Explainable AI (XAI) For Generative AI

In the rapidly evolving landscape of artificial intelligence, understanding how models arrive at specific outputs is crucial for ethical deployment and regulatory compliance. The "Explainable AI (XAI) For Generative AI" course, designed by renowned instructor Minerva Singh, serves as an essential guide for professionals aiming to demystify complex machine learning architectures. This comprehensive curriculum bridges the gap between raw Generative AI capabilities and actionable transparency. Learners will delve deep into the mechanics of popular tools like ChatGPT and Claude, mastering prompt engineering while laying the groundwork to build their own Large Language Model (LLM) based systems. Crucially, the course introduces cutting-edge XAI techniques to ensure that these generative systems remain fair, accountable, and trustworthy. Designed for data scientists, AI engineers, and business leaders, this curriculum ensures that participants can transition from deploying black-box algorithms to cultivating transparent, human-interpretable AI solutions. By prioritizing accountability, this course empowers tech professionals to confidently address biases and meet modern industry compliance standards.