Entrepreneurship for AI and Computer Science

2018-2019

Course Objective

After having finished this course successfully, the student is able to:
- Master the obliged literature on entrepreneurship from the course.
- Critically make use of theoretical foundations for practice-based
ideas.
- Think ‘out of the box’ concerning entrepreneurial ideas.
- Approach entrepreneurial challenges with extra confidence.
- Develop a business idea according the regular criteria.
- Thoroughly communicate the business plan in a short pitch.

Course Content

In recent years, entrepreneurship education has shifted from the
exclusive domains of business administration and economics to many other
domains as well, including beta sciences. In the academic year
2018/2019, the subject of entrepreneurship will be taught for the first
time for students in artificial intelligence and computer sciences at
the Faculty of Science at the Vrije Universiteit Amsterdam, in the form
of an elective. This is the third elective in entrepreneurship at this
Faculty, next to Entrepreneurship for Physicists (E4P) and
Entrepreneurship in Data Science and Analytics (EDSA).
This course is based on three pillars:
- The transfer of academic knowledge in the field of entrepreneurship,
during lectures and study of academic papers and books.
- The development of personal entrepreneurial soft skills, which may
contribute to entrepreneurial success, during interactive workshops.
- To come from a business idea to a solid business plan, with the help
of the adjusted Business Model Canvas 2018 approach and the study of an
own real life case.
Scientific research is not an explicit part of this course, but will be
dealt directly and indirectly within all three pillars.

Teaching Methods

Lectures, consultancy sessions.
Presence with all lectures and consultancy sessions is mandatory.

Method of Assessment

This course loads 6 ECs. The final grade for this course is based on an
essay (5%), an exam (50%) and the case (45%). All forms of examination
should be sufficient, i.e. a grade higher than 5.5. The essay and the
written exam are individual assignments whereas the case is a team
assignment. Next to these three obligatory aspects of the course, a
number of small assignments and/or cases have to be delivered.
Additional to the regular lectures, consultancy sessions are organized,
in which the groups meet with one of the lecturers, for the further
development of their business model canvases.

General Information

Course Code XM_0009
Credits 6 EC
Period P5
Course Level 400
Language of Tuition English
Faculty Faculty of Science
Course Coordinator prof. dr. E. Masurel
Examiner prof. dr. E. Masurel
Teaching Staff prof. dr. D. Iannuzzi
prof. dr. E. Masurel

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Lecture, Study Group
Target audiences

This course is also available as: