Course registration
To be admitted to this course, you have to register for the course in the registration system for seminars and labs by the Computer Science department and you have to get a seat.
Course Description
AI practitioners explore the solution space when developing AI solutions. They search for information and solutions on similar AI problems through blog entries, academic publications, and existing Git repositories.
They evaluate the content based on various criteria, such as:
- How well does the content address my AI problem?
- How credible is the presented approach?
- How difficult is it to reuse the solution?
Candidates that make it onto the shortlist are often collected in open tabs or simply remembered.
In this lab, we will develop a user-friendly tool to assist AI practitioners evaluating and managing potential solutions. Therefore, we will explore the usage of LLMs, text mining and repository mining.
- The teams are put together in an interdisciplinary manner, so that not all skills have to be combined in one person.
- Practical Skills: ML Basics, Frontend, Backend, Data Management
Dates
- TBA
Regular dates
- TBA
Individual dates
- Kick-off meeting, on the first regular date.
- Alpha milestone presentation, expected to take place on one of the regular dates.
- Presentation of the beta milestone, expected to take place on one of the regular dates.
- Final presentation, *date to be announced.