Foundations of Generative AI and Copilots

This unit introduces foundational concepts in artificial intelligence with emphasis on generative AI, Copilot-style assistants, and their practical applications. Students will learn core definitions, data and algorithm roles, machine/deep learning basics, prompt engineering, tool/provider evaluation, and initial workflow integration to prepare for deeper development and deployment in subsequent units.

Learning Objectives

• Analyze core AI concepts by distinguishing definitions of AI, the role of ubiquitous data, algorithms, standard hardware, and differences between machine learning and deep learning using real-world examples.
• Evaluate generative AI capabilities and limitations by comparing providers and account/version differences, assessing originality and academic/ethical considerations, and identifying tasks that AI cannot replace.
• Apply prompt engineering and Copilot techniques by creating, testing, and refining prompts and demonstrating use of Copilot features in Excel, PowerPoint, Teams, and GitHub Copilot to produce specified outputs.
• Demonstrate integration of AI into workflows by mapping desired outputs before prompting, selecting appropriate tools and plugins for use cases (e.g., marketing, localization, healthcare, finance), and outlining basic change-management strategies for adoption.