NVIDIA Learning Paths

NVIDIA Learning Paths bring together training, certification, and developer resources to help you build practical skills in AI, accelerated computing, and graphics.

Training and Certification Learning Paths

NVIDIA’s learning paths are structured, role-based development routes that guide learners from foundational knowledge to advanced technical mastery across AI, accelerated computing, and infrastructure deployment. Each path is designed to build skills progressively through a combination of coursework, hands-on labs, and practical assessments—culminating in industry-recognized certification opportunities.

Ansys, Siemens Gamesa

Accelerated Computing

Develop the skills to harness GPUs for high-performance computing, covering parallel programming, optimization, and efficient deployment.

Accelerated Data Science

Discover how to speed up your workflows using popular Python libraries and essential tools.

Deep Learning

Discover how to speed up your workflows using popular Python libraries and essential tools. Prepare for NVIDIA certification.

DGX Platform and Data Center

Empower your enterprise team with NVIDIA DGX™ administration training to quickly harness the full capabilities of NVIDIA's leading platform for AI development.

Generative AI and LLMs

Elevate your technical skills and earn NVIDIA certification in generative AI and large language models.

Industrial Digital Twins

Get started with essential foundation in developing OpenUSD-based digital twin applications and workflows for the era of physical AI.

Robotics Fundamentals

Start your robotics with essential foundations in simulation, Robot Operating System (ROS), and robot learning.

Universal Scene Description (OpenUSD)

Learn to harness the full potential of OpenUSD to accelerate your 3D workflow with these free courses.

Project Learning Paths

Build real-world applications with paths that guide you from learning core concepts to creating a functional project. Project learning paths will get you started quickly in a hands-on development environment.

How to Build an AI Agent

Learn about the foundational concepts of AI agents and build one yourself using NVIDIA Nemotron™ open-source models.

How to Build an Agentic RAG Application

Learn about RAG AI agents and create your own with NVIDIA Nemotron.

Deploy Faster Generative AI Models With NVIDIA NIM on GKE

Deploy pre-built NVIDIA NIM™ microservices for inference tasks on Google Kubernetes Engine and streamline AI model deployment. Created in partnership with Google Cloud.

Speed Up Data Analytics on GPUs

Learn how to accelerate analytics for large data sets on Google Cloud by tapping into NVIDIA GPUs—no code changes required. Created in partnership with Google Cloud.

Intro to Inference: How to Run AI Models on a GPU

Get started with the inference pipeline, model formats, and performance metrics. Created in partnership with Google Cloud. 

Quick Start to Quantum Computing with CUDA-Q

Learn to build hybrid quantum-classical applications by programming a variational algorithm yourself using the open-source NVIDIA CUDA-Q platform. 

Take the Next Steps

Get Certified

Certification from NVIDIA can be a key step in advancing your career. It validates your expertise, showcases your skills, and highlights your commitment to continuous improvement.

Elevate your career and make an impact with an NVIDIA certification.

Team and Individual Training

Whether you aim to acquire specific skills for your projects and teams, keep pace with technology in your field, or advance your career, NVIDIA Training can help you take your skills to the next level.

Contact us if you have questions about training, whether it’s for yourself or your team.

Stay Informed

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