Training Microsoft

Training goals

code: DP-3028 | version: A

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 on Azure Databricks.

 

Audience Profile:
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.

Conspect Show list

  • Implement Generative AI engineering with Azure Databricks
    • Module 1: Get started with language models in Azure Databricks
    • Module 2: Implement Retrieval Augmented Generation (RAG) with Azure Databricks
    • Module 3: Implement multi-stage reasoning in Azure Databricks
    • Module 4: Fine-tune language models with Azure Databricks
    • Module 5: Evaluate language models with Azure Databricks
    • Module 6: Review responsible AI principles for language models in Azure Databricks
    • Module 7: Implement LLMOps in Azure Databricks
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Additional information

Prerequisites

Familiarity with fundamental Azure Databricks concepts. Consider completing the "Get started with artificial intelligence on Azure" learning path and the "Explore Azure Databricks" module first.
Difficulty level
Duration 1 day
Certificate

The participants will obtain certificates signed by Microsoft (course completion).
Trainer

Microsoft Certified Trainer (MCT)

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