Intro to Reinforcement Learning
A self taught course teaching the main techniques in modern RL.
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Artificial Intelligence
Intro to Deep Learning
Builds up on the foundations from Intro to AI by discussing
specific hands on approaches to topics like MLPs, CNNs, RNNs, GANs, and more.
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Intro to Aritifical Intelligence
Laid the foundations for understanding key formulations in the field of AI.
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Robotics
Human Centered Autonomy
A graduate course discussing the design of intelligent robots that can
operate safely in the real world among humans. Research skills are developed by critiquing papers,
debating, reviewing, and more.
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Intro to Robotics
A course covering the necessary fundamentals of modern modeling, perception, planning,
and control of robotics.
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Hardware / Software Systems
Computer Systems Engineering
Introduces students to the concepts central to the development of modern computing
systems. There is an emphasis on the systems software that controls interaction between devices
and other hardware/software with a final project developing an operating system.
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Digital Systems Laboratory
A project based course where students learn to design, build, and test
digital systems with transistor-transistor logic, SystemVerilog, & FPGAs.
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