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

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. Implement Generative AI Engineering with Azure Databricks (DP-3028) Benefits In this course, you will: Gain hands-on experience implementing Retrieval-Augmented Generation (RAG) and fine-tuning large language models (LLMs). Explore multi-stage reasoning techniques using LangChain, LlamaIndex, Haystack, and DSPy. Understand and apply LLMOps practices for model deployment, monitoring, and governance with MLflow and Unity Catalog. Incorporate res