NVIDIA

Adding New Knowledge to LLMs

This course provides a comprehensive, hands-on guide to the essential techniques for augmenting and customizing LLMs. This course takes you on a co...

Building Agentic AI applications with LLMs

Gain hands-on experience in designing agents that efficiently retrieve and refine information, intelligently route queries, and execute tasks concu...

Building AI Agents with Multimodal Models

Learn how to build neural network agents that reason across multiple data types using advanced fusion techniques, OCR, and NVIDIA AI Blueprints for...

Building Conversational AI Applications (BCAA)

Build and deploy a conversational AI pipeline including transcription, NLP, and speech. You'll explore automatic speech recognition (ASR) and text-...

Building LLM Applications with Prompt Engineering

Very large deep neural networks (DNNs), whether applied to natural language processing (e.g., GPT-3), computer vision (e.g., huge Vision Transforme...

Building RAG Agents with LLMs

This course will observe how you can deploy an agent system in practice and scale up your system to meet the demands of users and customers. Agent...

Building Transformer-Based Natural Language Processing Applications (BNLPA)

Businesses worldwide are using artificial intelligence to solve their greatest challenges. Healthcare professionals use AI to enable more accurate,...

Deploying RAG Pipelines for Production at Scale

Gain hands-on experience deploying, monitoring, and scaling RAG pipelines with the NIM Operator and learn best practices for infrastructure optimiz...

Fundamental of Accelerated Data Science

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

Fundamentals of Deep Learning (NV-FUND-DL)

Businesses worldwide are using artificial intelligence to solve their greatest challenges. Healthcare professionals use AI to enable more accurate,...

Generative AI with Diffusion Models (NV-GEN-AI-DM)

Take a deeper dive into denoising diffusion models, which are a popular choice for text-to-image pipelines. Thanks to improvements in computing pow...

Model Parallelism: Building and Deploying Large Neural Networks (NV-MP-DEPLOY-NETW)

Rapid Application Development Using Large Language Models (RADLLM)

Gain a strong understanding and practical knowledge of LLM application development by exploring the open-sourced ecosystem including pretrained LLM...