Economics with Data Science - BSc (Hons)

with a Year in Industry

Course structure

Duration: 4 years full-time

Modules 

The following modules are indicative of those offered on this programme. This listing is based on the current curriculum and may change year to year in response to new curriculum developments and innovation.   On most programmes, you study a combination of compulsory and optional modules. You may also be able to take ‘elective’ modules from other programmes so you can customise your programme and explore other subjects that interest you.

Stage 1

You take all compulsory modules and then either Mode A or Mode B from the list of optional modules depending on your existing level in Mathematics.

Compulsory modules currently include

EC304 - Principles of Economics (30 credits) 

EC309 - Statistics for Economics (15 credits)

EC314 - Data Analysis for Economists (15 credits)

CO320 – Introduction to Object-Orientated Programming (15 credits)

CO359 – Programming for Artificial Intelligence (Python programming) (15 credits) This is a new module - information available soon

Stage 2

Compulsory modules currently include

EC500 - Microeconomics (30 credits)

EC502 - Macroeconomics (30 credits)

EC580 - Introduction to Econometrics (15 credits)

EC581 - Introduction to Time-Series Econometrics (15 credits)

ECXXX - Modelling and Computation for Economists (15 credits) This is a new module - information available soon

MA5956 – Big Data and Other Analytical Techniques (15 credits)

Optional modules may include

EC305 - Mathematics for Economics Mode A (15 credits)

EC306 - Mathematics for Economics Mode B (15 credits)

You have the opportunity to select elective modules in this stage.

Stage 3

Compulsory modules currently include

EC542 - Econometrics I: An Introduction to Modern Econometrics using Stata (15 credits)

EC543 - Econometrics 2: Topics in Time Series (15 credits)

ECXXX – Machine Learning for Economists (15 credits) This is a new module - information available soon

Optional modules may include

EC541 - Economics Dissertation (30 credits)

EC565 - Extended Economics Essay (15 credits)

EC569 - Economic Growth (15 credits)

EC570 - Microeconomics of Development (15 credits)

EC538 - Economic Controversies (15 credits)

EC540 - Development Economics (15 credits)

EC534 - The Economics of Money and Banking (15 credits)

EC585 - Mathematical Economics (15 credits)

EC603 - Financial Crises (15 credits)

EC583 - Political Economy (15 credits)

EC582 - The Economics of Human Capital (15 credits)

EC544 - Economic Integration in the EU (15 credits)

EC545 - Economics of the Labour Market (15 credits)

EC546 - Games for Economics and Business (15 credits)

EC547 - Industrial Economics (15 credits)

EC548 - International Finance (15 credits)

EC549 - International Trade (15 credits)

EC550 - Monetary Economics (15 credits)

EC553 - Public Economics (15 credits)

EC562 - Financial Economics: Financial Markets and Instruments (15 credits)

EC563 - Financial Economics and Asset Pricing (15 credits)

EC531 - Policy Analysis (15 credits)

EC631 - Applied Environmental Economics (15 credits)

Teaching and assessment

Teaching

All modules are taught by a combination of lectures and small group sessions. These small groups can include workshops, seminars, computer terminal classes, problem-based classes, peer teaching, student presentations, debates, role play, experiments, group work, students own guided work, 1-2-1 supervision, VLE based learning activities and research projects.

In addition, all staff are accessible for student consultations for two hours a week outside direct teaching time.

On average, you have a total of 12-14 hours of lecture, seminar and other formal contact time per week.

The School of Economics is committed to making sure that you leave Kent with much more than just a degree in Economics. We put great emphasis on the development of transferable skills, including numeracy, analytical problem solving, data analysis, and written and oral communication, as well as subject-specific skills for further study at postgraduate level.

Some modules are assessed by continuous assessment of coursework throughout the year and an end-of-year exam in the final term. A number of modules at each stage are assessed solely through coursework.

Contact hours

For a student studying full time, each academic year of the programme will comprise 1200 learning hours which include both direct contact hours and private study hours.  The precise breakdown of hours will be subject dependent and will vary according to modules.  Please refer to the individual module details under Course Structure.

Methods of assessment will vary according to subject specialism and individual modules.  Please refer to the individual module details under Course Structure.

Programme aims

The programme aims to:

• provide a flexible and progressive curriculum that is suitable for students who have or have not studied Economics and Data Science before.
• provide a stimulating education in the principles of Economics and Data Science and their application, in which high quality teaching motivates students to achieve their full potential.
• stimulate students intellectually through the study of economics and to lead them to appreciate its application to a range of problems and its relevance in a variety of contexts.
• provide a firm foundation of knowledge about the workings of economic systems and to foster an understanding of alternative approaches to the analysis of economic phenomena.
• equip students with technical skills and knowledge appropriate for graduates in economics and data science. 
• provide students with the ability to abstract and to develop simplifying frameworks for studying the real world.
• develop in students the ability for rigorous reasoning and a logical approach to solving real world problems using economics and data science techniques.
• develop in students the ability to apply economic and data science knowledge, analytical tools and skills in a range of theoretical, applied and policy problems.
• develop students understanding of econometric theory and data science, and carry out applied econometric and data science investigations using appropriate software.
• provide a range of options to enable students to study selected areas of economics and data science in depth, the teaching of which is informed by the research and scholarship of academic staff.
• provide students with the knowledge and skill base from which they can proceed to further studies in economics and data science, related areas or in multidisciplinary areas that involve economics and data science.
• develop in all students, through the study of economics and data science, a range of skills that will be of value in employment and self-employment.
• develop skills and knowledge of relevant economics and data science software.

Learning outcomes

Knowledge and understanding

You gain a knowledge and understanding of:

• The main concepts, principles, theories, models and methods of modern economic, econometric, and data science analysis and their application in different areas of Economics.
• The history and development of economic ideas and the differing methods of analysis that have been and are used by economists.
• The analytical skills that allow students to formulate and consider a range of economic, econometric, and data science problems and issues.
• The econometric, mathematical, statistical and computing methods used in Economics, Econometrics and Data Science.
• Economic data, economic, econometrics and data science methods used to analyse such data.
• Economic analysis of policy.
• Critical Discussion of specific problems, issues and policies in a range of areas in Economics, Econometrics, and Data Science.
• Key concepts affecting decision-making.
• An economic topic chosen by the student and submitted as a supervised dissertation or extended essay in final year.
• Information technology skills relevant for Economics, Econometrics, and Data Science.
• Software, including programming languages and tools, packages, practice, structuring of economic data and information.
• The role of logical mathematic argument and deductive reasoning used in applying economic modelling, econometrics, and data science techniques.

Intellectual skills

You gain the following intellectual skills:

• Ability to abstract the essential features of a complex system.
• Ability to think about what are the important variables and fixed parameters in solving a problem.
• Ability to analysis complex issues using deductive and inductive reasoning.
• Ability to organise and use information to analyse complex issues, test hypotheses, and apply core concepts and principles relevant to computing, statistics and econometrics.
• Ability to review critically alternative explanations and analyses of a problem.
• Ability to manage a supervised final year dissertation or extended essay on an economic topic chosen by the student.
• Ability to demonstrate skills in calculation and manipulation of mathematical and statistical material written within the programme and ability to solve problems formulated within it.
• Ability in computer skills and usage of relevant programming languages relevant.

Subject-specific skills

You gain the following subject-specific skills:

• Analytical skills in economics, econometrics, machine learning, and economic modelling.
• Ability to apply economic principles and analysis to a range of issues, problems and policies.
• Ability to abstract the essential features of an economic issue, problem or system.
• Knowledge of the principal sources of Economic data and information and ability to use and present this information.
• Be able to carry out economic, econometric, and machine learning analysis of economic data.
• Knowledge and ability to make and provide advice on how to make economic decisions.
• Ability to synthesise and compare critically different economic analyses of an economic issue.
• Ability to research the literature on an economic issue.
• Ability to apply economic skills to investigate a supervised final year project on an economic topic chosen by the student.
• Ability to use key aspects of econometrics, machine learning and economic modelling in analysing real world problems using small and large data set.
• Knowledge and ability to demonstrate understanding of fundamental concepts and algorithmic thinking including recursive, distributed and parallel possibilities, and their role in machine learning algorithms and economic modelling.
• Ability to use computational facilities and demonstrate skills in codification and storage of data as well as in pre-processing raw data for analysis.

Transferable skills

You gain the following transferable skills:

• Effective communication of analysis and ideas both orally, aurally and in written form
• Ability to assemble, analyse, use and present data.
• Understanding and ability to use economic, econometric, mathematical and quantitative methods to analyse issues and problems.
• Ability to analyse and make decisions, using economic concepts, e.g. opportunity cost and strategic behaviour.
• Development of Information Technology skills through using statistical, econometric, and programming packages.
• Independence in initiating and executing work.
• Ability to think critically about proposed analyses and solutions to a problem or issue.
• Become responsible for managing own learning and academic performance.
• Manage a supervised final year dissertation or extended essay on an economic topic chosen by the student.
• Computational skills including coding and programme development.

Careers

Graduate destinations

Our Economics graduates have developed careers in accountancy, banking and finance, journalism, management consultancy and business. Recent graduates have gone on to work for:

• Deloitte
• Government Economic Service
• HMRC
• Citibank
• KPMG
• PwC
• Bank of America
• Schroders
• Goldman Sachs
• Barclays.

Help finding a job

The School of Economics supports and advises you in deciding what to do after your Economics degree. We offer:

• one-to-one advice from a member of our employability team
• employability workshops
• talks from alumni and outside employers.

The University also has a friendly Careers and Employability Service which can give you advice on how to:

• apply for jobs
• write a good CV
• perform well in interviews.

Work experience

Internships, either for a week or two or for the whole summer, can be a valuable addition to your studies. We provide guidance and assistance on where to look and how to apply.

Career-enhancing skills

Alongside a thorough understanding of economic issues, you develop key transferable skills that will appeal to employers. These include the ability to:

• think critically
• communicate your ideas and opinions succinctly
• work independently
• use your initiative and be proactive
• work as part of a team and independently
• manage your time and plan effectively
• problem solve.

You can also gain extra skills by signing up for one of our Kent Extra activities, such as learning a language or volunteering.