Learning Path

Accelerated Computing

Learn how to accelerate your applications and your career with the power of GPUs.

    Gain hands-on experience with the fundamentals of GPU-accelerated computing. This learning path introduces core concepts, tools, and techniques to speed up complex applications—from parallel programming basics to performance optimization—so you can unlock the full power of accelerated systems.

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    Choose the Training That Best Matches Your Needs

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    Foundational

    Self-Paced

    An Even Easier Introduction to CUDA

    Free
    1 Hour
    Self-Paced

    Getting Started With Accelerated Computing With Modern CUDA C/C++

    $90
    8 Hours
    Certificate available
    Also offered as an instructor-led workshop
    Self-Paced

    Fundamentals of Accelerated Computing With CUDA Python

    $90
    8 Hours
    Certificate available
    Also offered as an instructor-led workshop

    GPU Programming With the C++ Standard Library

    Self-Paced

    GPU Acceleration With the C++ Standard Library

    $30
    2 Hours
    Self-Paced

    Scaling GPU-Accelerated Applications With the C++ Standard Library

    $30
    2 Hours

    Profiling

    Self-Paced

    Optimizing CUDA ML Codes With NVIDIA Nsight Profiling Tools

    $30
    2 Hours
    Self-Paced

    Nsight Analysis System: Build Custom Python Analysis Scripts

    $30
    2 Hours
    Self-Paced

    Find the Bottleneck: Optimize AI Pipelines With Nsight Systems

    $30
    3 Hours

    Additional Resources

    Blog

    What Is Accelerated Computing?

    Blog

    Why Accelerated Data Processing Is Crucial for AI Innovation in Every Industry

    Blog

    CUDA Accelerated: NVIDIA Launches Array of New CUDA Libraries to Expand Accelerated Computing and Deliver Order-of-Magnitude Speedup to Science and Industrial Applications

    Interested in a particular topic? View our full set of learning paths to see the recommended sequence of courses to take across various topics.

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