The program combines five disciplines, and this is how they work together:
Data engineering is about designing systems handling the data infrastructure. Data analytics is about data science and AI models you run on the data. Since all models inevitably provide an output, interpreting, explaining, and interacting with this output is critical. That is why data-driven decision-making is needed. Data-driven business development is about translating the models into business impact, supported by law and ethics that the first four disciplines need to align with.
Compulsory courses
In the first year, you will follow 7 core courses:
Semester 1.1
Data Intrapreneurship in Action
Data Mining
Data Engineering
Strategy and Business Models
Social Network Analysis for Data Scientists
Semester 1.2
Data Consultancy in Action
Interactive and Explainable AI Design
In the second year, you will follow 3 core courses:
Semester 2.1
Data Entrepreneurship in Action
Intellectual Property and Privacy
Master’s thesis
Semester 2.2
Data Ethics and Entrepreneurship
Master’s thesis
In Action courses
A unique feature of the program comprises a series of ‘in Action’ courses. Working in a team, you will learn by doing. You will apply data science methods to create business or societal value from data for companies and organizations. For example: advise city municipalities on the impact of cultural events using parking data of ParkNow. Or predict the costs and duration of a legal case for legal firm DAS. You will help WWF prevent illegal deforestation in developing countries, and help improve credit provision to SMEs done by fintech scale-up Floryn.
Elective courses
On top of the mandatory courses and master’s thesis, you have to pass 5 elective courses worth 30 EC in total. You are expected to choose one of the below specializations. To qualify for a certain specialization you should pass at least three courses from the relevant courses, including the core course (the course which is first in the list, marked in bold). You are strongly recommended to write your thesis in line with the specialization.
Data Engineer; Advanced Data Architectures, Cybersecurity, Real-Time Process Mining, Data-Driven Food Value Chain, Data Forensics.
Data Scientist; Deep Learning, Prescriptive Algorithms, Real-Time Process Mining, Causal Interference for Business Development, Natural Language Processing.
Data Entrepreneur/Consultant; Data-Driven Service Innovation, Data Visualization, Decision Support Systems, Entrepreneurial Finance, Natural Language Processing.
Data-Driven Researcher; Research in Action/Research Internship, Prescriptive Algorithms, Decision Support Systems, Causal Interference for Business Development, Natural Language Processing.
Master's thesis
You will write your thesis during the second year (30 EC). Similar to 95% of DSBE students you will do the thesis project at an external company or organization. The thesis has to advance one of the four scientific disciplines and create business or societal impact at the same time. Examples of theses done by our students in the past:
Predicting the occurrence of a change in a data stream (‘concept drift’) for Mobiquity and adapt their Machine Learning models accordingly and dynamically (Data Engineering).
Calculating the expected possession value in football using a componential approach in collaboration with KNVB (Data Analytics).
Supporting breast cancer treatment using deep learning algorithms in collaboration with Catharina Ziekenhuis (Data Analytics).
Help Bain Management Consulting group identify targets for potential acquisitions for their clients in the private equity market (Data-Driven Business Development).
Watch a trial lecture
Do you want to experience what a lecture of this Master's program is like? Watch the recording of a lecture and get an impression what to expect.
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