Implement Generative AI engineering with Azure Databricks (DP-3028)

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.

Module 1: Implement Generative AI engineering with 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

This course is designed for data scientists, machine learning engineers, and other AI practitioners who want to build generative AI applications using Azure Databricks. It is intended for professionals familiar with fundamental AI concepts and the Azure Databricks platform.