Skip to main content

Generative AI Solution Development

This is your introduction to contextual generative AI solutions using the retrieval-augmented generation (RAG) method. First, you’ll be introduced to RAG architecture and the significance of contextual information using Mosaic AI Playground. Next, we’ll show you how to prepare data for generative AI solutions and connect this process with building a RAG architecture. Finally, you’ll explore concepts related to context embedding, vectors, vector databases, and the utilization of Mosaic AI Vector Search.


Languages Available: English | 日本語 | Português BR | 한국어

Skill Level
Associate
Duration
4h
Prerequisites
  • Familiarity with natural language processing concepts
  • Familiarity with prompt engineering/prompt engineering best practices 
  • Familiarity with the Databricks Data Intelligence Platform


Outline

Introduction to RAG

  • What is RAG?
  • In Context Learning with AI Playground


Preparing Data for RAG Solutions

  • Data Storage and Governance
  • Data Extraction and Chunking
  • Embedding Model
  • Data Preparation in Databricks


Vector Search

  • Introduction to Vector Stores
  • Vector Search Process and Performance
  • Choosing the right Vector Database
  • Mosaic AI Vector Search
  • Creating a Vector Search Index


Assembling and Evaluating a RAG Application

  • MLflow
  • Evaluating a RAG Application and Continual Learning
  • Assembling a RAG Application

Upcoming Public Classes

Date
Time
Language
Price
May 08
09 AM - 01 PM (Europe/London)
English
$750.00
Jul 08
09 AM - 01 PM (America/New_York)
English
$750.00
Jul 09
09 AM - 01 PM (Asia/Kolkata)
English
$750.00
Jul 10
01 PM - 05 PM (Europe/London)
English
$750.00

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.

See all our registration options

Registration options

Databricks has a delivery method for wherever you are on your learning journey

Runtime

Self-Paced

Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos

Register now

Instructors

Instructor-Led

Public and private courses taught by expert instructors across half-day to two-day courses

Register now

Learning

Blended Learning

Self-paced and weekly instructor-led sessions for every style of learner to optimize course completion and knowledge retention. Go to Subscriptions Catalog tab to purchase

Purchase now

Scale

Skills@Scale

Comprehensive training offering for large scale customers that includes learning elements for every style of learning. Inquire with your account executive for details

Upcoming Public Classes

Data Engineer

Automated Deployment with Databricks Asset Bundles

This course provides a comprehensive review of DevOps principles and their application to Databricks projects. It begins with an overview of core DevOps, DataOps, continuous integration (CI), continuous deployment (CD), and testing, and explores how these principles can be applied to data engineering pipelines.

The course then focuses on continuous deployment within the CI/CD process, examining tools like the Databricks REST API, SDK, and CLI for project deployment. You will learn about Databricks Asset Bundles (DABs) and how they fit into the CI/CD process. You’ll dive into their key components, folder structure, and how they streamline deployment across various target environments in Databricks. You will also learn how to add variables, modify, validate, deploy, and execute Databricks Asset Bundles for multiple environments with different configurations using the Databricks CLI.

Finally, the course introduces Visual Studio Code as an Interactive Development Environment (IDE) for building, testing, and deploying Databricks Asset Bundles locally, optimizing your development process. The course concludes with an introduction to automating deployment pipelines using GitHub Actions to enhance the CI/CD workflow with Databricks Asset Bundles.

By the end of this course, you will be equipped to automate Databricks project deployments with Databricks Asset Bundles, improving efficiency through DevOps practices.

Languages Available: English | 日本語 | Português BR | 한국어

Paid
4h
Lab
instructor-led
Professional

Questions?

If you have any questions, please refer to our Frequently Asked Questions page.