watsonx.ai: Large Language Model Operations
- Course Code W7L186G
- Duration 1 day
Course Delivery
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Course Delivery
This course is available in the following formats:
-
Public Classroom
Traditional Classroom Learning
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Virtual Learning
Learning that is virtual
Request this course in a different delivery format.
Course Overview
TopThis 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. T
he course emphasizes practical experience through UI-based labs, enabling learners to build, deploy, and monitor AI models effectively.
Course Schedule
TopTarget Audience
TopAI specialists, data scientists, developers, or anyone interested interested in learning LLMOps using watsonx.ai
Course Objectives
TopAfter this course participants should be able to:
- 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
Course Content
Top- 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
Course Prerequisites
TopFurther Information
Top- Official course book provided to participants.