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Summer School

Data Science in Finance

The Data Science in Finance Summer School connects modern machine learning and artificial intelligence with practical financial applications. Designed for students, researchers, and professionals with a quantitative background, it combines rigorous foundations with hands-on experience in financial analysis and risk management.

Two complementary courses explore distinct approaches. Machine Learning for Financial Risk Management covers statistical learning, model evaluation, and methods for predicting financial outcomes and measuring uncertainty, with applications to credit risk, value-at-risk, and financial stress. Large Language Models in Finance explores how LLMs and AI agents can analyse financial documents and support business valuation, credit assessment, and portfolio management.

Through lectures, practical coding sessions, and financial case studies, participants learn to build useful applications and assess their reliability. Throughout the program, the emphasis is on sound evaluation, an understanding of model limitations, and the responsible use of these tools in financial practice.

Face-to-face

English

Next edition: July 2027

Early Bird deadline: April 15, 2027

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Discover all of our Data Science in Finance Summer School Courses!

Summer School

Data Science

Machine Learning for Financial Risk Management

Next edition: July 5-9, 2027

Instructor: André B.M. Souza

Summer School

Data Science

Large Language Models in Finance

Next edition: July 5-9, 2027

Instructor: Juan Imbet

Who attends BSE Data Science in Finance courses?

Those courses are specifically aimed at:

Students, researchers, and professionals seeking to deepen their understanding of data science techniques and their use in empirical finance

Program Directors

UPF and BSE

Lorenzo Cappello

UPF and BSE

PhD in Statistics, Bocconi University

Lorenzo Cappello

UPF and BSE

PhD in Statistics, Bocconi University

Lorenzo Cappello is an assistant professor in the Statistics group at Universitat Pompeu Fabra and affiliated professor at the Barcelona School of Economics. He previously was a postdoctoral scholar in the Department of Statistics at Stanford University, mentored by Prof. Julia A. Palacios. He earned his PhD in Statistics in 2018 from the Department of Decision Sciences at the Bocconi University, under the supervision of Stephen G. Walker and Sonia Petrone.

Teaching

Data Science Methodology Program
Statistical Machine Learning for Large and Unstructured Data

Research interests

Statistics

Explore biography

UPF and BSE

Filippo Ippolito

UPF and BSE

PhD, Saïd Business School (Oxford University)

Filippo Ippolito

UPF and BSE

PhD, Saïd Business School (Oxford University)

Filippo Ippolito is Associate Professor of Financial Management at Universitat Pompeu Fabra and BSE Affiliated Professor. He is the Director of the Master in Financial Economics at the BSE. Professor Ippolito holds a PhD in finance from Said Business School, Oxford, and an MPhil from the University of Oxford. In the past he has worked in the financial and consulting sectors. His research focuses on corporate debt, capital structure, corporate liquidity management and private equity. Professor Ippolito has published in the Journal of Finance, Journal of Financial Economics, Journal of Financial Intermediation, Journal of Monetary Economics and Journal of Corporate Finance.

Teaching

Financial Economics Program

Research interests

Corporate Finance

Explore biography

Why study at BSE?

Top 5 Economic Research Department

Study with professors who produce top-ranking research in their fields.

World-renowned Faculty

Receive the highest quality training, with courses developed with students in mind.

Barcelona

One of Europe’s most popular cities, combine learning with culture for the best learning experience.

Why should you attend BSE Summer School?

All BSE Summer courses are taught to the same high standard as our Master’s programs.

1

Network with like-minded peers from around the world

2

Short courses allow you to learn without a big time commitment

3

Try something new, expand your knowledge and career prospects, and advance your thesis

Admissions Process

What do you need to be able to apply? See the admissions requirements below.

Next edition: July, 2027

Early Bird deadline: April 15, 2027

Requirements

Successful candidates will usually demonstrate one or more of the following in an application to our Summer School programs:

A strong background in Economics or a field closely related to the course topic (Statistics, Law, etc.)
Postgraduate degree or current Master’s/PhD studies related to the course topic
Relevant professional experience

Requirements for Data Science for Finance Summer School

Some knowledge of R and Python is advised to take full advantage of the school

Mix and match your summer courses!

Remember that you can combine Data Science in Finance Summer School courses with courses in any of the other BSE Summer School programs (schedule permitting). Maximise your learning this summer and take advantage of our multiple-course discount.

FAQ

Do you still have questions? Check out our FAQ section below! Or contact our Admissions Team.

Can I see the full Summer School calendar?

You can view the full Summer School calendar here.

How much does each Summer School course cost?

Fees for each course may vary. Please consult each course page for accurate information.

Are there any discounts available?

Yes, BSE offers a variety of discounts on its Summer courses. See more information about available discounts or request a personalized discount quote by email.

Can I take more than one course?

Yes! you can combine banking Summer School courses with other BSE Summer School programs (schedule permitting). See the full schedule here.

Credit Transfers (ECTS)

To be eligible for credit transfers, students must complete a final project.

Students will deliver a short final project one week after the summer school finishes. It will consist in solving a final problem that will include the practical and empirical issues worked on in class.

Consult the Summer School Admissions page for more information about this option.