Google Generative AI in Production
- Code training GO8338
- Duur 1 dag
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Methode
Deze training is in de volgende formats beschikbaar:
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Klassikale training
Klassikaal leren
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Op locatie klant
Op locatie klant
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Virtueel leren
Virtueel leren
Vraag deze training aan in een andere lesvorm.
Trainingsbeschrijving
Naar bovenTraditional MLOps is a set of practices to productionize traditional ML systems for enterprise applications. Generative AI raises new challenges in managing and productionizing applications at scale. The field of generative AI operations seeks to address these new challenges.
In this course, you learn about the challenges that arise when deploying and productionizing generative AI-powered applications. You learn how to secure your generative AI-powered applications. Finally, you will discuss best practices for logging and monitoring your generative AI-powered applications in production.
Products:
- Vertex AI
Updated August 2026
Virtueel en Klassikaal™
Virtueel en Klassikaal™ is een eenvoudig leerconcept en biedt een flexibele oplossing voor het volgen van een klassikale training. Met Virtueel en Klassikaal™ kunt u zelf beslissen of u een klassikale training virtueel (vanuit huis of kantoor )of fysiek op locatie wilt volgen. De keuze is aan u! Cursisten die virtueel deelnemen aan de training ontvangen voor aanvang van de training alle benodigde informatie om de training te kunnen volgen.
Data
Naar bovenDoelgroep
Naar bovenDevelopers, DevOps engineers and machine learning engineers who wish to operationalize GenAI-based applications
Trainingsdoelstellingen
Naar bovenAfter this course participants should be able to:
- Understand generative AI operations
- Compare traditional MLOps and GenAIOps
- Analyze the components of an LLM system
- Define and compare RAG and ReAct
- Evaluate application deployment options
- Deploy, package, and version apps
- Maintain and update LLM models
- Test and evaluate gen AI-powered apps
- Deploy CI/CD pipelines for gen AI-powered apps
- Identify security challenges for gen AI applications
- Understand prompt security issues
- Apply sensitive data protection and DLP API
- Implement Model Armor
Inhoud training
Naar bovenModule 01: Introduction to Generative AI in Production
- Generative AI operations
- Traditional MLOps vs. GenAIOps
- Components of an LLM system
- RAG/ReAct architecture
Module 02: Generative AI Application Deployment
- Application deployment options
- Deployment, packaging, and versioning
- Lab: Deploying an Agentic Application on Cloud Run
Module 03: Productionizing Generative AI
- Maintenance and updates
- Testing and evaluation
- CI/CD pipelines for gen AI-powered apps
- Lab: Tracking Versions of Generative AI Applications
Module 04: Securing Generative AI Applications
- Security challenges
- Prompt security
- Sensitive Data Protection and DLP API
- Model Armor
- Lab: Securing Generative AI-Powered Applications
Voorkennis
Naar bovenCompletion of the "Application Development with LLMs on Google Cloud" or equivalent knowledge.
Examen
Naar bovenNone
Vervolgtrainingen
Naar bovenNone
