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Databricks Get Started Days (Data Engineering + Generative AI)

Get Started with Databricks for Data Engineering

In this course, you will learn basic skills that will allow you to use the Databricks Data Intelligence Platform to perform a simple data engineering workflow and support data warehousing endeavors. You will be given a tour of the workspace and be shown how to work with objects in Databricks such as catalogs, schemas, volumes, tables, compute clusters, and notebooks. You will then follow a basic data engineering workflow to perform tasks such as creating and working with tables, ingesting data into Delta Lake, transforming data through the medallion architecture, and using Databricks Workflows to orchestrate data engineering tasks. You’ll also learn how Databricks supports data warehousing needs through the use of Databricks SQL, Delta Live Tables, and Unity Catalog. With the purchase of a Databricks Labs subscription, the course also closes out with a comprehensive lab exercise to practice what you’ve learned in a live Databricks Workspace environment.


Get Started with Databricks for Generative AI

This course offers a practical introduction to the Mosaic AI 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 Mosaic AI tools such as Vector 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 using Mosaic AI.


You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.

Skill Level
Onboarding
Duration
4h
Prerequisites

Get Started with Databricks for Data Engineering


  • A basic understanding of data engineering principles and topics such as data collection, extraction, ingestion, and transformation.


Get Started with Databricks for Generative AI


  • Basic knowledge of generative AI engineering topics is recommended.

Outline

Get Started with Databricks for Data Engineering


Databricks Overview

Databricks Data Intelligence Platform

Demo: Databricks Workspace Walkthrough


Using Databricks for Data Engineering

Introduction to Data Engineering

LakeFlow Overview

Delta Lake Overview

Demo: Creating and Working with a Delta Table

Lakeflow Connect Ingestion Techniques Overview

Demo: Ingesting Data into Delta Lake

Data Transformation Overview

Demo: Transforming Data Using the Medallion Architecture

Performing ETL with DLT

Unified Orchestration Using Lakeflow Jobs

Demo: Creating a Simple Databricks LakeFlow Job

Lab: Ingest and Manipulate a Delta Table


Get Started with Databricks for Generative AI


Databricks Mosaic AI Overview

The Generative AI Opportunity

Databricks Mosaic AI Platform


Prompt Engineering with Internal & External Models

Prompt Engineering Basics

Demo: Prompt Engineering in AI Playground

Introduction to Mosaic AI Gateway

Demo: External Models with AI Gateway


Build & Register a RAG Pipeline

Retrieval Augmented Generation (RAG) Fundamentals

Mosaic AI Vector Search

MLFlow for GenAI

Demo: Build & Register a RAG Application


Evaluating and Deploying AI Systems

End-to-end Evaluation

Demo: Evaluation with Agent Framework

Real-time Deployment with Model Serving

Demo: Real-time Deployment with Model Serving


End-to-end RAG Pipeline on Databricks

Lab: End-to-end RAG Pipeline

Upcoming Public Classes

Date
Time
Your Local Time
Language
Price
Jul 23
11 AM - 03 PM (Asia/Singapore)
-
English
Free
Jul 23
01 PM - 05 PM (Europe/London)
-
English
Free
Jul 23
09 AM - 01 PM (America/Los_Angeles)
-
English
Free
Aug 19
11 AM - 03 PM (Asia/Singapore)
-
English
Free
Aug 21
01 PM - 05 PM (Europe/London)
-
English
Free
Aug 26
09 AM - 01 PM (America/Los_Angeles)
-
English
Free
Sep 18
11 AM - 03 PM (Asia/Singapore)
-
English
Free
Sep 23
01 PM - 05 PM (Europe/London)
-
English
Free
Sep 25
09 AM - 01 PM (America/Los_Angeles)
-
English
Free
Oct 21
11 AM - 03 PM (Asia/Singapore)
-
English
Free
Oct 23
01 PM - 05 PM (Europe/London)
-
English
Free
Oct 28
09 AM - 01 PM (America/Los_Angeles)
-
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.

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

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Instructors

Instructor-Led

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

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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

Databricks Get Started Days (Lakehouse Architecture + Data Warehousing)

Get Started with Lakehouse Architecture on Databricks

In this course, you will explore the Databricks Data Intelligence Platform from the perspective of platform architecture, specifically related to the platform foundation in lakehouse architecture. You will learn about the scope, vision, and capabilities of a platform founded in lakehouse architecture, with a focus on how Databricks integrates with a cloud platform’s architecture. You’ll learn about the key features of a successful lakehouse implementation, specifically how to adhere to the well-architected lakehouse framework, which emphasizes structural excellence through specific dimensions, principles and best practices. You’ll also learn about data architecture strategy for the acceleration of data and AI endeavors.

Get Started with Databricks for Data Warehousing

This course provides a comprehensive overview of Databricks’ modern approach to data warehousing, highlighting how a data lakehouse architecture combines the strengths of traditional data warehouses with the flexibility and scalability of the cloud. You’ll learn about the AI-driven features that enhance data transformation and analysis on the Databricks Data Intelligence Platform. Designed for data warehousing practitioners, this course provides you with the foundational information needed to begin building and managing high-performant, AI-powered data warehouses on Databricks.

This course is designed for those starting out in data warehousing and those who would like to execute data warehousing workloads on Databricks. Participants may also include data warehousing practitioners who are familiar with traditional data warehousing techniques and concepts and are looking to expand their understanding of how data warehousing workloads are executed on Databricks.

You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.

Free
4h
instructor-led
Onboarding

Databricks Get Started Days (Data Engineering + Machine Learning)

Get Started with Databricks for Data Engineering

In this course, you will learn basic skills that will allow you to use the Databricks Data Intelligence Platform to perform a simple data engineering workflow and support data warehousing endeavors. You will be given a tour of the workspace and be shown how to work with objects in Databricks such as catalogs, schemas, volumes, tables, compute clusters, and notebooks. You will then follow a basic data engineering workflow to perform tasks such as creating and working with tables, ingesting data into Delta Lake, transforming data through the medallion architecture, and using Databricks Workflows to orchestrate data engineering tasks. You’ll also learn how Databricks supports data warehousing needs through the use of Databricks SQL, Delta Live Tables, and Unity Catalog. With the purchase of a Databricks Labs subscription, the course also closes out with a comprehensive lab exercise to practice what you’ve learned in a live Databricks Workspace environment.

Get Started with Databricks for Machine Learning

In this course, you will develop the foundational skills needed to use the Databricks Data Intelligence Platform for executing basic machine learning workflows and supporting data science workloads. You will explore the platform from the perspective of a machine learning practitioner, covering topics such as feature engineering with Databricks Notebooks and model lifecycle tracking with MLflow. Additionally, you will learn about real-time model inference with Mosaic AI Model Serving and experience Databricks’ “glass box” approach to model development through AutoML. The course includes three instructor-led demonstrations, culminating in a comprehensive lab that reinforces the concepts covered in the demos.

You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.

Free
4h
instructor-led
Onboarding

Databricks Get Started Days (Data Engineering + SQL Analytics and BI)

Get Started with Databricks for Data Engineering

In this course, you will learn basic skills that will allow you to use the Databricks Data Intelligence Platform to perform a simple data engineering workflow and support data warehousing endeavors. You will be given a tour of the workspace and be shown how to work with objects in Databricks such as catalogs, schemas, volumes, tables, compute clusters and notebooks. You will then follow a basic data engineering workflow to perform tasks such as creating and working with tables, ingesting data into Delta Lake, transforming data through the medallion architecture, and using Databricks Workflows to orchestrate data engineering tasks. You’ll also learn how Databricks supports data warehousing needs through the use of Databricks SQL, Delta Live Tables, and Unity Catalog. With the purchase of a Databricks Labs subscription, the course also closes out with a comprehensive lab exercise to practice what you’ve learned in a live Databricks Workspace environment.

Get Started with SQL Analytics and BI on Databricks

In this course, you will learn basic skills that will allow you to use the Databricks Data Intelligence Platform to perform a simple data analytics workflow and support data warehousing endeavors. You will be given a tour of the workspace and be shown how to work with data objects in Databricks such as catalogs, schemas, tables, compute clusters, notebooks, and dashboards. You will then follow a basic data analytics workflow to perform tasks such as manipulating data using Databricks SQL, leveraging Delta Lake version logs to time travel, creating dashboards within the platform, and creating Genie Spaces for data exploration using natural language prompts. You will also learn how Databricks supports data warehousing needs through the use of Databricks SQL, Delta Live Tables, and Unity Catalog. 

You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.

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

Free
4h
instructor-led
Onboarding

Questions?

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