Get Started with Databricks for Generative AI
This course offers a practical introduction to the Databricks Data Intelligence Platform, focusing on its key components and features for building and deploying generative AI systems. Participants will learn how Databricks facilitates the development of scalable generative AI solutions and explore tools such as AI Search, the Agent Framework, and MLflow's generative AI capabilities for model tracking and logging. This course includes hands-on experience in constructing and evaluating Retrieval-Augmented Generation (RAG) pipelines, deploying generative AI agents, and leveraging evaluation frameworks to optimize performance. By the end of the course, learners will be equipped with the skills to design, deploy, and monitor common generative AI applications on the Databricks Data Intelligence Platform.
Languages Available: English | 日本語 | Português BR | 한국어 | Français
The content was developed for participants with these skills/knowledge/abilities:
• Familiarity with the Databricks Data Intelligence Platform and basic workspace operations (create clusters, run code in notebooks, use basic notebook operations)
• Basic knowledge of Python programming and working with APIs (Databricks SDK, external model integrations)
• Understanding of machine learning fundamentals, including model training, evaluation, and deployment concepts
• Basic familiarity with generative AI concepts (large language models, prompt engineering, hallucinations, retrieval-augmented generation)
• Intermediate experience with Unity Catalog for data governance and model registry operations
• Basic knowledge of vector search and similarity search concepts for document retrieval
• Familiarity with MLflow for experiment tracking, model logging, and evaluation frameworks
• Understanding of Delta Lake and data management concepts (tables, schemas, data formats)
Outline
1. Databricks AI Overview
• The Generative AI Opportunity
• Databricks AI Platform
2. Prompt Engineering with AI Playground
• Prompt Engineering Basics
• Demo: Prompt Engineering in AI Playground
3. Build & Register a Retrieval Pipeline
• Retrieval Augmented Generation (RAG) Fundamentals
• Databricks AI Search
• MLFlow for GenAI
• Demo: Build & Register a RAG Application
4. Evaluating and Deploying AI Systems
• End-to-end Evaluation
• Demo: Evaluation with MLflow
• Real-time Deployment with Model Serving
• Demo: Real-time Deployment with Model serving
5. Agent Bricks
• Introduction to Agent Bricks
• Lab: End-to-end RAG Pipeline
Upcoming Public Classes
Date | Time | Your Local Time | Language | Price |
|---|---|---|---|---|
Aug 12 | 09 AM - 11 AM (America/Los_Angeles) | - | English | Free |
Aug 18 | 12 PM - 02 PM (Asia/Singapore) | - | English | Free |
Sep 03 | 09 AM - 11 AM (America/Los_Angeles) | - | English | Free |
Sep 15 | 12 PM - 02 PM (Asia/Singapore) | - | English | Free |
Oct 08 | 09 AM - 11 AM (America/Los_Angeles) | - | English | Free |
Oct 20 | 12 PM - 02 PM (Asia/Singapore) | - | English | Free |
Public Class Registration
If your company has purchased success credits or has a learning subscription, please fill out the Training Request form. Otherwise, you can register below.
Private Class Request
If your company is interested in private training, please submit a request.
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Comprehensive training offering for large scale customers that includes learning elements for every style of learning. Inquire with your account executive for details
