Implement Generative AI Engineering with Azure Databricks

Before starting this module, you should be familiar with fundamental Azure Databricks concepts.

This course covers generative AI engineering on Azure Databricks, using Spark to explore, fine-tune, evaluate, and integrate advanced language models.

It teaches how to implement techniques like retrieval-augmented generation (RAG) and multi-stage reasoning, as well as how to fine-tune large language models for specific tasks and evaluate their performance.

Students will also learn about responsible AI practices for deploying AI solutions and how to manage models in production using LLMOps (Large Language Model Operations) on Azure Databricks.

Get started with language models in Azure Databricks 

Implement Retrieval Augmented Generation (RAG) with Azure Databricks 

Implement multi-stage reasoning in Azure Databricks

Fine-tune language models with Azure Databricks 

Evaluate language models with Azure Databricks

Review responsible AI principles for language models in Azure Databricks 

Implement LLMOps in Azure Databricks