GPU Programming provided by Coursera is a comprehensive online course, which lasts for 22 weeks long, 4 hours a week. GPU Programming is taught by Chancellor Thomas Pascale. Upon completion of the course, you can receive an e-certificate from Coursera. The course is taught in Englishand is Paid Course. Visit the course page at Coursera for detailed price information.
22 weeks long, 4 hours a week
30th, Oct 2022
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.
Course 1: Introduction to Concurrent Programming with GPUs
- Offered by Johns Hopkins University. This course will help prepare students for developing code that can process large amounts of data in ... Enroll for free.
Course 2: Introduction to Parallel Programming with CUDA
- Offered by Johns Hopkins University. This course will help prepare students for developing code that can process large amounts of data in ... Enroll for free.
Course 3: CUDA at Scale for the Enterprise
- Offered by Johns Hopkins University. This course will aid in students in learning in concepts that scale the use of GPUs and the CPUs that ... Enroll for free.
Course 4: CUDA Advanced Libraries
- Offered by Johns Hopkins University. This course will complete the GPU specialization, focusing on the leading libraries distributed as part ... Enroll for free.
