Economics and Data Science at Warwick

This course will not be available for 2022 entry, but you may be interested in our other Master's degrees below.

P-L1I1

MSc

1 year full-time

19 September 2022

Economics

University of Warwick

This unique MSc course explores the intersection between Economics and Data Science.

This course will be open for applications from 1^st December 2021.

Our MSc in Economics and Data Science is for graduates in Economics who would like to pursue and specialise in Data Science and Machine Learning through a postgraduate-level degree. The course links economic theory and empirical economics with the fast developing field of Data Science. You will acquire knowledge and skills in the areas of macroeconomic and microeconomic theory, econometrics, big data, machine learning and coding. An 8,000-word dissertation provides an opportunity to explore your own interests across these fields of study.

You will be automatically enrolled on a pre-sessional Mathematics and Statistics programme to equip you with the relevant methodological skills you need to succeed.

By the end of the course you will have the knowledge of quantitative methods to analyse large amounts of data with the purpose of generating new findings and insights relevant to problems in Economics.

Skills from this degree

The course will give you a unique opportunity to acquire skills from two fields of economics and data science, including:

• Advanced training in economic analysis and techniques, with an emphasis on data science techniques and methods pertaining to applications in economics
• Acquisition, management and processing of large volumes of data
• Computer software and numeracy skills
• Analytical skills to think about national and international economics problems, policies and decision making

You will have a combination of lectures, and small group support and feedback classes. You will also learn through independent study, which will include reading journals and books, completing problem sets and assessments, revising for exams and undertaking research.

In the summer term and summer vacation your independent study time will increase as you complete your research dissertation. Your dissertation work will normally be individually supervised on a one-to-one basis and we have an effective personal tutor system providing individual support.

Core modules are in the range of 50-175 students; optional modules vary (10-75) and classes typically average around 15-20 students.

An average of 8 hours of lectures and 3 hours of classes per week.

For MSc students, assessment is through formal examinations, coursework and an individually supervised research dissertation.

Feedback is a vital part of the assessment process, as it helps you to reach your full potential by identifying the strengths and weaknesses of your work and the actions needed to develop your understanding and enhance your performance.

Feedback is provided in a variety of ways, including:

• Grades and comments on marked work
• Solutions to problem sets
• Verbal feedback from tutors and peers in classes
• Advice and Feedback hours with academic staff
• Personal tutor meetings

Reading lists

Most departments have reading lists available through Warwick Library. If you would like to view reading lists for the current cohort of students you can visit our Warwick Library web page.

Your timetable

Your personalised timetable will be complete when you are registered for all modules, compulsory and optional, and you have been allocated to your lectures, seminars and other small group classes. Your compulsory modules will be registered for you and you will be able to choose your optional modules when you join us.

2:i undergraduate degree (or equivalent) specialising mainly in economics. This means you should have achieved a good standard in undergraduate courses in microeconomics, macroeconomics and econometrics/ economic statistics at an intermediate level.

We also expect a good standard achieved in mathematics taken at undergraduate level.

• Band A
• IELTS overall score of 6.5, minimum component scores not below 6.0.

There are no additional entry requirements for this course.

Foundations of Data Science

In this module you will develop the skills in programming languages and their usefulness to acquire, process, clear and analyse large volumes of data efficiently (Big Data). It provides a “hands-on” experience with economic data while developing rigorous foundations of data science methods and techniques.

Machine Learning and Big Data in Economics

The module presents the analytical tools and the knowledge to study economic problems using modern data science methods, as well as the challenge posed by identification of causal parameters of interest. The aim is to present the econometric techniques along with the hands-on implementation in the computer language.

Economic Analysis (A or B)

Economic Analysis will develop your understanding of advanced microeconomic and macroeconomic analysis, with a more applied version (A) or a more technical/theoretically orientated version (B).

Quantitative Methods: Econometrics B

Econometrics B will consolidate your knowledge of the fundamental econometrics research skills and will also give you an opportunity to explore more advanced topics in this area.

Dissertation

The dissertation will allow you to develop the skills needed to carry out original research in economics and data science.

• The Economics of Financial Markets
• Monetary Economics
• Labour Economics
• Topics in Applied Microeconomics

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