This workshop is designed for developers, data scientists, and product teams interested in building AI systems that are not only powerful, but also responsible. You’ll walk through a real-world case study of developing a machine learning model — from dataset analysis and bias detection to explainability tools and post-deployment monitoring. Learn how to implement fairness checks, use interpretable models, and apply governance frameworks that align with ethical AI principles. Participants will leave with tools and templates they can use immediately in their own workflows.