Planning and Scoping Generative AI Projects

Successful generative AI implementation requires a clear strategy that balances technical capabilities with practical business needs. This course provides a structured approach to planning AI initiatives, ensuring you understand both the potential and the pitfalls of this evolving technology. You will transition from basic awareness to being able to architect a project plan that addresses data requirements, model selection, and ethical considerations. By focusing on the foundational logic behind AI systems, you will learn how to lead projects that are both innovative and sustainable. What you'll learn: - Understand fundamental terminology and the technical foundations of Large Language Models. - Evaluate project feasibility by assessing technical risks, costs, and potential business impact. - Explore modern architectural patterns like Retrieval-Augmented Generation (RAG) to improve output accuracy. - Develop a project lifecycle that covers data preparation, prompt engineering, and model evaluation. - Apply ethical frameworks to mitigate risks related to bias, security, and model hallucinations. - Define measurable success metrics to track the performance and ROI of AI solutions. The course begins with essential definitions and core concepts before moving into the practical stages of project discovery, design, and risk management. This text-based program is built for beginners, project managers, and business leaders, with no prior technical background or programming experience required. Prepare your organization for the future of AI with a solid project foundation.