Best CUDA Programming Online Courses, Training with Certification-2022 Updated

CUDA is a parallel computing platform and programming model developed by Nvidia for general computing on its own GPUs. The students who are looking for the best CUDA programming courses, this is the correct platform for learning the course. CUDA has improved and broadened its scope over the years, more or less in lockstep with improved Nvidia GPUs. CUDA, GPUs have been adopted in many areas that need high floating-point computing performance. The CUDA Toolkit includes libraries, debugging and optimization tools, a compiler, documentation, and a runtime library to deploy your applications. Many no of CUDA programming courses available in the IT market, from them our expert’s panel handpicked some best CUDA programming courses for you which are listed below.

#1 CUDA programming Masterclass – Udemy

This CUDA programming Masterclass is the online learning course created by the instructor Kasun Liyanage and he is founder of intellect and  co founder at cpphive and also experienced Software engineer in industry with programming languages like java and C++. in this course you will learn about the parallel programming on GPUs from basic concepts to advance algorithm implementations with CUDA. The application programming interface model and parallel computing platform that helps the software engineers and software developers to enable the graphics processing unit is known as CUDA. in this course nearly 1k+ students are enrolled. This course is included with 11 hours on-demand video and 62 downloadable resources. 
Key points:

• In this course you will learn about the programming in CUDA and about the Basic workflow of parallel algorithm design and more about Parallel computing and Supercomputing.
• By taking this course you will gain knowledge on all Basic elements of CUDA program and also about the Organization of threads in a CUDA program like ,blockDim, blockIdx and gridDim.
• This course also teaches you about the Unique index calculation for 2D grid and about the topics like Sum array implementation, Memory transfer between device and host and also Device properties.
• In this course you will be taught with the topics like Warp divergence, Resource partitioning, Parallel reduction as synchronization, Performance comparison of reduction kernels, Profile driven optimization etc. 
• You will also cover the topics like CUDA asynchronous functions, CUDA streams, Stream synchronization, Floating point operations, Atomic functions and about parallel exclusive scan Parallel Compact algorithm etc.

Ratings: 4.1 out of 5.
You can Signup here <=> ClickHere

#2 Parallel Programming with CUDA – Udemy

The Parallel Programming with CUDA is the online learning course created by the Scientific Programmer and it helps you in learning about the use of scientific programming languages like  CUDA, Julia, MPI, OpenMP, Matlab, Octave, Bash, C++, Python Sed and AWK along with RegEx in processing scientific and real-world data. The application programming interface model and parallel computing platform that helps the software engineers and software developers to enable the graphics processing unit is known as CUDA. By taking this course you will gain knowledge on basics of GPU architecture. In this course nearly 2k+ students are enrolled. This course is included with 1.5 hours on-demand video and 2 downloadable resources. 
Key points:

• This course helps you in gaining knowledge on GPU programming with CUDA and more about  the basics of GPU architecture and how to write the programs in CUDA language with the help of  latest CUDA toolkit.
• By taking this course you will get to know about the topics like Heterogenous Computing, software layer of GPGPU, GPGPU Schema, and more about CUDA Blocks and Threads in 1D and 2D.
• In this course you will learn about CUDA Memory Hierarchy, documentation of CUDA Threads Programming and about the CUDA “Hello World!” code with some of the examples.
• You will also gain knowledge on CUDA variable addtion on the device, CUDA vector addtion, with N blocks and 1 Thread and, 1  Block and N threads and also N blocks and N threads.
• The instructor of this course teaches you about the topics like Source Code, Matrix Multiplication, Shared memory matrix muliplication and also about the variation between GPU and CPU code.

Ratings: 3.6 out of 5.
You can Signup here <=> ClickHere

#3 Introduction to GPU computing with CUDA – Udemy

This Introduction to GPU computing with CUDA online learning course is created by the Orange Owl which is a consultant service that works on developing software for solving challenging technical computing problems in industrial or  scientific areas with 10+ years of experience. This course teaches you about what exactly is coalescence means, Halo region, and also about shared memory and you will be taught with the basics of Parallel Computing with CUDA. The application programming interface model and parallel computing platform that helps the software engineers and software developers to enable the graphics processing unit is known as CUDA. In this course nearly 400+ students are enrolled. This course is included with 2 hours on-demand video and 21 downloadable resources. 
Key points:

• By taking this course you will get to know about the basics of parallel programming on GPU and basics of GPU architecture and also about how to write simple programs using CUDA language.
• This course helps you in gaining knowledge on the topics like GPU Computing with CUDA, Threads Blocks Cores, Heterogeneous Computing, NVIDIA Compiler Driver and also about Streaming Multiprocessors.
• The instructor of this course teaches you about CUDA Parallelization Paradigms and also about Workflow of CUDA Program with the help of some related examples.
• You will also be taught with the process of Error Checking on Visual Studio or Eclipse projects to avoid compatibility issues and how to use instructions detailed in course for creating projects on  your own.
• In this course you will detailed with the topics like CUDA Memories, Coalesced Global Memory Accesses, Shared Memory and Adjacent Differences and also about Two Dimensional Grids.

Ratings: 3.2 out of 5. 
You can Signup here <=> ClickHere