Last Updated Sep 2025This course covers the essentials of machine learning and how to leverage Azure’s platform for building, deploying, and managing ML models. You’ll learn about creating and managing the end-to-end lifecycle of ML models using Azure Machine Learning Studio and Azure AI Studio. You will understand the implementation of Generative AI. You’ll explore advanced MLOps features for automating the ML lifecycle, GenAIOps and monitoring model performance.
Duration - 16 Hours
Level - Intermediate
Style - Self paced
Course Type - Project Ready with Labs
Certification - No
Hands on Labs - Yes
Solution Areas - Azure - Cloud & AI Platform, Innovate with Azure AI Apps and Agents
Learn the fundamentals of machine learning and Azure Machine Learning, including tools like the CLI, Python SDK v2, and AI Studio. Explore creating ML resources, managing data concepts, and working with datastores and connections. Gain insights into data preparation with Apache Spark and leverage the Managed Feature Store for enhanced ML workflows.
Master the end-to-end process of training, deploying, and monitoring machine learning models with Azure Machine Learning. Explore Automated Machine Learning (AutoML), MLflow integration, and the use of ML pipelines and components to streamline workflows and optimize model performance. Learn to deploy and monitor models efficiently, ensuring robust and scalable ML solutions.
Dive into advanced Azure Machine Learning features, including Model Catalog, Collections, and prompt flow for streamlined workflows. Explore Retrieval Augmented Generation and Vector Stores (preview) to enhance generative AI applications. Learn effective strategies for monitoring and optimizing models for robust AI solutions.
Master MLOps with Azure Machine Learning, including Git integration, Azure Pipelines, and GitHub Actions. Explore GenAIOps for LLM workflows, secure AI applications, and implement robust security and governance practices. Learn Responsible AI techniques, configure dashboards, and share insights with the Responsible AI scorecard (preview) for ethical and effective AI solutions.
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Intermediate
Beginner
No. of
Learners - 179
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