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Retrieval Augmented Generation (RAG) Introduction (RXM403)
Duration
1
Course
LNX-RXM403
Available Formats
Classroom Training, Online Training
Course Description
Overview
Learn about Large Language Models (LLM) and how RAGs combine generative and retrieval-based AI models to extend the already powerful capabilities of LLMs. Get the knowledge you need about how a RAG works and how it’s assembled from component parts.Key Benefits for You:
- Live, instructor-led hands-on labs
- Develop unique skills
- Use RAG to refine LLM outputs
With our hands-on labs, you will develop a RAG using existing LLM and AI tools and apply RAG techniques to designs to solve problems.
Objectives
How will this course benefit the student?
- Harness the Power of LLMs
- Gain Competitive Skills with RAGs
- Advance Your Career
Audience
AI/ML Developers. Software & Data Engineers, IT and QA Staff. Technical Managers and more!
Prerequisites
-
Participants should have basic programming skills (preferably in Python), a foundational understanding of
mathematics and statistics, some experience with data analysis.
Topics
Module 1: LLM Overview
- Lab: Building an LLM Endpoint
- Lab: Data Collection and Chunking
- Lab: Creating Embeddings and Ingesting Data
- Labs: Building the Final RAG Solution
Self-Paced Training Info
Learn at your own pace with anytime, anywhere training
- Same in-demand topics as instructor-led public and private classes.
- Standalone learning or supplemental reinforcement.
- e-Learning content varies by course and technology.
- View the Self-Paced version of this outline and what is included in the SPVC course.
- Learn more about e-Learning
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