3 Best CUDA Courses [2021 JUNE] [UPDATED]

Best CUDA course tutorial class certification training online

CUDA is an advanced software tool that is ideally designed to perform parallel programming on GPUs. It gives the developers a competitive advantage over traditional methods. If you’re interested in learning about CUDA, we have compiled a list of some of the Best CUDA Classes, Tutorials, Courses, Training, and Certification programs available online. This list comprises all the essential study material with high-quality videos and hands-on projects to provide you the best learning experience. Besides, the courses are ideal for beginners, intermediates, as well as experts. Have a look at our compilation of Programming Language Courses.


3 Best CUDA Courses [2021 JUNE] [UPDATED]

1. CUDA Programming Masterclass with C++ (Udemy)

If you want to learn how CUDA helps perform parallel programming on GPUs, this course from Udemy is an appropriate choice. With this session, you’ll learn everything about CUDA, from the basic concepts to advance algorithm implementations. You’ll get  introduced to CUDA programming and the programming model that is used for parallel programming. The course consists of multiple learning modules that are focused on covering various aspects of CUDA. Besides, it is included with lots of programming exercises and quizzes offered to help you practice your skills.


Key USPs –

– Gain a detailed perspective of CUDA software and tools and how to install CUDA toolkit while having a look at the CUDA programming.

– Know about the basic workflow of parallel algorithm design and gain the ability to design and implement optimized parallel algorithms.

– Cover essential topics related to the CUDA execution model, such as resource partitioning, profile-driven optimization, parallel reduction, CUDA dynamic parallelism, etc.

– Enroll in the bonus video lecture focused on image processing with CUDA to help you learn about digital image processing.

– Discuss profiling techniques and some other CUDA tools, including NVVP, NvProf, CUDA Memcheck, and more.


Duration: 10-11 hours

Rating: 4.4 out of 5

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Review: This is an excellent course to start CUDA programming. Concepts are well explained both theoretically and with code. – Raj Prasanna.


2. Parallel Computing with CUDA (Plural Sight)

This is an entry-level course ideally designed for beginners who are just beginning with the CUDA parallel programming. Joining this learning session will show you how to get started with the CUDA platform and leverage NVIDIA GPUs power. The course is developed by Dmitri Nesteruk, who is a professional developer, podcaster, and technical evangelist. During the video lectures, the instructor will help you cover CUDA C’s basics while explaining the GPU architecture and presents solutions to some of the standard computational problems. Completing this session with given quizzes and assignments will provide you a certificate of completion to share with your resume and LinkedIn profile. Check out our list of Best Parallel Computing Courses.


Key USPs –

– An introductory course focused on teaching you about the history of CUDA, how it is helpful in parallel programming for GPUs, and more.

– Learn about the history of GPU computation, graphic processor architecture, using NSight, Profiling, and much more.

– Cover multiple essential topics related to CUDA, such as parallel programming patterns, atomic operations, types of memory, etc.

– Know about the types of memories used in parallel programming, such as global memory, constant and texture memory, shared memory, and local memory.


Duration: 4-5 hours

Rating: 4.5 out of 5

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3. Fundamentals of Accelerated Computing with CUDA C/C++ (NVIDIA Courses)

It’s always best to learn from the one who has developed the CUDA software. NVIDIA, a well-known name in the graphics market, offers multiple courses to help individuals learn about accelerated programming. This course is intended to teach you how the CUDA computing platform accelerates of CPU-only applications to run on the world’s fastest GPUs. Joining this program requires basic knowledge of the C/C++ language, familiarity with variable types, loops, functions, and manipulations. Apart from this program, you can enroll yourself in other related programs, including Accelerating CUDA C++ Applications, Scaling Workloads across Multiple GPUs with CUDA C++.


Key USPs –

– Learn how to utilize essential CUDA memory management techniques for optimizing accelerated applications.

– Learn to leverage command line and visual profiling that will guide you to check your work after completion.

– Learn to accelerate CPU-only applications to run their latent parallelism on GPUs while getting exposure to accelerated applications potential for concurrency.

– Be able to speed up and optimize existing C, C++ CPU applications with the CUDA tools and techniques.

– Gain an understanding of the iterative style of CUDA development to shipping accelerated applications quickly.


Duration: 8 hours

Rating: 4.4 out of 5

You can Sign up Here



The above courses will help you enough to begin with your CUDA journey. They are prepared by some of the best instructors in the industry with years of experience working with CUDA tools. So, take the opportunity to learn CUDA from your home.