1 - Explore Azure Databricks
- Get started with Azure Databricks
- Identify Azure Databricks workloads
- Understand key concepts
- Data governance using Unity Catalog and Microsoft Purview
- Module assessment
2 - Use Apache Spark in Azure Databricks
- Get to know Spark
- Create a Spark cluster
- Use Spark in notebooks
- Use Spark to work with data files
- Visualize data
- Module assessment
3 - Train a machine learning model in Azure Databricks
- Understand principles of machine learning
- Machine learning in Azure Databricks
- Prepare data for machine learning
- Train a machine learning model
- Evaluate a machine learning model
- Module assessment
4 - Use MLflow in Azure Databricks
- Capabilities of MLflow
- Run experiments with MLflow
- Register and serve models with MLflow
- Module assessment
5 - Tune hyperparameters in Azure Databricks
- Optimize hyperparameters with Optuna
- Review trials
- Scale hyperparameter optimization
- Module assessment
6 - Use AutoML in Azure Databricks
- What is AutoML?
- Use AutoML in the Azure Databricks user interface
- Use code to run an AutoML experiment
- Module assessment
7 - Train deep learning models in Azure Databricks
- Understand deep learning concepts
- Train models with PyTorch
- Distribute PyTorch training with TorchDistributor
- Module assessment
8 - Manage machine learning in production with Azure Databricks
- Automate your data transformations
- Explore model development
- Explore model deployment strategies
- Explore model versioning and lifecycle management
- Module assessment
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