Build machine learning solutions using Azure Databricks (DP-3014)
Course Outline
Azure Databricks is a powerful, cloud-scale platform for data analytics and machine learning. This hands-on class guides you through every step of building, training, optimizing, and deploying machine learning solutions with Azure Databricks. Designed for data scientists and ML engineers, the course covers Apache Spark, MLflow, AutoML, hyperparameter tuning, and deep learning, all within a scalable, collaborative environment. By the end, you’ll have the skills to implement real-world machine learning projects from experimentation to production.
Build machine learning solutions using Azure Databricks (DP-3014) Benefits
-
In this course, you will learn how to:
- Learn how to harness the full potential of Databricks for big data analytics and ML.
- Apply concepts through guided exercises using Spark, MLflow, AutoML, and PyTorch.
- Gain practical experience managing experiments, tuning hyperparameters, and deploying models at scale.
- Build expertise in modern machine learning techniques, including deep learning and production-ready workflows.
- Learn how Unity Catalog and Microsoft Purview support secure, governed, and team-based ML development.
-
Training Prerequisites
To fully benefit from this course, please ensure you possess proficiency in Python for data exploration and machine learning model training using popular open-source frameworks such as Scikit-Learn, PyTorch, and TensorFlow.
Machine learning with Azure Databricks Training Outline
- choosing a selection results in a full page refresh