Certification
Certification: CUDA Programming for High-Performance GPU Computing
Upgrade your CV with recognized expertise in CUDA programming. Master GPU computing techniques to accelerate AI, data science, and engineering workflows—demonstrating your ability to tackle complex, high-performance computing challenges.
The exam
Take the certification exam
Multiple-choice questions about the course. Pass with 70% or more and your certificate is issued at once, with a public page and an "Add to LinkedIn" button.
What the exam covers
2 questions from each of the 12 chapters of the course
20 multiple-choice questions, drawn fresh for every attempt. Pass with 70% or more.
- 01Intro16:52
- 02Deep learning ecosystem20:51
- 03CUDA setup9:20
- 04C/C++ review48:44
- 05Intro to GPUs15:53
- 06Writing your first kernels123:46
- 07The CUDA API99:56
- 08Faster matrix multiplication167:14
- 09Triton42:07
- 10PyTorch extensions13:27
- 11MNIST MLP project143:03
- 12Next steps and outro13:58
The Certification: CUDA Programming for High-Performance GPU Computing is designed for professionals seeking to master GPU programming using CUDA. Gain skills such as improved decision-making, increased productivity, and a future-proof career by learning advanced memory management, optimization, and performance profiling techniques. Enroll today to set yourself apart in high-performance computing and accelerate your professional growth.
This certification covers the following topics:
- GPU Architecture and Terminology
- CUDA Specific Memory Allocation and Data Transfer
- Kernel Indexing
- Matrix Multiplication: Naive and Optimized Kernels
- CUDA Streams for Asynchronous Execution
- cuBLAS LT for High-Performance Matrix Multiplication
- Atomic Operations for Thread Safety
- Kernel Fusion for Performance Optimization
- Tensor Cores for Accelerated Matrix Multiplication
- Profiling with NVIDIA Nsight Compute
- PyTorch Integration with Torch CUDA Extensions