Entrepreneurship for AI and Computer Science

Dit vak wordt in het Engels aangeboden. Omschrijvingen kunnen daardoor mogelijk alleen in het Engels worden weergegeven.

Doel vak

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
- 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.

Inhoud vak

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 was taught for the first
time for students of the master Computer Science (joint degree of the
Vrije Universiteit Amsterdam and the University of Amsterdam) and the
master Artificial Intelligence (Vrije Universiteit Amsterdam), in the
form of this elective Entrepreneurship for AI and CS (Artificial
Intelligence and Computer Science). This elective is only for students
from these two masters.

This course is based on three pillars:
- The transfer of academic knowledge in the field of entrepreneurship,
during lectures and study of academic papers from renowned international
journals and academic 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 approach and the study of an own
real life case.
Scientific research is not an explicit part of this course, although it
is one of the four pillars of academic entrepreneurship education.
However, scientific research will be dealt with directly and indirectly
within all three mentioned pillars of this course.


Lectures, workshops, coaching sessions, cases and small assignments.
Presence with all lectures, workshops and coaching sessions and timely
submission of the cases and the small assignments are mandatory.


The final grade is based on a team assignment (the Business Model Canvas
approach) and an individual written exam. Both the assignment and the
exam determine 50% of the final grade. Both the assignment and the exam
must be of sufficient quality.


A series of articles and one book, that will be presented in the course

Algemene informatie

Vakcode XM_0009
Studiepunten 6 EC
Periode P5
Vakniveau 400
Onderwijstaal Engels
Faculteit Faculteit der Bètawetenschappen
Vakcoördinator prof. dr. E. Masurel
Examinator prof. dr. E. Masurel
Docenten prof. dr. D. Iannuzzi
prof. dr. E. Masurel

Praktische informatie

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Werkvormen Hoorcollege, Werkgroep

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