Module

Voraussetzungen

Inhalte

The laboratory is implemented as one or several study projects using workflows for ML and science and related tools. For each project the following work steps have to be accomplished: • Getting acquainted with the state of the art • Project planning • Selecting the models and mechanisms to be used • Implementation of a prototype • Testing and evaluating the prototype • Documentation

Lernziele

After successfully completing the module, students will have acquired practical skills in developing and implementing machine learning workflows. They will be able to apply state-of-the-art-tools to utilize machine learning for reproducible science through reproducible, replicable, scalable, and portable workflows, related visualization and writing tools, and techniques relevant to implementing GDPR provisions for sensitive data.

Prüfungsleistung

• Executable and tested prototype (50% of total marks) • Complete documentation, 10-20 pages (20% of total marks) • Successful intermediate presentation of results, 10 min (10% of total marks) • Successful final presentation of results, 20 min (20% of total marks) A student passed the module, if he/she achieves 75% of the total.

Bemerkungen

• Study programme Artificial Intelligence M.Sc.: Compulsory elective module in complex „Seminars or Laboratories“ • Study programme Informatik M.Sc.: Compulsory elective module in complex "Seminare oder Praktika" (level 400)