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watsonx.ai: Large Language Model Operations
Course Description
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.
Objectives
- 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
Audience
AI specialists, data scientists, developers, or anyone interested interested in learning LLMOps using watsonx.ai
Topics
- 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
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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Self-Paced Training Terms & Conditions
This is a Self-Paced virtual class; it is intended for students who do not need the support of a classroom instructor.
If you feel you would better benefit from having access to a Subject Matter Expert, please enroll in the Instructor-Led version instead. Minimal technical support is provided to address issues with accessing the platform or problems within the lab environment.
Before you enroll, review the system requirements to ensure that your system meets the minimum requirements for this course. AFTER YOU ARE ENROLLED IN THIS COURSE, YOU WILL NOT BE ABLE TO CANCEL YOUR ENROLLMENT. You are billed for the course when you submit the enrollment form. Self-Paced Virtual Classes are non-refundable. Once you purchase a Self-Paced Virtual Class, you will be charged the full price.
After you receive payment confirmation from LearnQuest, you will be sent further access instructions and time limits for your course from IBM.
IMPORTANT!!! If your course provides access to a hands-on lab (Virtual Lab Environment), you will have a specific number of days (varies course by course) on the remote lab platform to complete your hands-on labs. Do not start your lab until you are ready to use your lab time effectively. Time allotted in the virtual lab environment will be indicated once you log into your course. The self-paced format gives you the opportunity to complete the course at your convenience, at any location, and at your own pace. The course is available 24 hours a day.
If the course requires a remote lab system, the lab system access is allocated on a first-come, first-served basis. When you are not using the elab system, ensure that you suspend your elab to maximize your hours available to use the elab system. Note: This does not add additional days to your Lab Environment time frame.
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Click the Skytap Connectivity Documentation button to read about the hardware, software and internet connection requirements.
Exam Terms & Conditions
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