Graduate AI and Data Science
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Edge Intelligence / Edge AI
A new course connecting local AI deployment, sensors, microcontrollers, model training, system constraints, and socially meaningful applications.
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Artificial Intelligence Systems
Project-based design and evaluation of intelligent systems with emphasis on systems thinking, deployment, professional context, and responsible decision-making.
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Applied Deep Learning
A rapidly updated deep-learning course using tiered laboratories and multiple entry points into advanced architectures and emerging methods.
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Applied Machine Learning
Applied model selection, evaluation, interpretation, and communication within the graduate data science pathway.
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Applied Machine Learning II
An advanced, applied course designed from the ground up around rigor, accessibility, reusable resources, and authentic model development.
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Mathematical Foundations for Data Science II
A mathematically rigorous and practically grounded course built around original modular references, worked examples, and transfer to AI systems.