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Part 2: Setting up your Free Edition account

Part 2: Setting up your Free Edition account

Creating an account

Go to https://www.databricks.com/try-databricks in your browser and select Free Edition (not the 14-day trial).

You will see a sign-up form. Fill in your name, email, and a password. Use your work email if you intend to eventually connect this to your organisation's Databricks workspace - it makes things simpler later. If you just want to experiment, a personal email is fine.

After submitting the form, you will receive a verification email. Click the link in it. If it does not arrive within five minutes, check your spam folder.

Once verified, you will be asked to choose a cloud provider: AWS, Azure, or Google Cloud. For Free Edition this choice does not affect what you can do - pick whichever you like. We use AWS in the screenshots throughout this course, but the interface is identical on Azure and Google Cloud.

What you see after first login

After logging in you land on the Databricks home screen. It looks like this:

  • Left sidebar - the main navigation. The icons from top to bottom are: Home, Workspace, Data, Compute, Workflows, and Settings. We will use most of these.
  • Central panel - this changes depending on what you have selected in the sidebar. On first login it shows a "Get started" panel with shortcuts to create a notebook, import data, and so on.
  • Top bar - your username, a help icon, and a search box.

Note on the sidebar: In Databricks Runtime 13 and later (including all current Free Edition workspaces), the Repos item no longer appears as a separate sidebar entry. Git-backed notebooks are now accessed through Workspace - look for the Git folder icon or use the Workspace browser to navigate to your repos. Part 5 covers this in detail.

The most important things to understand at this stage:

Workspace is where your notebooks live. Think of it like a folder structure in File Explorer, but in the cloud. When you create a notebook, it goes into your Workspace. Git-backed repos also live here, accessible via the Workspace browser.

Compute is where you manage clusters - the actual computers that run your code. Without a running cluster, notebooks cannot execute. We will cover this properly in Part 6.

Data is where you browse and manage datasets. For Free Edition users this shows you DBFS (Databricks File System) - the storage layer for your workspace.

Starting a cluster before anything else

Before a notebook can run, a cluster must be running. On Free Edition, you get one cluster.

Click Compute in the left sidebar. If you have never created a cluster, it shows an empty list and a button that says Create Compute (or Create cluster - the label has changed between versions). Click it.

On the cluster creation screen you will see various configuration options. On Free Edition, most of these are fixed — you cannot choose the instance type or size. What you can choose is the Databricks Runtime version. Select the latest LTS ML version (something like "14.3 LTS ML" or similar — LTS means Long Term Support, ML means it pre-installs machine learning libraries like scikit-learn, XGBoost, and MLflow so you do not have to install them yourself). If you are not sure which to pick, choose the one with "LTS ML" in the name.

Click Create Compute. The cluster takes 3-5 minutes to start. The status shows "Pending" and then "Running". While it is starting, move on to the next section.