LLMs, RAG, and Fine-Tuning: A Hands-On Guided Tour
This workshop is for data scientists and machine learning engineers who want to learn how to work with LLMs in production systems. Developers will learn how researchers and engineers work with LLMs, emphasizing connections between concepts like fine-tuning and RAG to the mathematical insights, cloud infrastructure, and APIs used to build and improve these systems. Business-minded executives will deepen their sense of what is possible with LLMs, a relative measure of how much it might cost, what new risks generative AI introduces, and how recent generative AI advances fit into the history of enterprise computing. The primary value of this workshop will be to help teams set reasonable goals and understand how to support your team’s next LLM projects successfully.
What This Workshop Covers
Using the Metaflow sandbox, a browser-based VSCode in which we’ve provisioned the full stack of ML infrastructure for you, you’ll learn about
Various proprietary off-the-shelf models and APIs.
Open-source LLMs.
Prompt engineering.
The Retrieval Augment Generation (RAG) pattern.
Vector databases.
Building a constantly updating production RAG system with Metaflow.
Warnings!
This is an engineering-focused course, not an ML course. You will get to build actual functional systems, not just models. Having said that, we intend it to be as accessible as possible for non-engineers: we want to make sure that all (data) scientists can build real-world DS, ML, and AI software systems;
We provide fully managed infrastructure for the course, including Kubernetes, schedulers, event triggering, and more - all this in your browser.
Notes:
This workshop is online and for EU/APAC timezone. Please sign up to our June Workshop for Americas/APAC timezone;
Some details of the workshop may change but we'll send round more detailed information in the weeks leading up to the workshop.