T-GAIPROD-AOfficial Google Curriculum
Generative AI in Production
1 dayInstructor-ledAdvancedLoading...
Overview
In this course, you learn about the different challenges that arise when productionizing generative AI-powered applications versus traditional ML. You will learn how to manage experimentation and tuning of your LLMs, then you will discuss how to deploy, test, and maintain your LLM-powered applications.
What You'll Learn
- Describe the challenges in productionizing applications using generative AI.
- Manage experimentation and evaluation for LLM-powered applications.
- Productionize LLM-powered applications.
- Implement logging and monitoring for LLM-powered applications.
Who Should Attend
Developers and machine learning engineers who wish to operationalize Gen AI-based applications
Prerequisites
Completion of "Introduction to Developer Efficiency on Google Cloud" or equivalent knowledge.
Products Covered
Vertex AIVertex AI PipelinesVertex AI EvaluationVertex AI StudioVertex AI Gemini APIGemini
Course Modules
1
Introduction to Generative AI in Production
Topics
- AI System Demo: Coffee on Wheels
- Traditional MLOps vs. GenAIOps
- Generative AI Operations
- Components of an LLM System
Learning Outcomes
- Understand generative AI operations
- Compare traditional MLOps and GenAIOps
- Analyze the components of an LLM system
2
Managing Experimentation
Topics
- Datasets and Prompt Engineering
- RAG and ReACT Architecture
- LLM Model Evaluation (metrics and framework)
- Tracking Experiments
Learning Outcomes
- Experiment with datasets and prompt engineering.
- Utilize RAG and ReACT architecture.
- Evaluate LLM models.
- Track experiments.
Activities
Lab: Unit Testing Generative AI ApplicationsOptional Lab: Generative AI with Vertex AI: Prompt Design
3
Productionizing Generative AI
Topics
- Deployment, packaging, and versioning (GenAIOps)
- Testing LLM systems (unit and integration)
- Maintenance and updates (operations)
- Prompt security and migration
Learning Outcomes
- Deploy, package, and version models
- Test LLM systems
- Maintain and update LLM models
- Manage prompt security and migration
Activities
Lab: Vertex AI Pipelines: Qwik StartLab: Safeguarding with Vertex AI Gemini API
4
Logging and Monitoring for Production LLM Systems
Topics
- Cloud Logging
- Prompt versioning, evaluation, and generalization
- Monitoring for evaluation-serving skew
- Continuous validation
Learning Outcomes
- Utilize Cloud Logging
- Version, evaluate, and generalize prompts
- Monitor for evaluation-serving skew
- Utilize continuous validation
Activities
Lab: Vertex AI: Gemini Evaluations PlaybookOptional Lab: Supervised Fine Tuning with Gemini for Question and Answering
Get This Training
No public classes currently scheduled. Express interest below or request private training.
Course Details
- Course Code
- T-GAIPROD-A
- Duration
- 1 day
- Format
- Instructor-led
- Level
- Advanced
- Hands-on Labs
- 4
- Modules
- 4
- Activities
- 6
- Price
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Questions About This Course?
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