watsonx.ai: Large Language Model Operations (W7S186G-SPVC)

Overview

This hands-on course introduces learners to the principles and practices of Large Language Model Operations (LLMOps), focusing on the development, deployment, and governance of AI models using IBM's watsonx.ai platform. Participants will explore the IBM LLM workflow, utilize Prompt Lab for model prompting, and develop Retrieval-Augmented Generation (RAG) models with AutoAI. The course emphasizes practical experience through UI-based labs, enabling learners to build, deploy, and monitor AI models effectively.

Audience

AI specialists, data scientists, developers, or anyone interested  interested in learning LLMOps using watsonx.ai

Prerequisites

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Objective

  • Understand the fundamentals of Large Language Model Operations (LLMOps) and their role in AI model lifecycle management
  • Navigate and apply the IBM LLM workflow within the watsonx.ai platform
  • Develop RAG models using AutoAI, integrating in-memory or external vector databases
  • Leverage Prompt Lab to create and refine prompts for foundational models, focusing on tasks like summarization
  • Deploy AI models and implement governance strategies using IBM's AI Governance tools to ensure compliance and transparency
Pokaz szczególy

Course Outline

  • Introduction
  • Module 1: Large Language Model Operations
  • Module 2: LLMOps on watsonx
  • Module 3: Prompting a foundational model with Prompt Lab
  • Module 4: Automating Retrieval Augmented Generation
  • Module 5: Deploying the generative AI assets
  • Module 6: Governing the generative AI assets
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