Introduction to Current Large Language Models and Platforms
First-year course in the Master program IREF
Bordeaux School of Economics
University of Bordeaux
Large Language Models (LLMs) are a transformative technology in artificial intelligence (AI) that enable machines to
process,
understand,
translate, and
generate human language.
They are
based on deep learning techniques and
are trained on massive datasets.
They revolutionized the field of natural language processing (NLP) and artificial "intelligence" (AI).
Examples: ChatGPT, Claude, Gemini, Llama, Mistral (Cocorico!), and many others...
In economics, LLMs have applications that include analyzing financial reports, forecasting economic trends, and simulating policy impacts.
This course starts with the principles and components of LLMs and then introduces the leading platforms currently available and the services they offer to students and future professionals.
Outline of the course
- Chapter 1: An introduction to the principles of LLMs - Slides - Audio presentation by NotebookLM.
- Chapter 2: Presentation of the main LLMs - Slides
- Principles of prompts and prompt engineering
- Applications in learning, research, and business
- Chapter 5: Learning with LLMs - Slides
- Chapter 6: AI Agents: Transforming Economics and Beyond - Slides - Report on Agentification written by ARI You.com
- Chapter 7: Applications in Economics and Finance - Slides
First control on machine: Thursday, Feb 20, 2025
Second control on machine: Thursday, April 3, 2025
Please come with your laptops - Instructions - Documents
References:
- Bowen, J. A. and Watson, C. E. (2024) Teaching with AI: A Practical Guide to a New Era of Human Learning. John Hopkins University Press.
- Mollick, Ethan R. and Mollick, Lilach, Assigning AI: Seven Approaches for Students, with Prompts (September 23, 2023). The Wharton School Research Paper, Available at SSRN: https://ssrn.com/abstract=4475995 or http://dx.doi.org/10.2139/ssrn.4475995
Interesting reads on the web
- Large language models: a primer for economists, by Byeungchun Kwon, Taejin Park, Fernando Perez-Cruz and Phurichai Rungcharoenkitkul, BIS Quarterly Review, 10 December 2024.
- Claude's prompt library