Master Project AI

2019-2020

Course Objective

The Master programme in Artificial Intelligence is a scientific program
that aims to provide the student with the knowledge, experience and
insights in AI needed to autonomously carry out his/her professional
duties. It is designed to prepare the student
for further education as scientific researcher (Ph. D. studies) as well
as to offer a solid basis for a career in business at an academic level.
Moreover, the program aims at educating students to acquire a practical
understanding of the position of the field of
Artificial Intelligence within a broad scientific, philosophic and
societal context. The Master Project AI marks the end of the Master
programme in Artificial Intelligence and aims to cover all its intended
final learning outcomes.

The learning outcomes of the course (based on the Dublin descriptors)
are as follows:
1) Knowledge and Understanding (reading up on relevant AI techniques for
the project at hand);
2) Applying Knowledge and Understanding (applying the AI techniques
within the project);
3) Making judgements (finding an appropriate technique, applying the
technique for a specific case);
4) Communication skills (reporting on your approach, choices and your
results and how to present your work)
5) Learning skills (e.g. finding new relevant techniques, assessing
their suitability, etc.).

Course Content

The Master Project AI marks the end of the Master programme in
Artificial Intelligence. Information about possible projects (incl.
internships) can be found on the Master Projects Canvas site and on the
site of the internship office vu.freshheroes.nl. Internships proposed by
students need prior approval by a staff member, who will also be
involved in the project supervision.

The graduation project lasts between 5 and 6 months. The students
participate in the KIM (Kunstmatige Intelligentie Middag/Artificial
Intelligence Afternoon) and present their work twice (once at the start
of the project and one in the end) and they attend presentations of
other students.

For more details, see Canvas.

Teaching Methods

The Master Project AI must always be supervised by at least one staff
member. The second supervisor can be an employee of the organisation
offering the internship. Internships proposed by students need prior
approval by a staff member. The grading is performed by two examiners
who hold a PhD degree, of which at least one should be a VU staff member
(typically the supervisor). The second examiner needs to comply with the
VU's formal requirements for second examiners as well, even in the case
that (s)he is not a staff member at the VU or a collaborating
University.

Method of Assessment

The final grade will be based on the quality of the research, the
written thesis, the KIM presentations and the participation in the KIM.

Target Audience

mAI

Additional Information

For all rules, assessment criteria, contact persons, and many practical
tips for your master project, see the Master project page on Canvas
(inclusive the "Manual for the Master Project AI").

General Information

Course Code X_400285
Credits 30 EC
Period Ac. Year (sept)
Course Level 600
Language of Tuition English
Faculty Faculty of Science
Course Coordinator dr. M. Hoogendoorn
Examiner
Teaching Staff dr. A.C.M. ten Teije

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Lecture
Target audiences

This course is also available as: