Apply today

Curriculum of the Master of Data Science for Public Policy

Build a strong technical foundation in mathematics, statistics and programming to master state-of-the-art data science technology. Build a strong substantial foundation in policy and governance to understand and analyse policy challenges. Develop data-informed tools to tackle policy challenges in fields such as digital governance, health, democratic processes, human rights, international security, sustainability, climate change, and more. Check out the course catalogue.

Semester 1

Semester 2

-

Semester 3 + 4

Your Data Science instructors

  • Simon Munzert , Professor of Data Science and Public Policy | Director, Data Science Lab

    I'm Simon Munzert and I am Professor of Data Science and Public Policy and Director of the Data Science Lab at the Hertie School. I teach Introduction to Data Science in the first semester of the MDS. This course will get you up to speed with the modern data science workflow with R. We will cover topics like version control (Git) and project management, web data collection, database storage, data wrangling, debugging, automation, and data science ethics. I've written a textbook on web data collection with R. In my research, I have used large-scale survey and tracking data as well as experimental methods to learn how to make people use important health apps, or how political propaganda affects people's vote choice.

    See all courses by Simon Munzert

  • Prof. Lynn Kaack, PhD | Assistant Professor of Computer Science and Public Policy

    I’m Lynn Kaack and I am Assistant Professor of Computer Science and Public Policy at the Hertie School. My research focuses on methods from statistics and machine learning to inform climate mitigation policy across. I’m also a co-founder and chair of Climate Change AI, which works at the intersection of machine learning and climate action. I teach Artificial intelligence and climate change in the second year of the MDS, a course that will give you insights into cutting edge research using AI and machine learning to address climate change. I also teach Deep Learning in the second year of the MDS, where you can learn the main theoretical concepts of (deep) neural networks, and its applications in computer vision, natural language processing and other areas. 

    See all courses by Lynn Kaack

  • Prof. Joanna Bryson, PhD | Professor of Ethics and Technology

    I’m Joanna Bryson and I am Professor of Ethics and Technology at the Hertie School. Her research focuses on the impact of technology on human cooperation, and AI/ICT governance. I’ve recently written a paper on polarisation under rising inequality and economic decline.I teach Individual and collective intelligence: Insights from biology and technology in the second year of the MDS, a course that uses AI modelling to understand both individual and collective intelligence through hands-on experience of developing intelligent dynamics. I also teach Governance and politics of artificial intelligence in the second year of the MDS, where we explore social transformations and corresponding policy challenges relating to AI and DT, highlighting active areas of political debate and policy research. 

    See all courses by Joanna Bryson

  • Prof. Asya Magazinnik, PhD | Professor of Social Data Science

    I’m Asya Magazinnik and I am Professor of Social Data Science at the Hertie School. I study political institutions, with emphasis on electoral geography, federalism, local politics, and law enforcement and am also interested in political methodology. I teach Mathematics for data science in the first semester of the MDS, a course that will provide you with a broad understanding of linear algebra, probability theory, statistics and optimisation, all necessary for understanding the theoretical underpinnings of modern statistics and machine learning methods.

    See all courses by Asya Magazinnik

  • William Lowe, Senior Research Scientist

    I’m William Lowe, a Senior Research Scientist at the Hertie School. My research covers legislative politics, political economy, and public policy, with a focus on statistical text analysis and causal inference. At Hertie, I teach Causal Inference and Machine Learning, where we look at the intersection of theoretical tools with practical applications in the analysis of data within the context of public policy, and Data Science and Decision-Making, where we study classical decision theory juxtaposed with the literature on human and machine cognitive performance and bias.

    See all courses by William Lowe 

  • Drew Dimmery, Professor of Data Science for the Common Good

    I’m Drew Dimmery and I am Professor of Data Science for the Common Good at the Hertie School. My research focuses on the intersection of machine learning and causal inference. I work a lot on experimental design and I think hard about how experimentation can be better and more efficient. I’m also interested in better applying the tools of machine learning to observational causal inference. I teach two courses in the second semester of the MDS. In Data Structures & Algorithms, you will become capable software engineers able to design and analyze algorithms able to manage complex projects. In Machine Learning, you will learn how and why machine learning works. In both classes you will get hands-on experience and projects you can add to your portfolio.