In the EECS 6.5930 Hardware Architecture for Deep Learning course, students are introduced to designing and implementing hardware architectures related to the efficient processing of algorithms in AI systems. In this course, students are taught how to build systems using platforms and deep learning tools, and are provided with knowledge about analyzing hardware architectures. Students will also focus on open-ended design projects. Students participating in this course will learn about topics such as accelerators, support for complex networks, programmable platforms, co-optimization of algorithms and hardware, advanced technologies, and training.
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