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The MSc in Data Science and Public Policy at UCL will prepare you to understand, evaluate and implement new statistical methods to answer key questions in public policy. This new one-year programme, provides highly structured training in applied data science as well as a thorough knowledge of political science or economics (depending on which “route” you select).
In the data science modules of the programme, you will undertake diverse, practical and rigorous quantitative methods training, which will equip you to understand, develop, and apply cutting-edge statistical methods.
Economics or Political Science Route
You will also specialise in either a political science or economics “route”, depending on your interests and previous qualifications. The modules you take on your chosen route will mean that you will also develop a deep understanding of social science theories from economics and political science that explain the modern policy process.
Taken together, the combination of data science and substantive public policy training on the MSc mean that you will leave the programme having gained a strong understanding of the statistical foundations of modern data analysis, and the ability to apply a wide variety of quantitative methods to answer important policy questions.
Summer Before Enrolling
Maths Camp
In the summer before you start the MSc Data Science and Public Policy programme, you'll complete an online, self-paced course in Mathematics and Statistics ("Maths Camp"). For most offer-holders, the material is a review of the undergraduate mathematics and statistics that you have studied.
You'll have online Maths Camp review sessions during the week before Induction Week. All students will sit an online exam on the course material during Induction Week.
Although the Maths Camp exam mark does not count toward the Data Science and Public Policy degree in a formal sense, the exam provides feedback on your readiness for the technical demands of the Data Science and Public Policy MSc programme.
Term 1
Core Modules
In the first term, you will take three core modules that will provide you with the foundational data science and programming skills that are required for modern quantitative analysis.
This two-term module is at the core of this degree and introduces you to core statistical methods in data science, as well as many recent advances in machine learning. You will learn the mathematical foundations of these approaches and gain experience in applying the methods to real-world public policy datasets.
This compulsory module will provide skills in data management, visualization, and programming in the R language.
You’ll also understand the role of data science in the contemporary policymaking process on the Data, Evidence and Public Policy core module. This module will also address some of the ethical and legal challenges that have arisen in response to the growth of data science approaches in this field
During Term One you’ll also take compulsory modules in substantive fields of economics or political science, depending on which route you select.
This structure means that you will be able to focus on the substantive areas of public policy that interest you the most, and the core data science modules in Term One will provide you with the tools necessary to answer interesting and important research questions in your chosen field.
Economics Route
If you are on the economics route, you will take one of the following existing modules taught in the Department of Economics:
Political Science Route
If you are on the political science route, you will take a module on The Politics of Public Policy (PUBL0098), which will introduce you to important theoretical approaches that political scientists use to study processes of public policy formation and delivery.
Term 2
In the second term, you will continue with more advanced data science training, but also have more freedom to concentrate on the subfields of public policy and data science methods that interest you the most.
You will continue to take Statistical Learning for Public Policy, which in term two focusses on a wide range of cutting-edge machine learning methods. You will also choose another data science module.
Exact module options change each year, but might include:
- Quantitative Text Analysis - PUBL0099
- Causal Inference - PUBL0050
- Machine Learning in Economics - ECON0126
- Data Science Theory - ECON0125
In addition, you will also take further modules from within the substantive route of the programme on which you are enrolled (Political Science or Economics).
Economics Route
- Compulsory module: Machine Learning in Economics - ECON0126
You'll also choose one module from a choice of economics options. Exact module options change each year and will also depend on your module choices in Term 1 but some examples include:
- Macroeconomic Policy - ECON0073
- Behavioural Economics - ECON0102
- Health Economics - ECON0069
- Environmental Economics - ECON0077
- Public Microeconomics - ECON0061
- Economics of Development - ECON0105
- Time-Series Econometrics - ECON0058
Political Science Route
You'll choose two modules from a choice of public policy options. Exact module options change each year but some examples include:
- International Political Economy - PUBL0004
- Public Management - PUBL0008
- Terrorism - PUBL0015
- Making Policy Work - PUBL0017
- Policy Implementation - PUBL0028
- Law and Regulation - PUBL0031
- International Trade Policy - PUBL0060
- The Political Economy of Development - PUBL0074
- Migration, Politics and Policy - PUBL0093
Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment and module content and availability is subject to change.
Term 3
Dissertation
In the third term, you will focus on an independent research project which culminates in a 10,000 word dissertation, which will make creative use of the data science skills developed throughout the year to answer a substantive question of public policy that is relevant to your chosen field.
Note: Each 15-credit module is equivalent to 150 hours of study and a 30 credit module equivalent to 300 hours of study. Contact hours may vary depending on module choices, but full-time students will approximately have 8-10 hours of contact hours each week during term time.
