Coursera - GPU Programming Specialization

[LeeAndro]

Last updated 12/2022MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChGenre: eLearning | Language: English + srt | Duration: 122 Lessons (9h 45m) | Size: 1.7 GB

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.

Machine Learning
GPU
Parallel Computing
Image Processing
C
Cuda
Python Programming
Thread (Computing)
Algorithms
C/C
Nvidia
Data Science

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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 perfog numerous computations in parallel and rapidly. Applications for these skills are machine learning, image/audio signal processing, and data processing.

Learners will complete at least 2 projects that allow them the freedom to explore CUDA-based solutions to image/signal processing, as well as a topic of choosing, which can come from their current or future professional career. They will also create short demonstrations of their efforts and share their code.

HomePage:

https://www.coursera.org/specializations/gpu-programming

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