Azure Machine Learning & Responsible AI – Developer Concepts Explained is a concise and practical learning guide designed to help developers understand the core building blocks of Azure Machine Learning and modern AI development practices. The course begins by introducing Responsible AI, explaining how Microsoft ensures fairness, transparency, and ethical decision-making in AI systems. Learners will also explore data labeling in Azure Machine Learning, which is essential for preparing high-quality datasets used to train accurate models. The course covers Azure Machine Learning CLI v2, showing how developers can build, manage, and collaborate on machine learning projects efficiently using command-line tools. It also explains the supported frameworks in Azure ML, helping learners understand how popular libraries and tools integrate into the platform. In addition, the course introduces Automated Machine Learning (AutoML), which simplifies model creation by automatically selecting the best algorithms and parameters. Learners will also discover managed endpoints, which allow easy deployment and scaling of machine learning models in production environments. Another key topic is how Visual Studio Code supports Azure Machine Learning workflows, making development more efficient and integrated. This course is ideal for developers and data science beginners who want to understand real-world Azure ML tools and workflows. By the end, learners will have a clear understanding of Azure ML capabilities and responsible AI principles.