Capstone Applied AI Project

In this course students will apply the topics learned in all previous 'AI Minor' courses on a group project proposed by one of the faculties. Each project will be supervised by an academic staff (PhD student, postdoc, assistant/associate/full professor) from a respective faculty. Those supervisors will be responsible for the generation of the research topic of the Capstone project.

The meetings with the client and TA are mandatory, and are biweekly or weekly depending on the week. They can be flexibly arranged, possibly online.

During the group project multiple deliverables are expected to be presented:

- Project plan (at the start of the project)

- Midterm presentation (mandatory if requested, in discussion with your supervisor, TA, course organizer)

- Final presentation

- Ethical reflections on the project

- Source code or other deliverables/results of the project

Grading is group-based and on the basis of a rubric. We will stick to 1 grade per group, unless there was a student that performed exceptionally well or poor in the group, in that case, we may decide to deviate from the group grade and issue individual grades.

Projects have NO RESIT, in case of failure of this course a redo in next academic year will be enforced. Following the EEMCS OER Implementation Regulations Article 2.4, it is not reasonable to offer a redo opportunity for the whole project as it is a large group process. However, for the components: ethical reflections, final presentation, source code and other deliverables, there is a repair opportunity under the following conditions:

1. An examiner will offer a student a repair opportunity when the obtained result of a (partial) assessment other than written examination is between 4.0 and 5.7 for the regular examination opportunity.

2. The maximum obtainable result for the repair option is a 6.0.

3. The repair opportunity takes place no later than the quarter following the regular examination opportunity in the same academic year.

Please also refer to the TER Article 5 for full information.

Disclaimer: information may change depending on unforeseen circumstances or measures (see: TER Art 29, sub 4)