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Overview
This GPU Programming Specialization is offered by Coursera in partnership with Johns Hopkins University. 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.
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
Skills you'll gain
- Machine Learning
- Python Programming
- Computer Programming
- Artificial Neural Networks
- C Programming Language Family
Programme Structure
Courses included:
- Introduction to Concurrent Programming with GPUs
- Introduction to Parallel Programming with CUDA
- CUDA at Scale for the Enterprise
- CUDA Advanced Libraries
Key information
Duration
- Part-time
- 2 months
- 10 hrs/week
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Campus Location
- Mountain View, United States
Disciplines
Computer Sciences Human Computer Interaction Web Technologies & Cloud Computing View 417 other Short Courses in Web Technologies & Cloud Computing in United StatesWhat students do after studying
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- Intermediate level
- At least 1 year of computer programming experience, preferrably with the C/C++ programming language.
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
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International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
Additional Details
- Coursera Plus: Subscribe to build job-ready skills from world-class institutions.
- $59/month, cancel anytime or $399/year with 14-day money-back guarantee
Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.
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