Course Overview
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.
What are the skills covered
- 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
Who should attend this course
his 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.
Course Curriculum
What are the Prerequisites
Before starting this module, you should be familiar with fundamental AI concepts and Azure Databricks. Consider completing the Get started with artificial intelligence learning path and the Explore Azure Databricks module first.
Course Modules
Exam & Certification
Note: There is no exam directly associated with this course. However, Microsoft offers an extensive portfolio of industry-recognized certifications that can help you stand out as a tech professional in 2025 and beyond. Achieving Microsoft certification is one of the most effective ways to validate your skills and accelerate your career.
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