
Dr. Jie Tao is an Associate Professor of Analytics in the Charles F. Dolan School of Business at Fairfield University. Dr. Tao's recent research interests include deep learning and natural language processing, as well as eXplainable AI. He published in prestigious Information Systems journals, such as ACM Transactions on Management Information Systems, IEEE Transactions on Engineering Management, and Information Systems Frontiers.
He also presented research articles at multiple international academic conferences and received the best paper award at Hawaii International Conference on System Sciences (HICSS-52’ 2020). Jie won the Robert E. Wall Award for his impactful research on using AI to detect and intervene mental health issues using AI. Dr. Tao also received the Association for Information Systems (AIS) ATLAS award for his services to AIS in 2013.
Dr. Tao is currently a certified instructor for the NVIDIA Deep Learning Institute. He served as the faculty advisor for one of the top 10 student teams in IBM WAGC 2016. He is also the founding director of the AI & Tech Institute at Fairfield Dolan.
AI from First Principles to Practice
Artificial intelligence is moving fast, but the principles behind it are simple enough to learn, test, and use. This course is about turning that simplicity into power. We ask what today’s models can and cannot do, and then we try it ourselves.
You will learn how to get models to answer, to argue, to draw, to sing, to film, to play. You will see where they shine, where they stumble, and how to chain them together into something sturdier than a single prompt. Each week is a mix of short talk, live build, and peer critique. By the end, you will have two things: a computational essay that tracks your thinking, and a working artifact that shows it. It might be a workflow, an agent, an app, a demo, a short film, a song. Whatever it is, it will be yours, and it will work.
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