Learn to operate machine learning solutions at cloud scale using Azure Machine Learning. This course leverages your Python and ML knowledge to manage data ingestion, model training, deployment, and monitoring in Microsoft Azure.

Learning Outcomes

• Provision an Azure Machine Learning workspace
• Use automated machine learning and designer tools for no-code model training
• Run code-based experiments and train machine learning models
• Create and manage datastores and datasets
• Manage experiment environments and compute targets
• Create and run pipelines to automate ML workflows
• Deploy models for real-time and batch inferencing
• Optimize models with hyperparameter tuning and automated ML
• Apply responsible ML principles including differential privacy and fairness
• Monitor models and data drift using Application Insights

Prerequisites

Fundamental knowledge of cloud computing concepts, experience in using Python for data exploration and visualization, training and validating ML models with frameworks like Scikit-Learn, PyTorch, TensorFlow, and working with containers.

Prerequisite Courses

• Explore Microsoft cloud concepts
• Create machine learning models
• Administer containers in Azure
• Microsoft Azure AI Fundamentals