Manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Python, Azure Machine Learning and MLflow.
Duration - 10 Hours
Level - Intermediate
Style - Self paced
Course Type - Credential Ready
Certification - Yes
Hands on Labs - Yes
Solution Areas - Azure - Cloud & AI Platform
This module introduces key concepts in designing machine learning solutions and configuring Azure ML workspaces. You'll learn to structure datasets, select compute resources, and explore Azure ML tools—covering workspace setup, data assets, compute targets, and a live demo with AutoML.
This module focuses on experimenting with Azure Machine Learning through custom model training using notebooks and terminal configurations, alongside model tracking via MLflow. It then explores optimization techniques using automated hyperparameter tuning—covering sampling strategies, search space design, and performance metrics to streamline and enhance model accuracy.
This module covers model management and deployment in Azure Machine Learning. Learners will explore registering and reviewing MLflow models, defining model signatures, and packaging feature specifications. The session also walks through deploying models to online and batch endpoints, configuring compute, and validating services for scalable consumption.
This module explores the optimization of language models for generative AI on Azure. Participants will learn to select, deploy, and benchmark models using the Azure AI Foundry SDK, evaluate their performance with manual testing and playground tools, and build effective AI applications through hands-on comparisons and guided demos.
In this exam preparation module, learn effective preparation strategies for the certification exam, including sample questions and study tips.
Take this assessment to validate your skills gathered from the self-paced online learning course completed in this course to mark your completion.
Intermediate
Beginner
Intermediate
Beginner
No. of
Learners - 0
Last Updated Sep 2025