GPU Programming Specialization
Master GPU programming with CUDA for high-performance computing: parallel programming, enterprise solutions, and advanced libraries to solve complex challenges.
Master GPU programming with CUDA for high-performance computing: parallel programming, enterprise solutions, and advanced libraries to solve complex challenges.
This comprehensive specialization teaches software developers and data scientists how to create high-performance applications using GPU computing. Through four detailed courses, students learn concurrent programming, CUDA framework implementation, enterprise-scale solutions, and advanced libraries. The program focuses on practical applications in machine learning, image processing, and data analysis, with hands-on projects using Nvidia GPUs. Designed for those with programming experience, it provides essential skills for developing efficient parallel computing solutions.
3.1
(24 ratings)
9,053 already enrolled
English
Powered by
What you'll learn
Master CUDA programming for parallel computing. Develop efficient GPU-accelerated applications. Implement enterprise-scale GPU solutions. Utilize advanced CUDA libraries for complex computations. Create machine learning applications using neural network libraries. Optimize parallel algorithms for maximum performance. Design scalable solutions for large-scale data processing.
Skills you'll gain
This course includes:
93 Hours PreRecorded video
2 projects
Access on Mobile, Desktop
FullTime access
Shareable certificate
Closed caption
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
Created by
Provided by
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 4 courses in this program
Introduction to Concurrent Programming with GPUs
Course 1 · 19 Hours to complete · 5 modules
Introduction to Parallel Programming with CUDA
Course 2 · 21 Hours to complete · 5 modules
CUDA at Scale for the Enterprise
Course 3 · 28 Hours to complete · 5 modules
CUDA Advanced Libraries
Course 4 · 25 Hours to complete · 5 modules
Fee Structure
Payment options
Financial Aid
Testimonials
Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.
Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.