NVIDIA DLI Teaching Kits

The NVIDIA Deep Learning Institue (DLI) Teaching Kits are complete course solutions for use by educators in a variety of academic disciplines that benefit from GPU-accelerated computing. Co-developed with leading university faculty, Teaching Kits provide full curriculum design coupled with ease-of-use. Educators can bridge academic theory with real-world application to empower next-generation innovators with critical AI skillsets.

Learn more about Teaching Kits by viewing the webinar Bringing GPU Computing to the Classroom.

The continually updated curriculum keeps coursework timely and relevant with the latest techniques and trends. NVIDIA Teaching Kits contain content such as:

  • Lecture slides
  • Lecture videos
  • Hands-on labs/coding projects/solutions
  • Online DLI courses with certification
  • e-books
  • GPU cloud resources

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Co-developed with Professor Yann LeCun and his team at New York University (NYU), the Deep Learning Institute (DLI) Teaching Kit covers introductory and advanced deep learning topics, including:

  • Introduction to Machine and Deep Learning
  • Applied Image Classification
  • Applied Object Detection
  • Convolutional Neural Networks
  • Applied Image Segmentation
  • Energy-based Learning
  • Unsupervised Learning
  • Generative Adversarial Networks
  • Recurrent Neural Networks
  • Natural Language Processing
  • And Many More!
  • Translated Russian version also available



Co-developed with Professor Wen-Mei Hwu and his team from University of Illinois (UIUC) and Professor Sunita Chandrasekaran and her team from University of Delaware, the Accelerated Computing Teaching Kit covers introductory and advanced accelerated parallel computing topics:

  • Introduction to CUDA C
  • Memory and Data Locality
  • Thread Execution Efficiency
  • Memory Access Performance
  • Parallel Computation Patterns
  • Efficient Host-Device Data Transfer
  • OpenACC, MPI, OpenCL
  • New! Unified Memory
  • New! Dynamic Parallelism
  • New! Multi-GPU Systems
  • New! CUDA Libray Usage
  • And Many More!
  • Translated Russian and Portuguese versions also available



Co-developed with Professor John Seng and his team, at California Polytechnic State University (CalPoly), the Robotics Teaching Kit with 'Jet' covers introductory and advanced multidisciplinary topics:

  • Intro. to Robotics and Jetson
  • ROS Robot O/S
  • Sensors
  • Computer Vision
  • Machine Learning
  • Dead Reckoning
  • Path Planning
  • And Many More!

An Exclusive Offer for Educators and Their Students

Qualified educators using Teaching Kits receive codes for free access to NVIDIA Deep Learning Institute (DLI) online, self-paced training for themselves and all of their students — a value of up to $90 per course per person. DLI content reinforces deep learning and accelerated computing concepts presented in the Teaching Kits and teaches students how to apply those concepts to end-to-end projects. Through built-in assessments, students can earn certificates that prove subject matter competency and can be leveraged for professional career growth. Each course presents a self-paced learning environment with access to a GPU-accelerated workstation in the cloud. All students need is a web browser and internet connection to get started. Although these courses are designed to be taken online, you are free to administer them to your students in a live setting as well. Information on how to request access for educators can be found inside the Teaching Kits upon approval.

Like to read more about these Teaching Kits or have questions? Checkout our Teaching Kit FAQ


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DLI Online and Instructor-led Courses

The NVIDIA Deep Learning Institute (DLI) offers hands-on training in AI and accelerated computing to solve real-world problems. Participants can earn certification to prove subject matter competency and support professional career growth.

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Getting Started with GPUs

Suggested labs, libraries, and reference materials for those new to GPU-accelerated computing.

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GPU Access and Development Tools

Recommended development tools, CUDA downloads, and other resources.

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Existing Course Material

Learn more about real university classes, labs, and MOOCs currently using GPUs.

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Training Material and Code Samples

Tutorials, seminars, training slides, and code samples that help teach an array of parallel programming concepts.

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