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}catch(e){} })(); (function() { 'use strict'; var parentSelector = '.menu-item.wpml-ls-current-language.menu-item-has-children'; function toggleSubmenu(link, forceClose) { var isExpanded = link.getAttribute('aria-expanded') === 'true'; if (forceClose || isExpanded) { link.setAttribute('aria-expanded', 'false'); } else { link.setAttribute('aria-expanded', 'true'); } } function handleKeydown(e) { var key = e.key || e.keyCode; if (key === 'Enter' || key === ' ' || key === 13 || key === 32) { e.preventDefault(); toggleSubmenu(this); } else if (key === 'Escape' || key === 'Esc' || key === 27) { if (this.getAttribute('aria-expanded') === 'true') { e.preventDefault(); toggleSubmenu(this, true); } } } function handleBlur(e) { var link = this; var parent = link.closest(parentSelector); if (!parent) return; setTimeout(function() { if (!parent.contains(document.activeElement)) { toggleSubmenu(link, true); } }, 100); } function init() { var parents = document.querySelectorAll(parentSelector); for (var i = 0; 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All exercises are performed directly on the Azure Databricks platform. You will build end-to-end generative AI pipelines. This training course prepares you for the DP-3028 Microsoft certification.
This training course is part of our Artificial Intelligence Training Courses. Explore our other AI training courses to fully leverage machine learning, LLMs and generative AI.
By the end of this training course, each participant will be able to:
This training course is designed for:
Azure Databricks is a unified analytics and AI platform on Azure built around Apache Spark, Delta Lake, and MLflow. It is used for data engineering (ETL/ELT), data warehousing (lakehouse), machine learning model training, and increasingly for generative AI applications: building RAG systems, fine-tuning open models, and operationalizing LLMs at scale. MFE-IT trains data engineers and AI practitioners on the DP-3028 generative AI curriculum.
DP-3028 is Microsoft’s official training reference for generative AI with Azure Databricks, covering Vector Search, Mosaic AI Model Serving, Foundation Model APIs, RAG architectures, Unity Catalog governance, and MLflow for AI lifecycle management. The MFE-IT DP-3028 training delivers this curriculum with hands-on practice on real datasets.
RAG on Databricks uses Vector Search to index your data (powered by Delta tables), retrieves relevant context at query time, then feeds it to an LLM via Mosaic AI Model Serving or Foundation Model APIs. Unity Catalog governs access, MLflow logs evaluations, and AI Gateway centralizes routing and policies. Through MFE-IT’s hands-on approach, learners build a production-grade RAG application during the training.
For generative AI specifically, Azure Databricks currently offers a more mature stack with Mosaic AI, Vector Search, and Foundation Model APIs natively integrated. Azure Synapse is stronger for traditional data warehousing and Power BI integration. Many organizations use both. Our MFE-IT training course on generative AI with Azure Databricks DP-3028 explains where each platform fits in a modern data and AI architecture.