Foundations of Azure AI

This unit introduces core concepts of artificial intelligence and Microsoft Azure AI workloads, covering cloud and client-server architectures, common AI scenarios (content moderation, personalization, knowledge mining), and the fundamentals of AI and machine learning models. It also establishes Responsible AI principles and practical considerations for data, model training, deployment, and evaluation to prepare learners for further hands-on units and certification study.

Learning Objectives

• Analyze core AI concepts and categorize Azure AI workload types (e.g., content moderation, personalization, knowledge mining, document intelligence) to select appropriate services for given scenarios
• Demonstrate understanding of cloud and client-server concepts by identifying Azure infrastructure elements and explaining how AI applications are deployed and managed in cloud environments
• Evaluate Responsible AI principles (fairness, reliability, safety, privacy, inclusiveness, transparency) and apply Azure responsible AI tools and practices to propose mitigation strategies for ethical and security risks
• Apply machine learning fundamentals by describing model types, data requirements, the training/validation/testing lifecycle, deployment options (pretrained vs. custom), and by designing a basic model training and evaluation plan that addresses overfitting and underfitting