CUDA Advanced Libraries
This course is part of GPU Programming Specialization.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full GPU Programming Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
2,124 already enrolled
Instructors:
English
Powered by
What you'll learn
Use cuFFT for signal and image processing
Implement linear algebra operations with cuBLAS
Develop data structures using Thrust library
Create neural networks with cuDNN and cuTensor
Build complete machine learning applications
Skills you'll gain
This course includes:
2.2 Hours PreRecorded video
1 peer review, 4 programming assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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 5 modules in this course
This advanced course focuses on mastering CUDA's high-performance libraries for complex computational tasks. Students learn to implement Fast Fourier Transforms with cuFFT, perform advanced linear algebra operations using cuBLAS and related libraries, utilize the Thrust library for efficient data structures, and develop machine learning applications with cuDNN and cuTensor. The curriculum culminates in a capstone project integrating multiple CUDA libraries.
Course Overview
Module 1 · 4 Hours to complete
cuFFT
Module 2 · 3 Hours to complete
CUDA Linear Algebra
Module 3 · 3 Hours to complete
The CUDA Thrust Library
Module 4 · 3 Hours to complete
CUDA Machine Learning
Module 5 · 9 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: GPU Programming Specialization
Instructor
Innovator in Computer Science Education
Chancellor Pascale has been a faculty member at Johns Hopkins University's Whiting School of Engineering for over 10 years, specializing in the Computer Science department. He earned his undergraduate degree in Computer Science from Drexel University and a Master’s degree from Johns Hopkins University. With over 15 years of experience in software and service development, he focuses on web applications, AI/ML for image and language translation, and network management. Chancellor Pascale was awarded the Fulbright-Nehru Fellowship, where he led a three-week workshop on Linux API development at Stella Maris College in Chennai, India.
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.