Programme Structure

The program is organized around three pillars:

• Model Building Skills
• Data Analysis and Statistics Skills
• Practice of useful analytics for government and society

The core courses provide training in fundamental aspects of applied data science, social research, and modeling of social and political phenomena. These courses create the necessary basis for the topics covered in the elective courses.

Most important skill set to be developed is in model thinking and model building. It brings together the predictive modeling and causal thinking with the knowledge of a wide range of analytical methods, forging in students the ability to apply methods meaningfully and accurately. We will introduce you to model thinking step by step, starting with the general courses devoted the methods of social research, and proceeding to the empirical training of the acquired skills.

The range of elective courses gives you an opportunity to tailor the program to your interests. In the first year, you will choose between the courses designed to develop the skills of handling and analyzing the data of different types: social network analysis, text analysis and mining, programming in Python. In the second year, courses mostly will involve the application of data analysis skills to real-life tasks in social science, industry, and policy-making.

In some courses, students will work in subgroups according to their level of the acquired skills, in other courses groups will be formed around thematic projects, uniting students with different skills, with the idea of diverse project teams and peer-to-peer education. The program is focused on project-based learning, and some courses will have collective capstone projects, where you will apply the skills of data analysis and model thinking to original data with original research questions.