| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ~Get Your Files Here ! | |||
| 1 - Getting Started with RAG on Databricks — The Enterprise AI Pattern | |||
| 1. Getting Started with RAG on Databricks.mp4 | 100.2 MB | ||
| 2 - Building the Data Pipeline — Ingest, Chunk, and Embed | |||
| 2. Building a RAG Pipeline with Databricks.mp4 | 344.8 MB | ||
| 3 - Working with Embeddings and Mosaic AI Vector Search in Databricks | |||
| 3. Working with Embeddings and Mosaic AI Vector Search in Databricks.mp4 | 238.6 MB | ||
| 4 - Building RAG Pipeline with Databricks — The Retrieval Chain | |||
| 4. Using Agent Bricks for RAG Workflows in Databricks.mp4 | 99.1 MB | ||
| 5 - Building and Optimizing Production RAG Agents on Databricks | |||
| 5. Building and Optimizing Production RAG Agents on Databricks.mp4 | 79.6 MB | ||
| 6 - REAL-WORLD ASSETS (Downloadable) | |||
| 6. ChecklistCheat Sheet.pdf | 37.9 KB | ||
| 6. Complete RAG Pipeline on Databricks.pdf | 41.9 KB | ||
| 6. FAQ with Answers.pdf | 43.1 KB | ||
| 6. REAL-WORLD ASSETS (Downloadable).html | 8.1 KB | ||
| 6. The Databricks RAG Pipeline Starter Notebook.pdf | 38.1 KB |
Databricks RAG Master Course: Build Production AI Pipelines
https://WebToolTip.com
Published 8/2026
Created by ACHRAF ER-RAYA
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 6 Lectures ( 1h 46m ) | Size: 871.9 MB
Master Databricks RAG. Build production AI pipelines, use Mosaic AI Vector Search, and deploy secure enterprise agents.
What you'll learn
⚡ Configure Databricks Workspaces and Unity Catalog to build secure, governed Generative AI data pipelines and AI applications natively on your Lakehouse.
⚡ Ingest unstructured data, process text with Apache Spark, and deploy continuous-sync Mosaic AI Vector Search indexes without external databases.
⚡ Build highly accurate Retrieval-Augmented Generation (RAG) pipelines integrating LangChain with Databricks Foundation Model APIs for LLM hosting.
⚡ Evaluate RAG models for groundedness using MLflow and deploy production-ready REST API serving endpoints for autonomous Databricks Agent workflows.
Requirements
❗ You need intermediate proficiency in Python programming and a basic understanding of SQL and data warehousing concepts. You must have access to a Databricks environment (a free trial on AWS, Azure, or GCP works perfectly for this). While a fundamental understanding of what Large Language Models (LLMs) are is helpful, no prior experience with Databricks Mosaic AI or MLflow is required.
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Udemy - Databricks Playbook - Operate, Govern and Defend the Lakehouse Posted by
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