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Generative AI Application Deployment and Monitoring

The course covers details about how to deploy, operationalize, and monitor generative deploying, operationalizing, and monitoring generative AI applications. The course will help you gain skills in the deployment of generative AI applications using tools like Model Serving. It also covers how to operationalize generative AI applications following best practices and recommended architectures. Finally, the course discusses the idea of monitoring generative AI applications and their components using Lakehouse Monitoring.

Skill Level

The content was developed for participants with these skills/knowledge/abilities: 

  • Familiarity with prompt engineering/prompt engineering best practices 
  • Familiarity with the Databricks Data Intelligence Platform
  • Familiarity with RAG  (preparing data, building a RAG architecture, concepts like embedding, vectors, vector databases, etc.)
  • Experience with building LLM applications using multi-stage reasoning LLM chains and agents
  • Familiarity with Databricks Data Intelligence Platform tools for evaluation and governance. 


Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos

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Registration options

Databricks has a delivery method for wherever you are on your learning journey



Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos

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Public and private courses taught by expert instructors across half-day to two-day courses

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Blended Learning

Self-paced and weekly instructor-led sessions for every style of learner to optimize course completion and knowledge retention. Go to Subscriptions Catalog tab to purchase

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Comprehensive training offering for large scale customers that includes learning elements for every style of learning. Inquire with your account executive for details

Upcoming Public Classes

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If you have any questions, please refer to our Frequently Asked Questions page.