Build a practical foundation in responsible AI strategy by learning how generative AI works, when to use it, and how to apply it more thoughtfully in workplace settings. In this course, you’ll develop skills relevant to roles across business, operations, marketing, product, HR, and team leadership where employees are increasingly expected to use AI tools responsibly. You’ll explore core generative AI concepts, compare AI tools to other approaches for specific tasks, and examine the risks that can affect quality, trust, and compliance.

This is a non-traditional, skill-based learning experience organized around real workplace tasks instead of a fixed lecture sequence. It’s designed to reflect responsibilities you may see in job descriptions and day-to-day work, from choosing the right tool for a task to recognizing bias, privacy, security, and intellectual property concerns before using generative AI. You can personalize your path based on what you already know, focus on the skills you need most, and skip content when it’s not necessary. The course curates high-quality lessons from expert instructors, selecting the strongest content for each skill so you can build practical, career-relevant responsible AI experience. By the end, you’ll be able to explain key generative AI terminology, describe how these models learn from large datasets, evaluate when generative AI is or isn’t the right fit for a task, identify common responsible-use risks, and apply organizational AI-use guidelines to realistic workplace scenarios. This course is a strong fit if you want a practical introduction to generative AI and responsible workplace use, with no technical background required.

Build practical enterprise AI strategy skills that help you evaluate generative AI opportunities, align investments to business goals, and communicate clear direction to leadership. In this course, you’ll develop hands-on experience relevant to roles such as AI strategy manager, innovation lead, digital transformation leader, product leader, and business technology executive. You’ll work on connecting generative AI initiatives to enterprise priorities, assessing the value of AI applications for unstructured data, benchmarking competitive adoption, and shaping strategic recommendations that support responsible business growth.

This is a non-traditional, skill-based learning experience organized around real workplace tasks instead of a fixed lecture sequence. It’s designed to reflect responsibilities you may see in job descriptions, from defining an enterprise GenAI vision and prioritizing use cases to evaluating impact, presenting strategic imperatives to executives, and making sustainable, cost-aware investment decisions. You can personalize your path based on what you already know, focus on the skills you need most, and skip content when it’s not necessary. The course curates high-quality lessons from expert instructors, selecting the strongest content for each skill so you can build practical, career-relevant enterprise AI strategy experience. By the end, you’ll be able to formulate a generative AI strategy aligned to business objectives, translate emerging technology concepts into executive-ready recommendations, benchmark competitive GenAI adoption, prioritize enterprise use cases, define KPIs to measure business impact, and incorporate sustainability and cost-efficiency into AI investment decisions. This course is a strong fit if you already have experience with business strategy, digital transformation, innovation planning, or technology leadership.