This Azure Machine Learning One Dev Questions course is designed to provide quick, clear explanations of the most important concepts in Azure Machine Learning. It is ideal for developers and data scientists who want to strengthen their understanding of core ML services and advanced Azure ML capabilities.
Students will begin by learning what Azure Machine Learning is and how it supports end-to-end machine learning workflows in the cloud. The course then explores Azure Automated Machine Learning (AutoML), which simplifies model building by automatically selecting the best algorithms and parameters.
A key focus of the course is hyperparameter tuning, where learners discover how to automatically optimize model performance using Azure ML tools. The course also introduces responsible AI principles, explaining how Microsoft ensures fairness, transparency, and accountability in machine learning systems.
In addition, learners will explore data labeling workflows, Azure ML CLI v2 for improved collaboration and development efficiency, and managed endpoints for deploying models in production environments. The course also covers framework support in Azure ML and how tools like Visual Studio Code integrate with Azure ML workflows.
By the end of the course, learners will have a strong conceptual understanding of Azure Machine Learning features and how to apply them effectively in real-world AI and data science projects.
