Infatoshi/cuda-course resource

Health v2 · maintenance only

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3972 stars · 682 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A free open-source CUDA programming course published with FreeCodeCamp, teaching GPU kernel development from C/C++ basics through optimized matrix multiplication, Triton, and PyTorch CUDA extensions. It culminates in building an MLP for MNIST in raw CUDA and targets NVIDIA GPUs on Ubuntu Linux.

Use cases

• learn CUDA programming from scratch
• write and optimize GPU kernels for deep learning
• understand how llm.c-style projects work
• speed up matrix multiplication with CUDA
• write custom PyTorch CUDA extensions
• get started with Triton kernel development

When to choose

• you have an NVIDIA GPU and want a structured, hands-on path into GPU programming
• you know Python and want to learn kernel optimization for ML workloads
• you want free course material with a concrete final project

When to avoid

• you need AMD, Intel, or Apple GPU programming (course is NVIDIA/CUDA-specific)
• you want a production library rather than educational material
• you cannot access Linux, WSL, or Docker environments

Facets

learning-resource · maturity active

gpu-computing machine-learning developer-tools gpu-computing deep-learning tutorials education python cpp cuda triton pytorch kernel-optimization free-code-camp nvidia linux gpu

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markdown · JSON · MCP: product_card(name="Infatoshi/cuda-course")