Master's Degree in Economics and Finance

Master's Degree in Specialized Economic Analysis

Master's Degree in Data Science

Admissions

Career Services

Alumni Community

Economics Program

Financial Economics Program

PhD Economics Track Program

Go to Master's degrees

Close

Data Science in Finance

Large Language Models for Finance

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

20h (10 days)

€1,375-€795

Online

English

Next edition: February 22 - March 5, 2027

Early bird deadline: January 20, 2027

Learn more

Data Science in Finance

Large Language Models for Finance

Complete your details and we'll keep you informed about the next edition.

First Name*

Last Name*

Email Address*

Message

I give my consent to be contacted by BSE with information about related academic offers in the future.

Who is this Course for?

Data Science in Finance

Large Language Models in Finance

Course overview

Large Language Models (LLMs) are rapidly transforming the financial sector, creating new opportunities to automate analysis, improve decision-making, and generate insights from large volumes of financial data. As artificial intelligence becomes increasingly integrated into financial services, understanding how to apply these technologies is becoming an essential skill for finance professionals and researchers.

The course “Large Language Models in Finance” provides a hands-on introduction to the use of Large Language Models (LLMs) and Artificial Intelligence in financial applications. Participants will explore how LLMs work, including the fundamentals of Natural Language Processing (NLP), Transformer architectures, model training, and fine-tuning techniques.

The program combines theoretical foundations with practical implementation, allowing students to develop AI-powered financial applications from scratch using modern tools such as Hugging Face Transformers and REST APIs.

Through real-world case studies and coding sessions, participants will learn how LLMs can be applied to:

Business valuation

Cash flow forecasting

Credit risk assessment

Sentiment analysis

Probability of default estimation

Financial decision-making under uncertainty

The course also introduces advanced topics such as AI Agents, AI Crews, and Small Language Models, highlighting the future of AI-driven finance.

Faculty

Discover what makes this Data Science in Finance course exceptional

1

Finance-focused applications: Explore how Large Language Models are transforming financial analysis, forecasting, valuation, and risk assessment.

2

Practical AI tools: Gain hands-on experience with Hugging Face Transformers and deploying LLMs using REST APIs.

3

Real-world case studies: Apply LLMs to business valuation, credit risk assessment, and other finance use cases.

4

From foundations to advanced techniques: Learn core concepts alongside topics such as transfer learning, fine-tuning, and financial forecasting.

5

Learn from an expert: Benefit from the expertise of Prof. Juan F. Imbet, whose research bridges finance and artificial intelligence.

6

Hands-on learning: Develop practical skills through coding exercises and applied financial AI projects.

Who is this course for?

This course would be of particular interest to:

Finance professionals, data scientists, researchers, and PhD students seeking hands-on training in Large Language Models (LLMs) and their real-world applications in valuation, credit risk, forecasting, and AI-driven financial analysis

Learning outcomes

By the end of the course, participants will have:

Understood the fundamental concepts of Natural Language Processing (NLP) and explored how it is applied to various financial tasks
Gained foundational knowledge of large language models, including the Transformer architecture and practical tools like Hugging Face Transformers, to apply them in finance
Developed an understanding of data preparation, training, and fine-tuning techniques for large language models
Explored transfer learning and how pre-trained language models can be customized for specific financial tasks like forecasting and sentiment analysis
Learned how to leverage large language models for business valuation tasks, including forecasting cash flows and conducting scenario analysis
Gained hands-on experience with entity recognition from financial statements and how LLMs can be used for comparable selection in valuations
Mastered the techniques of fine-tuning large language models for credit risk assessment and estimating probabilities of default
Learned how to deploy LLM applications using a REST API to handle real-world financial decision-making under uncertainty
Developed their own AI Crew as a set of specialized agents to solve a real-world finance problem

Key topics for Large Language Models in Finance

Take a look at the themes covered during this course.

Introduction to Large Language Models

Overview of Natural Language Processing (NLP) and its applications in Finance.
Introduction to Large Language Models.
Understanding the Transformer Architecture.
Setting up the Python environment for the course.
Introduction to the Hugging Face Transformers Library

Advanced Topics on Large Language Models

Preparing and preprocessing data
Training LLMs
Transfer learning and fine-tuning concepts.
Pre-trained language models for Finance tasks.

Practical Session I: LLMs for Business Valuation

Forecasting cashflows using LLMs
Scenario Analysis
Comparable selection using LLMs
Entity Recognition from Financial Statements

Practical Session II: Credit Risk

Fine-tuning a model to assess credit risk
Using LLMs to approach complex household decisions under uncertainty
Using LLMs to estimate probabilities of default
Deployment of an application using a REST API

Other Applications in Finance and Future Trends

Creating your own AI Crew

List of References

Books / Articles

The course slides and code will be distributed with the course pack. Some additional references include:

‘Natural Language Processing with Transformers, Revised Edition’ by Lewis Tunstall, Leandro von Werra, Thomas Wolf, Released: May 2022, Publisher: O’Reilly Media, ISBN: 9781098136796
The Predictive Edge, Alejandro Lopez-Lira, Released: 2024 Publisher: Wiley ISBN: 9781394242719
Quick Start Guide to Large Language Models, Sinan Ozdemir, Released: 2024, Publisher: Pearson Addison-Wesley, ISBN: 9780138199197
Text as Data, Justin Grimmer, Margaret E. Roberts, and Brandon M. Stewart. Released: 2022, Publisher: Princeton University Press, ISBN: 9780691207551

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

Admissions

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

Next edition: February 22 - March 5, 2027

Early bird deadline: January 20, 2027

Requirements

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

Requirements for Large Language Models in Finance

A basic understanding of Python programming
A basic background in finance
Familiarity with data analysis concepts is beneficial but not mandatory

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.

Schedule

Time

1
Mon

2
Tue

3
Wed

4
Thu

5
Fri

18:00-20:00

Lecture /Practical

Sessions take place Mon-Fri over 10 days.

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

Large Language Models in Finance

Modality

Online

Total Hours

20h

ECTS

0

Regular Fee

1,375€

Reduced Fee*

795€

* 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.

See the full Executive Education calendar

The full calendar is available to view here.

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.