1/17 [IN-PERSON] MLOps Community San Francisco Fall & Winter Workshops – Part III
In part III of our “Fall & Winter Workshops” series, the MLOps.community is organizing a half-day hands-on workshop on Jan 17th, 2024 where you’ll learn the basics of Retrieval Augmented Generation and learn best practices and design patterns for scaling …
In part III of our “Fall & Winter Workshops” series, the MLOps.community is organizing a half-day hands-on workshop on Jan 17th, 2024 where you’ll learn the basics of Retrieval Augmented Generation and learn best practices and design patterns for scaling to production.
You can find more information about the workshop here: https://lu.ma/cnukdjcd
THIS IS A PAID WORKSHOP. PLEASE PURCHASE THE COURSE HERE. ONCE YOU’VE PURCHASED THE COURSE, PLEASE REGISTER ON THE LUMA PAGE – https://lu.ma/cnukdjcd
Workshop Objectives In this workshop, you’ll gain the skills to develop a “Question and Answer” (Q&A) system using Large Language Models (LLMs). The course explores the implementation of a Q&A system over a proprietary Knowledge Base (KB) utilizing the Retrieval-Augmented Generation (RAG) technique. We’ll cover the steps involved in such a Q&A system – a data pipeline for preprocessing, ingesting data into a vector database, semantic search for the answer from the question, and compiling a response for the user using an LLM. You will be creating a proof-of-concept prototype using the provided data (or your own) and scalable patterns. In the second part, we cover advanced techniques including design patterns to take your prototype to production.
Target Audience This course is designed for Software Engineers, ML Engineers, and Data Engineers who want to learn the latest techniques for implementing a Q&A system over proprietary data. An ideal learner of this workshop would be able to build a PoC prototype in their organizations and be able to demonstrate to their internal stakeholders a foundational understanding of how they can build an LLM-powered application for both internal users and external customers.
This will be a half-day event with two sessions:
Instructor: Rahul Parundekar