1 day EN / DE Max 16

Generative AI in Production

Traditional 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.

€920,00 excl. VAT

Individual scheduling

The courses are held as dedicated group sessions. Once you've booked, we'll coordinate a date that works for your team and send invitations to all participants.

Prerequisites

Completion of the "Application Development with LLMs on Google Cloud" or equivalent knowledge.

What you'll learn

  • Understand the challenges in productionizing applications using
    generative AI
  • Manage experimentation and evaluation for LLM-powered application
  • Productionize LLM-powered applications
  • Secure generative AI applications
  • Implement logging and monitoring for LLM-powered applications

Course modules
Generative AI operations Traditional MLOps vs. GenAIOps Components of an LLM system RAG/ReAct architecture
Application deployment options Deployment, packaging, and versioning
Maintenance and updates Testing and evaluation CI/CD pipelines for gen AI-powered apps
Security challenges Prompt security Sensitive Data Protection and DLP API Model Armor
Cloud Operations Cloud Logging Monitoring Cloud Trace Agent Analytics and AgentOps Putting it all together
Generative AI in Production