Data Engineering · Data Engineering

Databricks

This track covers Databricks' unified analytics platform: Lakehouse architecture, cluster management, notebooks, and Delta Lake. You'll learn to build and run ETL pipelines, optimize Spark jobs, and enable data quality. It's for data engineers and analysts who want to operationalize data workloads. You'll leave able to design multi-stage ELT workflows and govern data on the Databricks platform.

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Lesson outline

  1. 1
    Sign Up for Databricks Community Edition

    Sign up for Databricks Community Edition — Databricks tutorial.

  2. 2
    Explore the Databricks Workspace UI

    Learn the Databricks workspace UI in this step-by-step tutorial. Understand the layout, navigate core components like the sidebar and notebooks, and complete a hands-on exercise to build confidence.

  3. 3
    Run Your First Databricks Notebook

    Learn how to create a Databricks workspace, launch a cluster, and run your first notebook in this hands-on tutorial for beginners.

  4. 4
    Databricks Clusters & Node Types

    Understand Databricks clusters and node types — how to choose the right cluster and nodes for your workloads, with a hands-on exercise and troubleshooting tips.

  5. 5
    Create an All-Purpose Cluster

    Create and configure an all-purpose cluster — Databricks.

  6. 6
    Manage Databricks Libraries

    Learn to manage libraries and install Python packages in Databricks. This lesson covers library types, installation methods, and best practices for keeping clusters up-to-date.

  7. 7
    Work with DBFS

    Master the Databricks File System (DBFS) in this hands-on tutorial. Learn what DBFS is, how to manage files using dbutils and SQL, and best practices for storing data and notebooks in your Databricks workspace.

  8. 8
    Databricks SQL: Query Tables

    Learn how to query tables in Databricks SQL. This hands-on Databricks tutorial covers the essentials: connecting to tables, running queries, and troubleshooting common issues. Perfect for data engineers and analysts looking to operationalize data workloads on the Lakehouse.

  9. 9
    Read & Write Spark DataFrames

    Master reading and writing data with Spark DataFrames in Databricks. This hands-on tutorial covers core concepts, step-by-step workflows, and troubleshooting for real-world data engineering.

  10. 10
    Delta Lake Table Basics

    Delta Lake table basics — Databricks.

  11. 11
    Create Your First Delta Table

    Create your first Delta table in Databricks — hands-on steps, troubleshooting, and what to study next.

  12. 12
    CRUD on Delta Tables

    Master CRUD operations on Delta tables in Databricks Lakehouse, with hands-on steps and best practices.

    Databricks — step-by-step tutorials

    What you will find here

    This track walks through databricks in order — each lesson is server-rendered HTML you can read without JavaScript. Follow the outline, then practice in the browser IDE when a lesson links to runnable code.

    Tutorials vs quizzes and code samples

    Tutorials teach in sequence. For quick checks use quizzes. For copy-paste snippets see code samples. For deeper reading browse articles.