Azure Databricks Exercises
These exercises are designed to support the following training content on Microsoft Learn:
- Implement a data lakehouse analytics solution with Azure Databricks
- Implement a machine learning solution with Azure Databricks
- Implement a data engineering solution with Azure Databricks
- Implement Generative AI engineering with Azure Databricks
You’ll need an Azure subscription in which you have administrative access to complete these exercises.
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Explore Large Language Models with Azure Databricks -
Retrieval Augmented Generation using Azure Databricks -
Multi-stage Reasoning with LangChain using Azure Databricks and Azure OpenAI -
Fine-Tuning Large Language Models using Azure Databricks and Azure OpenAI -
Evaluate Large Language Models using Azure Databricks and Azure OpenAI -
Responsible AI with Large Language Models using Azure Databricks and Azure OpenAI -
Implementing LLMOps with Azure Databricks -
Real-time Ingestion and Processing with Spark Structured Streaming and Delta Lake with Azure Databricks -
End-to-End Streaming Pipeline with Delta Live Tables in Azure Databricks -
Optimize Data Pipelines for Better Performance in Azure Databricks -
Implement CI/CD workflows with Azure Databricks -
Automate data ingestion and processing using Azure Databricks -
Implementing Data Privacy and Governance using Unity Catalog with Azure Databricks -
Use a SQL Warehouse in Azure Databricks -
Automate an Azure Databricks Notebook with Azure Data Factory -
Get started with machine learning in Azure Databricks -
Use MLflow in Azure Databricks -
Train a model with AutoML -
Optimize Hyperparameters for machine learning in Azure Databricks -
Manage a machine learning model using Azure Databricks -
Train a deep learning model -
Explore Azure Databricks -
Explore data with Azure Databricks -
Transform data with Apache Spark in Azure Databricks -
Use Delta Lake in Azure Databricks -
Create a data pipeline with Delta Live tables -
Deploy workloads with Azure Databricks Workflows