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Join the NVIDIA Developer Program and take one of the complimentary technical self-paced courses below (worth up to $90).


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8 hours

Generative AI with Diffusion Models

Take a deeper dive into denoising diffusion models, which are a popular choice for text-to-image pipelines, with applications in creative content generation, data augmentation, simulation and planning, anomaly detection, drug discovery, personalized recommendations, and more.


3 hours

Synthetic Data Generation for Training Computer Vision Models

Learn how to use synthetic data in cases where data collection is a challenge. NVIDIA Omniverse Replicator streamlines synthetic data generation (SDG) using 3D assets into a single application and offers the ability to modify the appearance and format of the data.


8 hours

Fundamentals of Accelerated Computing With Python

Explore how to use Numba—the just-in-time, type-specializing Python function compiler—to create and launch CUDA® kernels to accelerate Python programs on massively parallel NVIDIA GPUs.

8 hours

Getting Started with Accelerated Computing in Modern CUDA C++

Learn how to accelerate and optimize existing C/C++ CPU-only applications to apply the power of GPUs using the most essential CUDA techniques and the NVIDIA Nsight™ Systems profiler.

2 hours

Optimizing CUDA Machine Learning Codes With Nsight Profiling Tools

Check out NVIDIA Developer Tools, a collection of applications that span desktop and mobile targets and enable developers to build, debug, profile, and develop cutting-edge software using the latest visual computing hardware from NVIDIA. In this course, you’ll learn the effective use of two powerful NVIDIA developer tools: Nsight Systems and Nsight Compute.

2 hours

GPU Acceleration with the C++ Standard Library

Learn to write simple, portable, parallel-first applications using only standard C++ language features that can be compiled without modification to take advantage of NVIDIA GPU-accelerated environments.


6 hours

Accelerating End-to-End Data Science Workflows

Explore how to perform multiple analysis tasks on large datasets using NVIDIA RAPIDS™, a collection of data science libraries that allows end-to-end GPU acceleration for data science workflows.

2 hours

RAPIDS Accelerator for Apache Spark

Get a walk-through of the RAPIDS Accelerator for Apache Spark, including running SQL queries on CPU and GPU in Spark and diving into the toolset that helps enable success.

4 hours

Exploring Adversarial Machine Learning

Learn how to deploy your own machine learning models on a GPU server.


8 hours

Getting Started With Deep Learning

Explore the fundamentals of deep learning by training neural networks and using results to improve performance and capabilities.

2 hours

Introduction to Graph Neural Networks

Learn the basic concepts, models, and applications of graph neural networks.

4 hours

Deploying a Model for Inference at Production Scale

Learn how to deploy your own machine learning models on a GPU server.

2 hours

Get Started With Highly Accurate Custom ASR for Speech AI

Learn to build, train, fine-tune, and deploy a GPU-accelerated automatic speech recognition (ASR) service with NVIDIA® Riva that includes customized features.

Expand Your Knowledge and Sharpen Your Skills

The NVIDIA Developer Program connects you with the best resources to do your life’s work. Join now and receive exclusive access to free tools, extensive learning opportunities, and expert help.


Developer Resources Non-Member Access Developer Program Community Access
Tools & Technology
NVIDIA NIM™ and NVIDIA Omniverse™ for research, development, and testing.
CUDA Toolkit
Early Access Programs  
Academic Grant Programs*  
Deep Learning Institute (DLI)  
On-Demand Limited Access
Developer Videos and Webinars Limited Access
GPU Technology Conference (GTC)
Developer Newsletter General Access Personalized Content
Developer Forums Read-Only Expert Help, Recognition, and Networking Opportunities
Exclusive Developer Events    
Technical Blogs Read-Only
Hardware & Product Documentation
Research Papers
White Papers & Technical How-Tos
NVIDIA GPU Cloud [NGC] Catalog

* Academic grants available for qualified researchers

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