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- AI
Generative AI with Databricks
This learning path is actively in production. More content will be added to this page as it gets published and becomes available in the library. Planned content includes:
- Introduction to Generative AI with Databricks - Prompt Engineering and Prototyping in Databricks AI Playground - Building Retrieval-Augmented Generation (RAG) Pipelines with Databricks - Mosaic AI Agent Framework — Building and Deploying AI Agents - MLflow, Model Serving, and Governance for Generative AI - Production-Grade Generative AI with Databricks at Scale
This comprehensive learning path will show you how to build, deploy, and scale intelligent applications on the Databricks platform. By following this path, you’ll gain hands-on insights into Databricks’ cutting-edge tools such as Mosaic AI, AI Playground, MLflow, and Unity Catalog, and learn how to operationalize generative AI for real-world business and technical challenges. Whether you’re a data scientist, AI engineer, or solution architect, this path equips you to create scalable, reliable, and enterprise-ready AI solutions that deliver measurable value across your organization.
Content in this path
Generative AI with Databricks
Watch the following courses to get learning about Generative AI with Databricks!
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What You'll Learn
- How to design, prototype, and refine generative AI workflows using Databricks’ AI Playground, prompt engineering techniques, and retrieval-augmented generation (RAG) pipelines
- How to build, deploy, and manage AI agents and foundation models with the Mosaic AI Agent Framework, MLflow, and Model Serving, while ensuring governance, security, and reproducibility
- How to operationalize production-grade generative AI solutions using Databricks at scale, enabling enterprise-wide adoption
- Learners should be familiar with Databricks and Python based data workflows.
- Generative AI
- Databricks
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