Explore more training options offered by the NVIDIA Deep Learning Institute (DLI). Choose from an extensive catalog of self-paced, online courses or instructor-led virtual workshops to help you develop key skills in AI, HPC, graphics & simulation, and more.Ready to validate your skills? Get NVIDIA …

Explore more training options offered by the NVIDIA Deep Learning Institute (DLI). Choose from an extensive catalog of self-paced, online courses or instructor-led virtual workshops to help you develop key skills in AI, HPC, graphics & simulation, and more.Ready to validate your skills? Get NVIDIA …

Explore more training options offered by the NVIDIA Deep Learning Institute (DLI). Choose from an extensive catalog of self-paced, online courses or instructor-led virtual workshops to help you develop key skills in AI, HPC, graphics & simulation, and more.Ready to validate your skills? Get NVIDIA …

In this hands-on lab, learn how to take advantage of Universal Scene Description (OpenUSD) to accelerate your Extended Reality (XR) development and enhance visual fidelity like never before. This session will equip you with the skills and tools necessary to build, customize, and stream your own …

High-fidelity simulations in science and engineering are computationally expensive and time-prohibitive for quick iterative use cases, from design analysis to optimization. NVIDIA Modulus, the physics machine learning platform, turbocharges such use cases by building physics-based deep learning …

Learn how to get started with AI-assisted annotation using MONAI Label. MONAI Label is an open-source image labeling and learning tool that allows researchers to create novel AI models and collaborate with a clinical team. You’ll get a short introduction to MONAI Label and then dive deep into creating your …

Graph neural networks (GNNs) are an increasingly popular class of artificial neural networks designed to process data that can be represented as graphs. The two prominent GNN frameworks are the Deep Graph Library (DGL) and PyTorch Geometric (PyG). The RAPIDS cuGraph effort has been working on …

Vision transformers (ViTs) are taking computer vision by storm, offering incredible accuracy and robust solutions for countless industries. However, there are many practical challenges to deploying ViTs, including pre-training, fine tuning, deploying, and managing the complexity of such a large model. …

The new wave of interest in large language models (LLMs) brought vector databases to the forefront of technologies for AI applications. We'll clearly need accurate and performant query results from vector databases to meet an ever-growing demand for data and sophisticated applications, which is where …

The growth in AI is driving the need for substantial compute infrastructure in data centers to train and deploy models. The right cluster management tools are critical for managing this infrastructure at scale and ensuring its optimal utilization. This lab will introduce the NVIDIA Base Command Manager …

Learn how to use NVIDIA AI Workbench as the focal point in generative AI workflows. We'll explain how other elements of NVIDIA AI Enterprise interoperate with AI Workbench. Within an AI workflow, we'll give a step-by-step example of how AI Workbench can be used to execute a project on a Lenovo …

Join AI experts to learn how to build a production-ready application that can reduce spear phishing — one of the largest and most costly cyberthreats to organizations. Customized for individuals and usually very convincing, spear phishing emails are difficult to defend against due to a lack of training…

To use insights from proprietary data and conversations with customers worldwide to build better products and serve customers, companies deploy large pre-trained language models and external retrieval and search mechanisms into their conversational applications such as chatbots, virtual …

Large language models (LLMs) have recently captured significant attention in healthcare. Their stellar performance across a range of applications highlights their potential for vital tasks like medical question-answering. However, LLMs can produce "hallucination" errors, generating overly confident …

Join us for this hands-on lab and learn how to harness the power of large language models (LLMs) and Jetson AGX Orin to build next-generation AI applications that can see, hear, and speak. You'll have the opportunity to work with LLMs in a real-world setting, fine-tuning and using them for tasks like image …

Join NVIDIA specialists for a hands-on lab where we'll introduce the basics of the Omniverse development platform. You'll learn how to get started building 3D applications and tools that deliver the functionality needed to support industrial use cases and workflows for aggregating and reviewing…

Kinetica, in partnership with NVIDIA, introduces a large language model engine that seamlessly translates natural language requests into SQL queries. Using the power of GPUs, their database offers advanced geospatial capabilities. You'll discover the magic behind creating an LLM for user-friendly …

First, we'll discuss what a large language model (LLM) is and list some of the strengths and weaknesses of these models, looking at a handful of models and approaches. We'll explain the difference between pre-training and fine-tuning. We'll discuss Input processing by showing the steps of taking an input …

Building vision AI applications for the edge often requires long, costly development cycles. A powerful new collection of NVIDIA Metropolis APIs and microservices helps you accelerate the development and deployment of vision AI applications on NVIDIA Jetson Orin. We'll dive deeper into these microservices…

Multimodal generative AI has recently seen significant advancements, enabling the creation of realistic images from textual or other inputs. Due to the complexity of these models, understanding how they function and how to apply them in practical settings can be challenging. We'll walk you through the …

Join us for an exciting introduction to foundation models in generative AI! In this training lab, we'll explore the basics of foundation models, their significance, applications, and the latest developments in the field of AI. Whether you're an academic, industry professional, or anyone eager to dive into the…

Retrieval-augmented generation (RAG) systems show great promise for business applications, but a naive approach simply pairing a vector database retriever with a general-purpose large language model (LLM) rarely leads to high-quality results. Learn techniques that can take your RAG system …

Autonomous mobile robots (AMRs) are a key element of industrial automation. Training AMRs in the real world is often a difficult, expensive process and prevents many from taking advantage of their tremendous potential. Combining remote control car platforms such as F1Tenth and JetRacer with …

Learn to take your ISO C++ application to the next level by using the C++ parallel algorithms to accelerate your code on GPUs and multicore CPUs. C++ is one of the most widely-used programming languages and provides a rich set of parallel building blocks for your application. Learn how to …

The RAPIDS Accelerator for Apache Spark leverages the distributed big data processing framework of Spark along with the power of GPUs to greatly speed up extract-transform-load and analytics workloads while reducing cost. In this training lab, we'll walk through the RAPIDS Accelerator for Apache Spark, …

Our introduction to the Isaac Robot Operating System will include: A hands-on tutorial showing how to use the Isaac ROS dev container; How to run Isaac ROS perception packages on Jetson; and A demo of how to test a robot in simulation with hardware in the loop, using Isaac SIM and Isaac ROS. …

Join AI experts to learn how to use the NVIDIA cuOpt cloud service to minimize vehicle routing inefficiencies by finding the most optimal routes for a heterogeneous fleet of vehicles making deliveries, pickups, dispatching jobs, and more. Bring your laptop to get access to the latest NVIDIA …

Get ready to master the art of steering AI towards accuracy in the medical domain. In this training lab, we’ll learn how to develop “guardrails” to ensure your AI stays on track and delivers trustworthy results. We’ll uncover how Nemo Guardrails can avert AI hallucinations by employing robust filters, …

In this training lab, you will learn the benefits of using reinforcement learning to train robot behaviors. Then you'll learn how to train robots quickly and easily with NVIDIA Isaac Sim in AWS Cloud. Finally, you'll learn to scale training for robots across multiple GPU nodes to expedite performance using AWS…

The demand for accelerated large language models (LLMs) has surged with the growing popularity of generative models. These models, often boasting billions of parameters, hold immense potential, but also pose challenges during large-scale deployments. Join us as we delve into the world of …

In a world where AI's evolution within the metaverse, digital twins, and simulations is accelerating, there is a widespread eagerness to learn how to navigate this rapidly advancing landscape. The technological landscape has transformed significantly since the initial introduction of Omniverse. Join …

Robotics applications have grown in popularity recently, with robots being used in industries including manufacturing, healthcare, and agriculture (among others) to increase production, quality, efficiency, and safety. And with the help of other technologies such as artificial intelligence, sensor technologies,…

Enterprises are increasingly seeking ways to automate their data management processes to save time and reduce manual labor. This training lab will focus on the practical use of multimodal Retrieval-Augmented Generation (RAG) agents to automate routine tasks involving databases such as MySQL, …

The potential clinical benefits of combining the power of mRNA expression with the rich context of tissue morphology are considerable. Equally impressive is the amount of data preparation and processing needed to perform this analysis. In the absence of well-established pipelines dedicated to …

Transformer-based large language models (LLMs) have revolutionized the ways to understand and explore massive datasets and enable us to generate and augment relevant data efficiently. Initially applied for natural language processing tasks, LLMs have extended applicability in understanding …

Retrieval augmented generation (RAG) pipelines are already changing every aspect of modern enterprise operation. There are countless online tutorials demonstrating proof-of-concept-level naïve RAG applications incapable of dealing with large volumes of traffic and large document volumes. This…

Create a synthetic version of a real-world object. Synthetic datasets help increase training and effectiveness of neural networks, but sometimes creating them to mimic the complex real world is difficult. Learn how to capture a complex physical object, filter the image capture for best results, …

In this hands-on lab, you’ll unlock the power of OpenUSD to build a real-time configurator in Omniverse. Along the way you’ll learn about workflows, asset considerations, and USD composition concepts that you can apply directly to your own development process. In the lab you’ll author a …

AI Industrial applications present unique challenges, including the need for near-perfect accuracy (99%+) and high throughput. These already demanding requirements are further complicated by the widespread issue of data scarcity in the industrial sector, attributed to factors such as data ownership…

Learn how NVIDIA's profiling tools, Nsight Systems and Nsight Compute, can help you accelerate modern compute workloads. In the first half of this lab, you'll get hands-on experience with optimizing CUDA applications using Nsight Systems, which is a system-wide performance analysis tool that …

In this introductory level training lab, we will cover the fundamentals of working with Universal Scene Description (OpenUSD) - an open and extensible ecosystem for describing, composing, simulating, and collaborating within 3D worlds. Learn how you can use USD for non-destructive workflows, how layers…

DeepVariant is one of the most popular variant callers in genomics right now. It uses image-based deep learning methods to predict mutations in a genome. DeepVariant comes with a pre-trained model out of the box that works very well across a wide set of scenarios, but it's possible to train new models for…

Synthetic data generation (SDG) is a data augmentation technique necessary for increasing the robustness of models by supplying additional data to train models. We'll explore the use of Transformers for synthetic tabular data generation in the context of credit card transactions. We'll use…

The goal of the vehicle routing problem (VRP) is to identify an optimal set of routes for a fleet of vehicles visiting multiple delivery locations. The changing economic and geopolitical scenario has made last-mile delivery one of the most challenging and expensive tasks of the logistics fulfillment cycle. In…

"How much data is enough?" is a common question when fine-tuning or training your own object detection models. In cases where data collection is a limiting factor, we can utilize synthetic generated data. Omniverse Replicator makes generating this 3D data streamlined in a single application, with …

Learn how to build and run an AI model while being aware of the AI medical project life cycle. You'll get a short introduction on the MONAI Deploy architecture, understanding how it's focused on defining the journey from research innovation to clinical production environments in hospitals. You'll walk through …

With the arrival of NVIDIA RTX and real-time ray tracing APIs like DXR and Vulkan Ray Tracing, it's now easier than ever to create stunning visuals at interactive frame rates. Learn how to utilize NVIDIA Nsight Graphics to profile and optimize 3D applications that use ray tracing. Using an example application, …

This hands-on training lab teaches how to accelerate HPC applications using the portable parallelism and concurrency features of the C++17 and newer standards, without any language or vendor extensions, such that a single version of the code is portable to multi-core CPU and to heterogeneous…

Transformer-based large language models (LLMs) have revolutionized the ways to understand and explore massive datasets and enable us efficiently generate and augment relevant data. Now, these transformer models have extended applicability in understanding languages of the molecules of life …

Gain experience with NVIDIA debugger and correctness tools by using CUDA-GDB and compute-sanitizer's functionalities on multiple small CUDA sample applications. Learn the basics of Nsight Visual Studio Code Edition and CUDA-GDB — how to build a project, how to start the debugger, detect and …

Learn the basics of working with digital humans in Omniverse Create as you embark on a journey to populate a virtual world. Omniverse Create provides cutting-edge capabilities for 3D content simulation and visualization, forming an important first step in the digital human creation pipeline. Learn about …

Learn how to get started with AI-assisted annotation using MONAI Label and OHIF or 3D Slicer as your image viewer, and walk through creating your own MONAI Label application. MONAI Label is an open-source image labeling and learning tool that allows researchers to create novel AI models and …

Write your first graph neural network, complete with automatic feature engineering, visualization, and deployment, in this lab using popular open source libraries: PyGraphistry[AI], NVIDIA RAPIDS (cuDF, cuGraph, cuML), and GPU neural network ecosystems (DGL, PyG, TF). Graph neural networks are in a…

Universal Scene Description (USD) is transforming 3D data modeling across various industries and is poised to be the open standard that enables the 3D evolution of the internet — the metaverse. In this hands-on training, we'll present what makes USD unique and the fundamentals for describing, …

During this training lab, you'll learn how to move video processing workflows to the GPU to benefit from hardware acceleration with the NVIDIA Video Codec SDK and NVIDIA DALI. We'll use JAX and PyTorch, but you'll be able to apply the techniques presented in a broad set of frameworks and technologies. …

Federated learning has emerged as a promising solution to the problem of data privacy and locality in training robust AI models. By enabling distributed model training without data sharing, federated learning allows researchers and data scientists to train generalizable models across diverse, …

Universities are at the forefront of nurturing the next generation in the emerging technologies of accelerated computing, data science, robotics and AI. NVIDIA Deep Learning Institute (DLI) Teaching Kits lower the barrier of incorporating AI and GPU computing in coursework with freely downloadable …

Session-based recommendation (SBR) has been an important task in online services like ecommerce and news portals, where users may have very distinct interests in different sessions. SBR models have been proposed to model the sequence of interactions within the current user session. They have …

DeepVariant is one of the most popular variant callers in genomics right now. It uses image-based deep learning methods to predict mutations in a genome. DeepVariant comes with a pre-trained model out of the box that works very well across a wide set of genomes; however, for more advanced …

Master NVIDIA's profiling tools for CUDA and AI workloads. After learning how to use Nsight Systems to identify and solve inefficiencies and scalability issues on the application level, you'll deep-dive into the challenges of tuning your CUDA kernels for maximum efficiency with Nsight Compute. Take a tour …

This hands-on training lab teaches how to accelerate HPC applications using the portable parallelism and concurrency features of the C++17 and newer standards, without any language or vendor extensions, such that a single version of the code is portable to multi-core CPUs and to …

Join Mark III, an NVIDIA Elite Partner, for an Introduction to machine learning (ML) tutorial and an interactive, practical lab on using ML techniques to see anomalies in sensor and machine data and predict when maintenance failures might occur. You'll receive access to a Jupyter Notebook guided …

NVIDIA Holoscan is a highly optimized platform for processing high-speed, low-latency streaming data generated by sensors at the edge. It can be used to build streaming AI pipelines for a variety of domains, including medical devices, high performance computing at the edge, industrial inspection, …

Learn about the basics of Omniverse and get started on your journey to generate realistic life-like simulations as a first step to creating your digital twin. Start to integrate our powerful and unique PhysX features into your workflow. Take it a step further and explore the magic of Omniverse Warp. …

In recent years, deep learning has shown impressive performance in medical imaging analysis. However, for a model to be useful in the real world, it needs to be reliable, besides being valid and interpretable. The uncertainty quantification (UQ) methods determine the calibrated level of a model'…

Learn about Auto3DSeg, a low-code framework for building 3D medical image segmentation models using MONAI. Researchers and data scientists need a common foundational framework to perform training experiments and compare against the state of the art. MONAI provides domain-specific …

This training introduces the book "Learning Deep Learning" (LDL) from NVIDIA Deep Learning Institute (DLI). "LDL" was published by Pearson in 2021 and teaches deep learning from scratch to people with a programming or computer science/engineering background. Without requiring any prior machine …

NVIDIA RAPIDS accelerates Python data science workflows from visualization and discovery to production inference. Its tremendous coverage across a wide range of important algorithms gives data scientists amazing superpowers. However, superheroes sometimes prefer to chart their own courses, …

Omniverse Replicator augments costly, laborious human-labeled real-world data, which can be error prone and incomplete, with the ability to create large and diverse physically accurate data tailored to the needs of autonomous vehicle and robotics developers. It also enables generating ground-truth …

Explore new techniques for building simulation tools with a focus on usability for the industrial end user. The industrial automation space is in desperate need of better simulation tools, but most people interacting with automation are simulation and programming novices. This highlights the need for …

Deep learning (DL) has shown impressive capabilities across various fields. However, the growing size of DL models is outpacing hardware capacity, resulting in a demand for large models to be trained and inferenced more efficiently and easily. We'll introduce a user-friendly DL system, Colossal-AI, that …

Training robots requires high-fidelity simulation. In addition, it requires a multitude of data extracted from a broad variety of scenes. Generating this training data can require considerable compute resources running simulations in parallel. In this session, get hands on experience running NVIDIA …

Create your own custom 3D workflow tools with NVIDIA Omniverse. By the end of this session you will have created a custom UI directly in the 3D scene. Use this for your bespoke scenarios such as annotations, data labeling, changing properties, showing alternate variations, visualizing related …

AI inference is continuing to become more prevalent in workstation applications. However, in most cases, the AI portion of what the user perceives to be the feature is only a small part of the overall pipeline. Learn how to ensure that the inference on the GPU is as optimal as it can be, and also the …

Feature engineering is an important component in (tabular) machine learning problems, which can be easily integrated into an existing model. The tabular data structure limits the models' capabilities to learn the relationships between features, and adding handcrafted features can significantly boost …

Despite the ever-increasing interest in applying deep learning (DL) models to medical imaging, the typical scarcity and imbalance of medical datasets can severely impact the performance of DL models. The generation of synthetic data that might be freely shared without compromising patient privacy is…

MONAI has established itself as the de facto platform for medical AI. Its origins are within radiology, but since the V1.0 release pathology has become an integral part of the platform. There is now a wealth of pathology-specific content in MONAI. Learn how to use this new content to analyze slides using state-…

Join us in this small, interactive session designed for business leaders who recognize the importance of AI and want to better understand terminology, concepts, and benefits. Through a combination of presentations and discussion, we'll address questions such as: What's possible with AI today? How …

New career opportunities are emerging in the development of shared virtual 3D worlds that are interactive, immersive, and collaborative. NVIDIA Omniverse paves the way for interconnected creativity in 3D, physically realistic, virtual worlds. In this presentation, we explore the latest …

Graph neural networks (GNNs) are models designed to perform inference on unstructured data described by graphs. For different segments and industries, GNNs find suitable applications such as molecular analysis, drug discovery and repurposing, predicting stock market developments, …

This tutorial introduces the Merlin framework which aims to make the development and deployment of recommender systems easier, providing methods for evaluating existing approaches, developing new ideas and deploying them to production. There are many techniques, such as different model …

In this workshop, you will learn how to run high fidelity robotic simulation with photo-realistic environments and highly accurate physics models. You will learn how to build a Docker image containing NVIDIA Isaac Sim, ROS, and other robotics application development and simulation tools …

Learn the basics of Omniverse Create and XR as you embark on a journey to creating a virtual world. Omniverse Create and Omniverse XR provide cutting edge capabilities for 3D content simulation and visualization, forming an important first step in the digital twin creation pipeline. In this course, you’ll…

GPU based audio processing has long been considered something of a unicorn in both the Pro Audio industry as well as the GPU industry. The potential for utilizing a GPU’s parallel architecture is both exciting and elusive, due to the number of computer science issues related to working with …

Learn how the physics and simulation features in Omniverse can simulate real-life physics and situations. Get a deep-dive look into Omniverse Create, its interface, and what PhysX is, as well as a peek at Machinima and that interface. Gain foundational knowledge of Create and how it’s relevant. …

Omniverse Replicator augments costly, laborious human-labeled real-world data, which can be error prone and incomplete, with the ability to create large and diverse physically accurate data tailored to the needs of AV and robotics developers. It also enables the generation of ground truth data that is …

Harnessing the incredible acceleration of NVIDIA GPUs is easier than ever. For over a decade NVIDIA has been collaborating in the C++ standard language committees on the adoption of features to enable parallel programming without the need for additional extensions or APIs. On account of this work, …

Learn how to use GPUs to deploy machine learning models to production scale with the Triton Inference Server. At scale machine learning models can interact with up to millions of users in a day. As usage grows, the cost of both money and engineering time can prevent models from reaching their full …

Modern quantum computing systems are noisy, remotely-hosted resources that have enabled experimentation but are currently incapable of application-specific quantum advantage. Research and development activities promise to considerably advance this situation, and we are starting to observe…

This training session introduces Sionna - NVIDIA’s new open-source software library for GPU-accelerated link-level simulations and 6G research. It enables the rapid prototyping of complex communication system architectures and provides native support for the integration of neural networks. In this …

Learn how to get started with AI-assisted Annotation using MONAI Label and OHIF or 3D Slicer as your image viewer and walk through creating your own MONAI label application. MONAI Label is an open-source image labeling and learning tool that allows researchers to create novel AI models and …

Learn how to build and run an AI model while being aware of the AI medical project life cycle. You’ll get a short introduction to the MONAI Deploy architecture, understanding how it’s focused on defining the journey from research innovation to clinical production environments in hospitals. You’ll walk through…

Attendees of the lab will gain experience with NVIDIA debugger and correctness tools by using CUDA-GDB and compute-sanitizer's functionalities on multiple small CUDA sample applications. In this workshop, you'll learn the basics of Nsight Visual Studio Code Edition and CUDA-GDB: how to build a …

With the arrival of NVIDIA RTX and realtime Ray Tracing APIs like DXR and Vulkan Ray Tracing, it's now easier than ever to create stunning visuals at interactive frame rates In this training, you'll learn how to utilize NVIDIA® Nsight™ Graphics to profile and optimize 3D Applications that are using Ray Tracing. …

Learn about designing, training, and evaluating domain-specialized health-care imaging AI models using MONAI. Researchers and data scientists need a common foundation to perform training experiments and compare against the state of the art. MONAI provides domain-specific …

Recent advances in combinatorial, computational, and synthetic chemistry have led to rapidly expanding accessible chemical space - including small molecular compounds suitable for drug discovery. Efficient exploration of such large-size chemical libraries can impact and expedite the …

Advances in the deep learning-based large language model (LLM) architectures have shown their impact on various complex tasks, including image and text processing, data generation, etc. Understanding the vast data related to biomolecules such as DNA, proteins, and drug-like chemicals …

If you have ever heard about InfiniBand you probably know it’s the pre-dominate network technology for AI and HPC deployments and now you have the chance to try it yourself. In this workshop you will have the opportunity to experience how simple it to operate and manage an InfiniBand fabric from an…

Parabricks is a GPU accelerated genomics software designed for secondary analysis. Compared to CPU based tools such as GATK, Parabricks is up to 80x faster for variant calling. This gives researchers the ability to run much more analysis on their data in a fraction of the time. In this workshop, we will …

Virtually all clinical and medical knowledge is contained in the rich free text information generated from research papers, physician notes in electronic medical records, lab notebooks and other areas that span across healthcare and life sciences applications. Extracting and structuring information from …

This training introduces the book "Learning Deep Learning" (LDL) from NVIDIA Deep Learning Institute (DLI). "LDL" was published by Pearson in 2021 and teaches deep learning from scratch to people with a programming or computer science/engineering background. Without requiring any prior machine …