In this module, you'll set the foundation for everything that follows. You'll understand why this course focuses on collaboration with AI rather than AI as a technology, and you'll learn what to expect: a lasting framework for working with AI systems instead of disposable tips and tricks. By the end, you'll have a clear picture of your learning journey and the outcomes you'll walk away with.

In this module, you'll learn the AI Fluency Framework, a durable structure for thinking about human-AI collaboration. You'll first understand why "fluency" is the right metaphor and how it differs from simple AI literacy. Then you'll learn the four core competencies (Delegation, Description, Discernment, Diligence) and how they map across the three modes of working with AI: Automation, Augmentation, and Agency.

In this module, you'll build a working mental model of generative AI. You'll learn what makes generative systems different from earlier AI, how concepts like context windows and emergent capabilities shape what's possible, and where today's models genuinely shine versus where they struggle, including knowledge cutoffs, hallucinations, and reasoning limits. You'll come away able to reason about AI behavior rather than treating it as a black box.

In this module, you'll develop the judgment to decide what work to do with AI versus independently. You'll learn to assess your goals, evaluate AI platform capabilities honestly, and distribute tasks strategically across yourself and the AI. You'll then put the skill into practice by scoping a real project and creating a delegation plan you'll execute throughout the rest of the course.

In this module, you'll learn how to translate your intent into prompts that work. You'll move beyond ad-hoc prompting to a structured approach built on three components: Product Description, Process Description, and Performance Description, which together create the collaborative environment you need. You'll see why the AI can't read your mind and how clearly articulating outputs, methods, and interaction style transforms the quality of what you get back.

In this module, you'll develop hands-on prompt engineering skills. You'll learn the six core techniques that make prompts reliably effective: providing context, showing examples, defining constraints, decomposing complex tasks, asking for reasoning first, and assigning a role or tone, plus the patterns experienced practitioners use to recognize when a prompt needs to be reworked. By the end, you'll have a practical toolkit you can apply to any AI interaction.

In this module, you'll learn to evaluate AI work thoughtfully rather than taking it at face value. You'll see how Discernment is the natural counterpart to Description: where Description shapes what goes in, Discernment shapes how you respond to what comes out. You'll learn to assess output quality, detect problems in the AI's reasoning, and recognize when its collaborative behavior needs to change.

In this module, you'll combine the two competencies you just built (Description and Discernment) into a working iterative cycle. You'll apply the loop to your own multi-step project, refining your prompts based on what you observe in the AI's responses and adjusting how the AI is behaving as the work unfolds. The exercise turns abstract framework into muscle memory.

In this module, you'll learn how to act responsibly when working with AI. You'll explore the ethical foundations of AI collaboration through three lenses: how you choose and engage with AI systems (Creation), how you communicate AI's role to others (Transparency), and how you take ownership of what you produce and share (Deployment). The module emphasizes that different contexts have different norms, and that meeting them is part of fluent AI use.

In this module, you'll bring the full course together and plan how you'll keep growing after it ends. You'll revisit the four core competencies and how they apply across Automation, Augmentation, and Agency. You'll also have the chance to work through additional self-directed activities such as competency self-assessments, personalized prompt libraries, and structured development plans, designed to make AI Fluency a lasting practice rather than a one-time course.