- Provision an Azure Databricks workspace and cluster
- Use Azure Databricks to train a machine learning model
- Use MLflow to track experiments and manage machine learning models
- Integrate Azure Databricks with Azure Machine Learning
In this one-day Implementing a Machine Learning Solution with Microsoft Azure Databricks training class, you'll learn how to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning.
This courseis designed for data scientists with experience in Python who need to learn how to apply their data science and machine learning skills on Azure Databricks
Webucator is a Microsoft Certified Partner for Learning Solutions (CPLS). This class uses official Microsoft courseware and will be delivered by a Microsoft Certified Trainer (MCT).
- Introduction to Azure Databricks
- Getting Started with Azure Databricks
- Working with Data in Azure Databricks
- Lab: Getting Started with Azure Databricks
- Lab: Working with Data in Azure Databricks
- Training and Evaluating Machine Learning Models
- Preparing Data for Machine Learning
- Training a Machine Learning Model
- Lab: Preparing Data for Machine Learning
- Lab: Training a Machine Learning Model
- Managing Experiments and Models
- Using MLflow to Track Experiments
- Managing Models
- Lab: Using MLflow to Track Experiments
- Lab: Managing Models
- Integrating Azure Databricks and Azure Machine Learning
- Tracking Experiments with Azure Machine Learning
- Deploying Models
- Lab: Running Experiments in Azure Machine Learning
- Lab: Deploying Models in Azure Machine Learning
Each student will receive a comprehensive set of materials, including course notes and all the class examples.
Experience in the following is required for this Azure class:
- Experience using Python to work with data and some knowledge of machine learning concepts.