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Accelerated Data Science in the Classroom: Teaching Analytics and Machine Learning with RAPIDS
Polo Chau , The Georgia Institute of Technology | Haekyu Park, The Georgia Institute of Technology
The demand for accelerated data-science skill sets among new graduate students grows rapidly as the computational demands for data analytics applications soar. This session introduces a novel yet reproducible approach to teaching data-science topics in a graduate data science course at the Georgia Institute of Technology, taught by Professor Polo Chau. Haekyu Park, a computer science Ph.D. student and teaching assistant of the course, will co-present key pedagogical considerations and solutions that help students learn GPU-accelerated data science and analytics using the open-source RAPIDS framework. For example, we present a hybrid, flexible approach for students to learn, where they can choose to experiment with RAPIDS using a local NVIDIA DGX-1 system, or the cloud, or both.