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Data Science

Data Science for Economics

Get an introduction to basic but important concepts in Data Science and Machine Learning for Economics.

15h (2.5 days)

Online

English

Program date: February 16-18, 2026

Early bird deadline: January 19, 2026

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Data Science

Data Science for Economics

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Who is this Course for?

Data Science for Economics

Course Overview

Machine learning has become the new standard to carry out data analysis and prediction.In today’s data-rich environment, the ability to construct and understand statistical models based on big data is crucial for economists at policy institutions, think tanks and consulting firms.

This is a 15-hour online course that exposes you to state-of-the-art data science tools employed to tackle economic problems. The course is taught with a hands-on approach via Jupyter notebooks. The course is composed of three units that guide participants through the process of converting raw data into actionable insights:

Data handling and visualization
Supervised learning tools: ranging from linear models such as LASSO, Ride and Elastics Net to nonlinear models, such as Decision Trees, Random Forests and Boosting
Unsupervised learning learning tools: such as clustering algorithms and Principal Component Analysis

Classes will consist of rigorous training of the topics together with practical sessions to learn how to deploy these techniques to real data sets. Built around Jupyter Notebooks, this course offers participants the opportunity to improve their programming skills in both Python and R, the most widely used programming languages in data science.

Faculty

Discover what makes this Data Science course exceptional

1

Economics focus: Learn how data science and economics intersect at one of Europe's top institutions.

2

Comprehensive Data Science Training: Covers data handling, visualization, supervised and unsupervised learning tailored for economic applications.

3

Hands-on Practice with Jupyter Notebooks: Practical coding experience in Python and R, key for data science roles.

4

Instruction from Expert Faculty: Led by academics with robust experience in data science and economics.

5

Flexible Format: Available online to suit different schedules and timezones.

Who is this course for?

This course is designed for early-career professionals and graduate students with a background in economics or finance who want to build a solid foundation in data science and machine learning.

It is particularly well-suited for:

Young professionals with a Master’s degree in Economics or Finance who did not have the opportunity to study data science during their academic training.
PhD students looking to complement their research with essential data science and machine learning techniques.

The course takes a foundational and generalist approach, making it ideal for those who are new to the field and looking to acquire practical tools they can apply in economics, finance, or policy work.

Learning outcomes

This program has been designed for economists who want to enhance their data science skills and who in particular, want to:

Work with and extracted valuable insights from real data
Improve programming skills in two of the most used programming languages in data science
Gain skills to understand some of the key methods, as well as their limitations used by data scientists
Gain practical experience in applying these methods to large and heterogenous data
Learn how to work with large data sets

Key topics for Data Science for Economics

Take a look at the themes covered during this course.

Missing Data and Visualization

Linear Regression

Penalized Regression Models

Classification

Random Forests + Boosting

k-Nearest Neighbors and CART

Clustering and PCA

Intro to R

Supervised Learning in R

Unsupervised Learning in R

List of References

Books

The Elements of Statistical Learning. T. Hastie, R. Tibshirani, and J. Friedman. Springer Series in Statistics Springer New York Inc., New York, NY, USA, (2001).
An Introduction to Statistical Learning: with Applications in R, G. James, D. Witten, T. Hastie, R. Tibshirani, Springer Series in Statistics Springer New York Inc., New York, NY, USA, (2021).

Why should you attend BSE Executive Education courses?

All BSE Executive Education 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 and expand your knowledge and career prospects

Testimonials

KP

Konstantinos Pouliakas

As a researcher/professional of an EU agency, I was in need of a fast and succinct introduction to the principles of Machine Learning and Data Science. The course was very rigorous and covered targeted material and Python programs that may act as a springboard for more reading and learning on the topic…The course did a good job highlighting to potential Data Scientists that one needs rigorous theoretical understanding of the behavioral models, as opposed to simply programming some lines of code. I would highly recommend the course to professionals who, like myself, do not have the luxury of time due to family or other constraints to attend lengthy courses and lectures.

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LA

Liudmila Alekseeva

I enjoyed the BSE Data Science course. It met all of my expectations. I got an excellent overview of the theory and methods in Data Science with the use of Python. Intensive lectures, practical examples, and the individual projects we completed made the learning process very effective. I also appreciate that the professor not only gave us tools, but also explained the theory underlying them and the potential problems related to their implementation. After this course, I did not become a professional data scientist in Python at once, but the course gave me a fast start and a great motivation to continue developing in this field.

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Admissions

Considering taking part in BSE Data Science for Economics Executive Education course? Check you meet the requirements below.

Program date: February 16-18, 2026

Early bird deadline: January 19, 2026

Requirements

Candidates are assessed on an individual basis according to their professional or academic background

Requirements for Data Science in Economics

Prior familiarity with Python, R, Jupyter Notebooks, and matrix algebra is recommended for optimal participation in this course
Students must have their own laptop or desktop computer and a stable internet connection to participate and benefit from the course fully

Course Schedule

The times listed are Central European Time (CET). Compare with your time zone on time.is

Instructors, topics, and schedules are subject to change.

Day 1

Time

Session

9:15-9:30

Introduction

09:30 - 11:00

Missing Data and Visualization

Break

11:30 - 13:00

Linear Regression

Break

14:30 - 16:00

Penalized Regression Models

Break

16:30 - 18:00

Classification

Day 2

Time

Session

09:30 - 11:00

Random Forests + Boosting

Break

11:30 - 13:00

k-Nearest Neighbors and CART

Break

14:30 - 16:00

Clustering and PCA

Break

16:30 - 18:00

Intro to R

Day 3

Time

Session

09:30 - 11:00

Supervised Learning in R

Break

11:30 - 13:00

Unsupervised Learning in R

Certificate and Fees

Certificate

Participants who attend at least 80% of the course will receive a Certificate of Attendance free of charge. Participants will not be graded or assessed during the course.

Fees

A 10% discount applies when the confirmation payment is completed on or before the announced Early Bird deadline.

Other course discounts are available. Find out more information in our Fees and Discounts pdf.

Fees for courses in other Executive Education programs may vary.

Course

Data Science for Economics

Modality

Online

Total Hours

15h

Regular Fee

Reduced Fee*

* Reduced Fee applies for PhD or Master’s students, Alumni of BSE Master’s programs, and participants who are unemployed.

FAQ

Need more information? Check out our most frequently asked questions.

How much does each Executive Education 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 Executive Education courses. See more information about available discounts or request a personalized discount quote by email.