Level: Intermediate to Advanced
Prerequisite: See below
Large language models (LLMs) have taken the world by storm, transforming how we interact with technology through natural language understanding and generation. These models are trained on vast quantities of text data, enabling them to perform a broad array of natural language processing (NLP) tasks, such as summarization, question answering, sentiment analysis, and entity recognition—but do you know how to apply these models to your business data safely, securely, ethically, and profitably?
In this hands-on course, you will be provided with the fundamentals to “talk with your data” by understanding and effectively implementing an LLM in an information-retrieval, question-answering use case. In particular, you will learn the importance of model selection, the art of prompt tuning, how to build a basic retrieval augmented generation (RAG) system, and ways to further improve your system—from fine-tuning the LLM with custom domain data to selecting the right information-retrieval algorithm.
After this workshop, you will be ready to apply these skills—in your own business, with your own data, and on your own platforms—to bring the benefits of LLMs to your business. While we will be working in a Google Colab notebook in class, the course is designed to benefit those working with LLMs in any environment.
You Will Learn
- What problems are LLMs designed to solve
- How to decide which LLM to use
- Several methods to interact with LLMs
- Metrics for evaluating and optimizing retrieval augmented generation (RAG)
- Ways in which classic NLP tasks can be applied to your business
- Techniques to safely and securely customize LLMs with your business data
Geared To
Anyone interested in the practical application of large language models, including:
- Data scientists interested in improving their use of LLMs
- Data analytics developers
- Data engineers
- Business and data analysts
- BI and analytics developers and managers
Pre-requisites
Workshop exercises will feature pre-written Python code, meant to be run in an online notebook.
The instructor will guide you on how to run the code, but comfort reading code will help.
Laptop Setup
Students must bring their laptops to class and have access to Google Drive.
Machine Requirements:
Windows PC or Mac with
- Google Chrome or another web browser
- Access to Google Drive
Setup:
Instructions will be emailed to registrants prior to the event to prepare your laptop before the conference.
There is no time allotted in class for laptop preparation.
* Enrollment is limited to 40 attendees.