Data Science and Society

Become a Data Analyst and provide solutions for societal challenges with the use of complex data sets. Add value to a team, company or organization with a combination of technical skills, knowledge about legal and ethical issues related to data science, and the ability to effectively communicate with professionals and researchers from different disciplines. Specialize by following one of four tracks: Business, Governance, Media, or Health.

Data Science and Society is a one-year multidisciplinary Master’s program where you learn how to use data science methodologies to build upon the domain-specific knowledge you have already acquired.

The program is built on a sound mix of theory and practice. The core principle of the program is learning by doing. You will specialize by following one of four tracks: Business, Governance, Media, or Health.

You will learn how to:

• Write code in python, R, and/or SQL to transform and visualize data and then identify patterns and gather insights from large and complex datasets.
• Build, train, test and evaluate machine learning models. You learn to select the model(s) most appropriate for the data you have and the task you want to solve.
• Translate the results of your machine learning analyses into actionable solutions and recommendations.
• Use these tools and skills ethically within the EU laws and regulations for data privacy.

This program does not require prior knowledge on programming, data processing, or machine learning.

Tracks

You will be admitted to one of four tracks. This is to encourage you to select elective courses and a thesis project that align with the knowledge you have gained in your previous education. The content of your previous education determines to which track(s) you can be admitted.

• Business track. Work with real-world data from customers and businesses to build models that generate insights and recommendations to improve business strategy.

• Governance track. Use data science methods that can minimize bias and provide explainable predictions. Work with data at local, national, and international scales to produce insights that can lead to fair, transparent, and sustainable governance and policy.

• Health track. Harness the variety of data sources in the health domain (medical images, text, demographics, etcetera) to design and implement analyses that can be used to improve health and wellbeing.

• Media track. Employ advanced signal processing and extraction techniques to generate insights about how people communicate to and with each other across a variety of mediums.

The examples of thesis topics on the Programs and courses page illustrate the wide variety of data and research questions you can focus on within the various tracks.