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Summer School

Data Science

The BSE Data Science Summer School explores cutting-edge machine learning tools. “Data Science for Economics” provides a broad overview of key data analysis methods, with an emphasis on applications in Economics.

Advanced courses include “From Prediction to Action: Machine Learning and Optimisation for Better Decisions”, “From Text to Data: Language Models You Can Trust” and “Statistical Machine Learning for Large Data”.

The teaching style of the courses is hands-on. Special attention will be devoted to applying the methodologies introduced in class on empirical data using Jupyter notebooks coded in either Python or R.

The courses of the BSE Summer School in Data Science give participants the tools to apply modern machine learning techniques, from data exploration to building predictive models and extracting insights.

Face-to-face

English

Next edition: June-July 2027

Early Bird deadline: April 15, 2027

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Discover all of our Data Science Summer School Courses!

Summer School

Data Science

Data Science for Economics

Next edition: June 28 - July 2, 2027

Instructor: Jordi Llorens

Summer School

Data Science in Finance

Large Language Models in Finance

Next edition: July 5-9, 2027

Instructor: Juan Imbet

Summer School

Data Science

From Prediction to Action: Machine Learning and Optimisation for Better Decisions

Next edition: July 5-9, 2027

Instructor: Alberto Santini

Summer School

Data Science

From Text to Data: Language Models You Can Trust

Next edition: July 5-9, 2027

Instructor: Arnault Gombert

Summer School

Data Science in Finance

Machine Learning for Financial Risk Management

Next edition: July 5-9, 2027

Instructor: André B.M. Souza

Summer School

Data Science

Statistical Machine Learning for Large and Unstructured Data

Next edition: July 12-16, 2027

Director and Instructor: Lorenzo Cappello

Who attends BSE Data Science courses?

This course is specifically aimed at:

Graduate students looking to build a strong foundation in machine learning
Professionals and consultants who want to transition into data science and machine learning roles and are interested in expanding their machine learning skills for predictive modeling and data-driven decision-making
Researchers & academics seeking to incorporate machine learning methods into their research projects

Program Director

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

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: June-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 in Economics course

Participants should be familiar with the fundamentals of linear algebra and programming with Python and R

Requirements for the other Data Science courses

Participants must be familiar with statistical machine learning and Python and R

Mix and match your summer courses!

Remember that you can combine Data Science 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.