Welcome to Module 2! In this module, we’ll begin by discussing the importance of checking for approved AI tools or policies in the workplace, initial steps to start using AI tools, and the prerequisites and resources needed for using those tools. You’ll gain insights into common challenges but also best practices for overcoming them when adapting AI tools in a professional setting. We’ll discuss the distinction between creative and critical thinking tasks supported by GenAI, and identify practical applications of GenAI in both creative and analytical domains. We'll identify different prompting techniques, understand various prompting styles, and recognize when and how to apply each technique to different tasks. We have a lot to cover, so let's get started!

Welcome to Module 3! In this module we’ll focus on critical and creative thinking with GenAI. You’ll review a series of demos on how to use GenAI, and discuss scenarios of different types of knowledge workers and how they might use these tools. You’ll identify how certain tasks can integrate both creative and critical approaches using GenAI tools. We’ll then evaluate initial challenges of adopting AI tools by exploring practical strategies and examples and build a framework to identify and select appropriate AI tools based on the task’s creative or analytical nature. Finally, you’ll recognize the relevance of GenAI tools in the context of knowledge work and foster a mindset of experimentation and exploration with those tools for specific needs. Let’s get started!

Welcome to the final module! In this module, we have some important topics to discuss regarding safety considerations when using AI and expanding your learning. We’ll explore key limitations and challenges of AI. You’ll learn how to use AI ethically and safely, and we’ll discuss practical concerns related to current AI models and their applications. You’ll comprehend the implications of AI’s lack of transparency and explainability then identify privacy and security risks associated with sensitive data in AI. We’ll discuss sources and manifestations of bias in AI systems and assess strategies to identify, report, and address algorithmic bias and explore methods to promote ethical considerations, fairness, and inclusivity in AI. We’ll then assess improvements made in AI training to reduce hallucinations. You’ll also learn about explainability in AI and its importance in decision-making processes. Finally, we’ll explore the future of work and methods for adapting to AI advancements and find reliable sources of information about AI tools and updates.