practical experience in data analysis without requiringprior programming knowledge. The course emphasizes the universal applicability of machine learningacross diverse contexts, enabling participants to understand data patterns with minimal priorknowledge.Participants areaskedto bring their laptops. If you do not have your own laptop, pleaselet me know, we have some laptopsand while examples from kidney research will be highlighted, theconcepts and methods covered are broadly applicable to various data problems beyond the biomedicaldomain.

Schedule