Data Science
Applied data science, analytics, and experimentation workflows.
Fundamentals of Deep Learning
NVIDIA DLI
Businesses worldwide are using artificial intelligence to solve their greatest challenges.
Learn how to identify anomalies and failures in time series data, estimate the remaining useful life of the corresponding parts, and use this information to map anomalies to failure conditions.
Applications of AI for Anomaly Detection
NVIDIA DLI
Whether your organization needs to monitor cybersecurity threats, fraudulent financial transactions, product defects, or equipment health, artificial intelligence can help catch data abnormalities before they impact your business.
Deploy a deep learning model to automate disaster management use cases.
Building Real-Time Video AI Applications
NVIDIA DLI
Learn the skills you need to enable real-time transformation of raw video data from widely-deployed camera sensors into deep learning-based insights.
Building A Brain in 10 Minutes
NVIDIA DLI
The notebook explores the biological inspiration for early neural networks.
Introduction to Graph Neural Networks
NVIDIA DLI
Learn the basic concepts, implementations, and applications of graph neural networks (GNN) with hands-on interactive activities so that you can get started using GNN as a graph analysis tool.
Organizations analyze large amounts of tabular data to uncover insights, improve products and services, and achieve efficiency.
Exploring Adversarial Machine Learning
NVIDIA DLI
In this course, which is designed to be accessible to both data scientists and security practitioners, you'll explore the security risks and vulnerabilities that adopting machine learning might expose you to.
Fundamentals of Accelerated Data Science
NVIDIA DLI
Data science is about using scientific methods, processes, algorithms, and systems to analyze and extract insights from data.
Data science is about using scientific methods, processes, algorithms, and systems to analyze and extract insights from data.
Learn how foundation models can reveal novel biological insights, while leveraging NVIDIA’s platform to accelerate the entire workflow for fast, scalable results.
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 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.
Learn how to optimize vector database workloads on the GPU.
Paid live cohort from Maven covering machine learning and generative AI, sourced from Machine Learning for Engineers.
Paid live cohort from Maven covering generative AI and data and analytics, sourced from AI for Product Managers.
Paid live cohort from Maven covering agentic AI and generative AI, sourced from AI for Designers, Agentic AI for Product Managers.
Paid live cohort from Maven covering agentic AI and generative AI, sourced from Agentic AI for Engineers, AI Coding for Engineers.
Paid live cohort from Maven covering LLM systems and generative AI, sourced from AI for Product Managers.
Paid live cohort from Maven covering data and analytics and machine learning, sourced from AI for Designers, AI for Product Managers.
Paid live cohort from Maven covering machine learning and generative AI, sourced from Machine Learning for Engineers.
Paid live cohort from Maven covering AI evaluation and generative AI, sourced from AI for Product Managers, AI Evals for Product Managers.