Core Modules

• Microeconomics for Data Science

  The goal of this module is to introduce students to a mixture of undergraduate and graduate topics of microeconomics relevant for data scientists. A key part of the module is a set of empirical projects allowing to practice routine tasks in data science.

• Econometric Methods

  This module aims to provide an overview of basic econometric methods. The focus is on understanding and interpreting the econometric assumptions and techniques in light of actual empirical applications.

• Fundamentals of Data Science

  The aim of this module is to build a strong foundation of the fundamentals of data science with plenty of hands-on experience. The content will cover data types and storage, retrieval, pre-processing, manipulation, and visualisation. Further it will look at how to design web applications and introduce students to big data engineering: SQL, AWS, etc.

• Machine Learning in Economics

  This module considers the majority of classical machine learning algorithms and covers their usage in practice, implementation, and theoretical properties.

• Causal Inference and Machine Learning

  This module considers key issues around the design of a number of learning algorithms to take account of the fundamental problem that there is no ground truth for causal inference. The course will also cover non-technical considerations relevant for causality and decision-making. Students should be able to answer industry questions such as “How would you estimate an effect of X on Y?” in a certain real situation, which involves creative thinking, understanding data, domain knowledge, etc.

• Research Computing

  In this course we will introduce students to the basic concepts and best practices required to produce high quality, maintainable code for research. This will cover not only developing code for individual research but also developing code as part of a collaboration and for public release. The majority of the course will be in python, but the general principles taught are applicable to any programming task in any language.​​

• Seminar Series and Case Studies

  The seminar series will familiarize students with the work of industry and academic experts. The accompanying group presentations will allow students to excel in teamwork and foster their presentation skills if they wish.