Course details

8.3593

Projects at the intersection of neuroscience and machine learning

 Independent Study Course
SS 2023 Prof. Dr. rer. nat. Tim Christian Kietzmann, Dr. rer. nat. Sushrut Thorat OFFLINE
4h/wk
8 ECTS 		M.Sc modules:
CC-MP-IDC - Interdisciplinary Course
CC-MW - Distinguishing elective courses
CC-MWP-AI - Artificial Intelligence
CC-MWP-NI - Neuroinformatics
CC-MWP-NS - Neuroscience
CS-MP-IDC - Interdisciplinary Course
CS-MWP-AI - Artificial Intelligence
CS-MWP-CNP - Cognitive (Neuro-)Psychology
CS-MWP-NI - Neuroinformatics
CS-MWP-NS - Neuroscience

CS-MW - Master elective course 		Tue: 14-16

Content and goal: In this course, you will work on your own in-depth project, either alone or (preferably) with at least one other student. The projects can be chosen from a list provided by the instructors or decided jointly with students and instructors. The course will begin with in-depth discussions to help you decide the details of the projects. In the subsequent weekly meetings, you will provide brief summaries of your progress - what is done, what are the roadblocks, and what are the next steps, and the group and instructors will provide guidance on how to proceed further. Students will be required to review each-other’s code to learn to write clearly/accessibly, and to take the perspective of an external code-reviewer. By the end you will have completed a project at the intersection of neuroscience and machine learning, you will have learned to review code, to communicate problems, and you will have gotten an in-depth insight into the research field as such. You will be required to document your project in the form of a research paper or a thesis. Target audience: Master students who have at least completed an introductory course in cognitive neuroscience or neurobiology and an introductory course in deep learning. Students are also required to be proficient in python. Grading: If you participate with a *standalone* project your grade will be based on your project, documentation and your active participation in the weekly meetings. If you take this seminar for your thesis, no credit/grade can be given.