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

Learning Path1: 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