Data Science (joint bachelor TiU)

The Bachelor Data Science is a joint undergraduate program by Tilburg University and Eindhoven University of Technology. The bachelor is an English taught program that teaches you to analyze and apply complex, unstructured data to provide new insights to unsolved issues faced by government, industry and society.

This video gives you an impression of the program.

Intended Learning outcomes

Within the boundaries of the Dutch Qualification Framework, the Bachelor Data Science educates students to an academic Bachelor of Science (BSc) level. The Program Directors of both universities work together closely on drafting and monitoring the program objectives and Intended Learning Outcomes (ILOs). The ILOs are in line with the Dublin Descriptors that apply to the first cycle in higher education (the bachelor’s degree), safeguarding the academic level of the program. In summary, the program ILOs ensure that graduates: have knowledge and understanding of the core theories, principles and methods of data science and the societal context of data science; are able to apply their knowledge and understanding in practice, including the ability to make effective professional judgements regarding data and data-driven solutions; are data science professionals who can effectively communicate in society and practice; and are reflective, critical, lifelong learners (e.g., graduates are educated to the point of being able to enroll in specialized master’s programs across data science, data engineering and data analytics). In detail, the ILO s for the Bachelor Data Science are:
 

Knowledge and understanding:

1. Graduates have foundational knowledge and understanding of the theories, principles, methods and techniques for data acquisition, storage and processing.
2. Graduates have foundational knowledge and understanding of the theories, principles, methods and techniques focused on data analysis.
3. Graduates are familiar with social, legal and ethical aspects associated with data science in addressing business problems and societal and scientific challenges.

Applying knowledge and understanding:

1. Graduates are able to acquire, store and process data in a way that allows for data exploration and analysis.
2. Graduates are able to apply methods and techniques for data analysis.
3. Graduates know how to solve business problems and societal and scientific challenges, tackling them from a broad, interdisciplinary perspective in combination with methods and techniques for data analysis.

Making judgements:

1. Graduates are able to identify business problems and societal and scientific challenges that can be addressed using data science methods and techniques.
2. Graduates are able to assess the quality, potential and limitations of data sets and data science methods and techniques in relation to the business problem, societal challenge or scientific challenge at hand, and to understand and interpret the results.
3. Graduates have the ability to critically reflect on the context of their technical knowledge and solutions, including social, legal and ethical aspects.

Communication:

1. Graduates have good communication skills (both oral and written) and are able to visualize and communicate their work to both specialists and non-specialists.
2. Graduates can communicate clearly and work professionally in a multidisciplinary and international team.

Learning skills and attitude:

1. Graduates obtain the learning skills necessary to successfully continue their study at the level of a master’s program.
2. Graduates are open to new developments, knowledge and ideas in the data science field, and are able to proactively learn and apply state-of-the-art data science methods and techniques.
3. Graduates show a reflective and critical attitude towards themselves and their field, including a social, legal and ethical awareness with regard to the possibilities and limitations of data science.

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