Minor Data Science - Vrije Universiteit Amsterdam

Extracting knowledge and insights from data

The minor consists of a number of advanced courses that complement the corresponding Bachelor programmes in Information Sciences, Computer Science and Artificial Intelligence in the direction of data collection and data-driven solution methods.

The minor is composed by two compulsory courses on Introduction to Data Science, and Data Wrangling, plus two constrained choices, where students select the courses that better fit their interests.

In the first constrained choice students can choose one course between: Data Structures and Algorithms*, or Strategic Management of Technology and Innovation (marked as '1 out of 2' in the list below).

In the second constrained choice students can choose two courses between: Data Analytics and Privacy, Information Retrieval, or Logistics Analysis (marked as '2 out of 3' in the list below).

*Students from Computer Science cannot choose this course as it is already part of their curriculum. Students from Artificial Intelligence who have followed the course Data Structure and Algorithms for AI XB_0043 also cannot choose this course because the courses are too similar.

Related VU master’s programmes:

Introduction to Data Science (compulsory)

This introductory course will provide an overview of the field of Data Science. We will discuss the different specialties within data science and the ethical issues that arise around data collection and use.
See study guide.
Data Structures and Alg for AI (P1)

The course is concerned with data structures and the design and analysis of algorithms.
See study guide.
Strategic Management of Technology and Innovation (1 out of 2)

This course focuses on the strategic management of technology and innovation. Innovation refers to the development and implementation of new products, services, processes and business models and many of those innovations are enabled by technological developments. Innovation is crucial for business organizations to stay competitive in ever changing markets.
See study guide.
Data Analytics and Privacy (2 out of 3)

Data analytics has the ability to pose significant challenges to privacy, human autonomy and dignity. The ability to influence people in ways they can act against their own interest is what political scientists describe as power.
See study guide.
Information Retrieval (2 out of 3)

This course covers the core aspects of information retrieval and search engines, including indexing, Boolean retrieval, the different types of queries, query execution, the vector space model, web crawling, networks, link analysis, PageRank, classification, and clustering.
See study guide.
Logistics Analysis (2 out of 3)

The overall objective of the course Logistics Analysis is to furnish you with knowledge and skills to analyze logistics problems in a variety of industries including manufacturing, transportation and services.
See study guide.
Data Wrangling (compulsory)

Data wrangling is the process of gathering data in its raw form and molding it into a form that is suitable for its end use.
See study guide.

Data Science

Course overview

Introduction to Data Science (compulsory)

Data Structures and Alg for AI (P1)

Strategic Management of Technology and Innovation (1 out of 2)

Data Analytics and Privacy (2 out of 3)

Information Retrieval (2 out of 3)

Logistics Analysis (2 out of 3)

Data Wrangling (compulsory)