Databricks Setup
This guide covers setting up Databricks Free Edition for the courses.
Create Account
- Go to databricks.com
- Click "Try Databricks Free"
- Sign up with your email
- Verify your account
Workspace Setup
Create Cluster
- Navigate to Compute in the sidebar
- Click Create Cluster
- Select the smallest instance type
- Enable auto-termination (15 minutes)
Install Libraries
For Python notebooks:
%pip install mlflow databricks-feature-store
Features Used
Course 3: MLOps
| Feature | Purpose |
|---|---|
| Experiments | MLflow tracking |
| Catalog | Model registry |
| Jobs | Pipeline orchestration |
| SQL Warehouses | Feature computation |
| Playground | Model testing |
Course 4: GenAI
| Feature | Purpose |
|---|---|
| Playground | Foundation Models |
| Vector Search | Semantic retrieval |
| Genie | AI/BI demo |
| Experiments | Evaluation tracking |
| Jobs | RAG orchestration |
Notebook Conventions
All Databricks notebooks in this repository use:
# Databricks notebook source
# MAGIC %md
# MAGIC # Notebook Title
# COMMAND ----------
# Code cell
Running Labs
- Import notebook into Databricks workspace
- Attach to running cluster
- Run cells sequentially
- Complete TODO sections
Troubleshooting
Cluster won't start
- Check your free tier limits
- Ensure auto-termination is enabled
- Try a smaller instance type
MLflow not found
%pip install mlflow --quiet
dbutils.library.restartPython()
Feature Store issues
%pip install databricks-feature-store --quiet
dbutils.library.restartPython()