AI courses for modern practice

The course focuses on teaching production-level deployment of LLM applications especially enterprise-grade deployment of RAG pipelines.

Learn techniques that can take your RAG system from an interesting proof-of-concept to a serious asset.

Build a simple Python extension with this introductory course.

Learn how NIM enables the building, deploying, and scaling of AI applications.

Learn how to build a variety of LLM-based applications through the use of modern prompt engineering techniques.

Just like how humans have multiple senses to perceive the world around them, computers have a variety of sensors to help perceive the human world.

Build foundational skills in robotics simulation and control with Isaac Sim, the first step in the Isaac Sim Learning Path.

Learn how to use two powerful NVIDIA developer tools: Nsight Systems and Nsight Compute.

Get started quickly in developing LLM-based applications by exploring the open-sourced ecosystem including pretrained LLMs.

Retrieval-Augmented Generation (RAG) pipelines are revolutionizing enterprise operations.

Learn how to write, compile, and run GPU-accelerated code, leverage CUDA core libraries to harness the power of massive parallelism provided by modern GPU accelerators, optimize memory migration between CPU and GPU, and implement your own algorithms.

Data science is about using scientific methods, processes, algorithms, and systems to analyze and extract insights from data.