AI courses for modern practice

Accelerate your robotics innovation with this hands-on workshop focused on simulation-first development, AI-powered perception, and synthetic data generation using NVIDIA Isaac.

Learn to build custom Python analysis scripts using the Nsight Analysis System to programmatically identify and summarize application performance bottlenecks.

Learn how to build responsive, interactive dashboards for large datasets using GPU-accelerated Python libraries.

Learn how clustering algorithms like K-Means, DBSCAN, and HDBSCAN are used to uncover patterns in data and power real-world applications, while leveraging NVIDIA GPUS to accelerate the entire workflow for fast, scalable results.

Learn to tailor large language models for specialized domains by curating custom datasets, training new tokenizers, and applying techniques like domain-adaptive pretraining and supervised fine-tuning.

Learn how to assess and adapt Large Language Models for specialized enterprise tasks through systematic evaluation and parameter-efficient fine-tuning.

Learn how to integrate large language models (LLMs) with NVIDIA Inference Microservices (NIM) and cuGraph to create cutting-edge, graph-based AI solutions for handling complex, interconnected data.

Introducing reinforcement learning for robotics with Isaac Lab.

Going further with reinforcement learning for robotics with Isaac Lab.

Accelerate external aerodynamics simulations using NVIDIA's PhysicsNeMo library.

Learn to profile and optimize AI pipelines using NVIDIA Nsight Systems to identify and eliminate performance bottlenecks in GPU-accelerated applications.

This course provides a practical, end-to-end guide to building, training, and deploying autonomous medical robots using NVIDIA’s Isaac Sim and Isaac for Healthcare.