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Teaching Kits for Educators

Universities are at the forefront of nurturing the next generation in the emerging technologies of accelerated computing, data science, and AI. NVIDIA Deep Learning Institute (DLI) Teaching Kits lower the barrier of incorporating AI and GPU computing in coursework with downloadable teaching materials and online courses that provide the foundation for understanding and building hands-on expertise in these critical areas.

Enhancing Curricula with NVIDIA Teaching Kits

Watch Video (01:52)

Benefits for Educators

Removing Barriers to Teaching New Technologies

Saves Class and Lab Planning Time

Developing new teaching materials like lecture slides and hands-on labs can take a significant amount of time for busy faculty. Teaching Kits significantly cut course content development time for instructors.

Reduces Cost and Infrastructure Needs

New teaching materials and supplies cost money and create barriers to entry for students. Teaching Kits provide educators and their students access to GPUs in the cloud through free online courses.

NVIDIA co-develops Teaching Kits with academic partners

Addresses Academic Theory and Fundamentals

Many tech companies only provide applied industry and professional training material to universities, which lacks fundamentals and academic theory. NVIDIA co-develops Teaching Kits with academic partners to combine the latest industry trends, GPU architectures, and applications, with fundamental theory and pedagogy from academia.

Singular, Comprehensive Course Offering with Support

Another barrier is the expertise required to teach the technology and select the platforms and resources best for teaching. The Teaching Kits program offers support from NVIDIA and NVIDIA’s educator communities, discussions at conferences, getting-started guides, webinars, an open channel for educators to provide feedback and ask questions, plus more.

Teaching Resources

The Foundation for Next-Generation Innovators

Generative AI

Developed in collaboration with Assistant Professor Sam Raymond from Dartmouth College, this teaching kit is set to empower the next generation of professionals with the skills and knowledge needed in the rapidly evolving field of generative AI. The kit explores the practical implementation of generative AI with NVIDIA GPUs through hands-on experimentation with large language models (LLMs), diffusion models for image and video, multimodal LLM architectures, distributed model training, and accelerating inference.

Read Blog: NVIDIA Deep Learning Institute Launches Generative AI Teaching Kit

Deep Learning

Co-developed with Professor Yann LeCun and his team at New York University (NYU), this Teaching Kit leverages the latest computing frameworks and techniques to explore introductory and advanced deep learning topics, from image classification to generative adversarial networks (GANs) to natural language processing (NLP).

Watch Video: Bringing AI to the Classroom: NVIDIA's Deep Learning Teaching Kit

(60 Minutes)

Accelerated Computing

Co-developed with Professor Wen-Mei Hwu and his team from the University of Illinois (UIUC) and Professor Sunita Chandrasekaran and her team from the University of Delaware, this Teaching Kit covers introductory and advanced topics such as parallel programming APIs, programming tools and techniques, principles and patterns of parallel algorithms, and processor architecture features and constraints.

Watch Video: Accelerated Computing Teaching Kit for University Educators: Introduction and Use Cases

(60 Minutes)

Edge AI and Robotics

In collaboration with the University of Oxford and the University of Maryland Baltimore County, the Edge AI and Robotics Teaching Kit includes lecture slides and hands-on labs spanning topics such as big data and IoT, vision AI, reinforcement learning, conversational AI, diversity, ethics, and security, as well as autonomous robotics.

Watch Video: Getting Started with the Edge AI and Robotics Teaching Kit

(48 Minutes)

NVIDIA and Georgia Institute of Technology (Georgia Tech)

Data Science

In collaboration with the Georgia Institute of Technology (Georgia Tech) and Prairie View A&M University, this Teaching Kit focuses on GPU-accelerated algorithms and data science using the RAPIDS™ framework. The content has also been developed with cultural awareness, addressing issues such as bias and fairness in data science.

Watch Video: Accelerated Data Science in the Classroom: Teaching Analytics and Machine Learning with RAPIDS

(60 Minutes)

Graphics and Omniverse

Created in consultation with top film and animation schools in our Studio Education Partner Program, this Teaching KIt is designed for college and university educators looking to bring graphics and NVIDIA Omniverse™ - an open platform for virtual collaboration and real-time physically accurate simulation - into the classroom.

Watch Video: Learn How Educators Incorporate Omniverse in Media & Entertainment, Game Development, AECO, and the Industrial Metaverse

(95 Minutes)

Science and Engineering

Co-developed with Professor George Karniadakis and his team at Brown University, this Teaching Kit has dedicated modules for physics-informed machine learning (physics-ML) due to its potential to transform simulation workflows across disciplines, including computational fluid dynamics, biomedicine, structural mechanics, and computational chemistry.

Read Blog: NVIDIA Deep Learning Institute Launches Science and Engineering Teaching Kit

Comprehensive Content—Made by and for Educators

Co-developed with university faculty, NVIDIA Teaching Kits provide content to help university educators incorporate GPUs into their curriculum and deliver AI-ready content. And access to DLI online courses offers the opportunity to earn certificates of subject matter competency to support career growth.

Syllabi, lecture slides, and videos

Hands-on labs, quizzes, exams, and solutions

Quick-start guides and e-books

DLI Teaching Kits are very helpful for me and act as a class booster. Initially, I start with the basic training examples. The kits really help me to teach them the basics of deep learning such as convolutional neural networks, recurrent neural networks, and their training processes.

- Vipul Kumar Mishra, Associate Professor, Bennett University, India

Students know that the material we present is state of the art and up to date, so it gives them confidence in the material and draws a lot of excitement.

- Daniel Wong, Assistant Professor of Electrical and Computer Engineering, University of California, Riverside

If you want to spend time productively and if you want to do cool research, use the Teaching Kit. You'll save valuable time, and there's a lot of freedom to do it your own way adapted to your culture and to the demands of your own students but supported with very high-quality resources.

- Sunita Chandrasekaran, Assistant Professor, University of Delaware

- Vipul Kumar Mishra, Associate Professor, Bennett University, Indias

Students know that the material we present is state-of-the-art and up to date, so it gives them confidence in the material and draws a lot of excitement.

- Daniel Wong, Assistant Professor of Electrical and Computer Engineering, University of California, Riverside

- Sunita Chandrasekaran, Assistant Professor, University of Delaware

Partner Universities

NVIDIA partners with leading universities to co-develop content for DLI Teaching Kits, combining academic fundamentals and theory with the latest technology resources.

Advance Your Students' Skills in Accelerated Computing, AI, and Data Science.

Request a Teaching Kit