Azure Databricks
Design AI with Apache Spark™-based analytics.
Learning
Learning Paths
Azure Databricks is a cloud-scale platform for data analytics and machine learning. Data scientists and machine learning engineers can use Azure Databricks to implement machine learning solutions at scale.
Levels: Intermediate
Roles: Data Scientist
Modules
Design a machine learning solution with Azure Machine Learning v2
Levels: Beginner
Roles: Data Scientist
Modules
Data engineering with Azure Databricks
Levels: Intermediate
Roles: Data Engineer
Modules
Learning Modules
Azure Architects design and recommend data integration solutions.
Design a data ingestion strategy for machine learning projects
Explore Azure Databricks
Use Apache Spark in Azure Databricks
Run Azure Databricks Notebooks with Azure Data Factory
Use SQL Warehouses in Azure Databricks
Learn how to use AutoML to train optimal machine learning models for your data in Azure Databricks
Learn how to use deep learning libraries like PyTorch in Azure Databricks, and to distribute training by using Horovod
Learn how to use the Hyperopt library in Azure Databricks to tune machine learning hyperparameters.
Learn how to train machine learning models using Spark and the MLlib library in Azure Databricks.
Learn how to use MLflow in Azure Databricks to track machine learning experiments and deploy models.
Use Delta Lake in Azure Databricks