What you’ll learn

  • Develop CUDA software for running massive computations on commonly available hardware
  • Utilize libraries that bring well-known algorithms to software without need to redevelop existing capabilities
  • Students will learn how to develop concurrent software in Python and C/C++ programming languages.
  • Students will gain an introductory level of understanding of GPU hardware and software architectures.

Description

This specialization is intended for data scientists and software developers to create software that uses commonly available hardware. Students will be introduced to CUDA and libraries that allow for performing numerous computations in parallel and rapidly. Applications for these skills are machine learning, image/audio signal processing, and data processing.

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