Data Science & Econometrics
A fully online, buildable postgraduate programme that combines modern data science with the rigour of econometrics — co-developed with Lancaster University Management School. Stack modules from a 20-credit certificate of achievement up to a 180-credit MSc, taught by world-leading academics and practitioners.
About the programme.
About the programme
Our Data Science and Econometrics postgraduate programme is built to be flexible. It allows you to tailor your learning to your specific interests, studying online around your career. Best-in-field experts lead all specialist courses for unrivalled quality. Choose from five core modules and ten electives, and join us for as little as one module or build up to a full MSc.
How it works
Our buildable online Data Science and Econometrics programme is built with you in mind: learn with the best, around your career, and join a global network of analysts and econometricians wherever you are. All students receive a complimentary DataCamp subscription to consolidate their core data skills at their own pace.
Flexible learning
Learn live online with expert tutors and review recordings whenever you need, fitting your studies around your career. Start with just 60 credits and build up to a full MSc, accredited by Lancaster University — a world-class institution.
ECTS equivalence
We can provide a certificate of equivalence between credits obtained on our Post Graduate programmes and ECTS (European Credits), giving students the flexibility to transfer credits to other institutions — for example as part of a study-abroad programme or Erasmus exchange. 10 Lancaster University credits = 5 ECTS.
Entry requirements.
- ✓2:2 Bachelors degree or international equivalent
- ✓IELTS minimum 6.5 (or equivalent)
- ✓Apply from any country
- ✓Open to any academic background
Modules.
Select from 5 core and 10 elective modules to build your qualification — from a 20-credit Postgraduate Certificate of Achievement up to a 180-credit MSc. All modules are delivered fully online with live sessions, recordings, and tutor support.
Core Module
Elective Module
Dissertation
A combination of contact hours and private study.
Core Modules
Foundations of Econometrics
Foundations of Data Science
Microeconometrics and Panel Data Econometrics
Time Series Econometrics and Forecasting
Elective Modules
Automatic Model Selection Methods
Natural Language Processing
Causal Machine Learning
What you'll be able to do.
Build production-grade data pipelines
Engineer end-to-end workflows in Python and R — from ingestion and cleaning through modelling, deployment and monitoring.
Apply ML with econometric rigour
Combine modern machine-learning methods with the identification and inference standards of econometrics to make defensible, decision-grade analyses.
Work with high-dimensional & unstructured data
Handle large-scale, text and high-frequency data using state-of-the-art tools, while understanding their statistical foundations.
Communicate insight to decision-makers
Translate technical work into clear narratives, visualisations and recommendations that move organisations.
Professor of Econometrics at the University of Leicester, with research spanning factor models, structural breaks and high-dimensional inference.
Senior Lecturer at Bayes Business School (City, University of London), specialising in panel data econometrics and applied microeconomics.
Professor at Aix-Marseille School of Economics, with extensive work on inequality, causal inference and machine learning for econometrics.
Associate Professor at Vrije Universiteit Amsterdam, with research focused on Bayesian econometrics, simulation methods and forecasting.
Fees & funding.
Fees are payable per module, allowing you to pace your investment over up to 3 years. Indicative fees for the 2025/26 academic year. A complimentary DataCamp subscription is included with all qualifications.
Frequently asked.
Do I need to know Python or R already?+
Some prior coding exposure helps, but is not required. The complimentary DataCamp subscription lets you build the foundations before term begins, and the Foundations of Data Science module formalises core skills.
How does this differ from a pure data science MSc?+
We pair modern data science with econometric rigour — identification, inference, causal reasoning — so you don't just predict, you can explain and defend results in decision contexts.
How much time should I expect to commit per module?+
Core modules require around 200 hours of study in total (approx. 20 hours per week across a 10-week term), made up of 25 contact hours and 175 hours of private study. Elective modules require around 100 hours of study in total (approx. 10 hours per week), made up of 15 contact hours and 85 hours of private study.
Can I start with less than the full MSc?+
Yes — many students begin with the PG Certificate (60 credits) and decide later whether to continue to Diploma or MSc. Credits accumulate towards the higher award.
Is the qualification recognised internationally?+
Yes. The MSc is awarded by Lancaster University Management School — a triple-accredited business school — and ECTS equivalence can be issued on request for credit transfer.
Apply, or speak with our admissions team.
Applications are reviewed on a rolling basis. Join an upcoming Virtual Open Day to meet the faculty and current cohort before you apply.