Generative AI, powered by advanced machine learning models and deep neural networks, is revolutionizing industries by generating novel content and driving innovation in fields like healthcare, finance, and entertainment. NVIDIA is at the forefront of this transformation with its state-of-the-art GPU architectures and software ecosystems, such as the H100 Tensor Core GPU and CUDA platform, which optimize the development and deployment of generative models, according to NVIDIA Technical Blog.

The Importance of Generative AI Education

As generative AI models, such as GANs and transformers, become increasingly sophisticated, there is a growing demand for skilled professionals who can develop, refine, and ethically deploy these technologies. A strong educational foundation in generative AI equips students with the practical skills and theoretical knowledge needed to innovate in areas like content creation, drug discovery, and autonomous systems.

College and university education in generative AI is crucial due to the rapidly expanding role of AI in almost every industry. By integrating generative AI into their curriculum, universities prepare the next generation of AI researchers, engineers, and thought leaders to advance the field and address the complex challenges associated with AI-driven innovation.

The new Generative AI Teaching Kit, a collaboration between the NVIDIA Deep Learning Institute (DLI) and Dartmouth College, is set to empower the next generation of professionals with the skills and knowledge needed in this rapidly evolving field.

This comprehensive teaching resource enables educators to provide students access to cutting-edge tools, frameworks, and practical exercises crucial for understanding the complexities of Generative AI and large language model development and deployment. By equipping students with a deep understanding of generative AI techniques, the Teaching Kit enables educators to foster future innovation and creativity in AI-driven industries.

As students transition into the workforce, they will be better prepared to tackle global challenges, from improving healthcare and science to advancing sustainable technologies.

Sam Raymond, adjunct assistant professor of engineering at Dartmouth College, was instrumental in developing the content. “Empowering students with skills to understand and potentially develop their own GPU-accelerated Generative AI applications is the primary objective,” said Raymond. “I believe students who go through this course will be at a significant advantage in the job market and help bridge the knowledge gap in industries today.”

Overview of the Generative AI Teaching Kit

All Teaching Kits include lecture slides, hands-on labs, Jupyter notebooks, knowledge checks, and free online self-paced courses that provide certificates of competency for students, all comprehensively packaged up and ready for classroom and curriculum integration.

The aim of the Generative AI Teaching Kit is to introduce the foundational concepts of natural language processing (NLP) essential for understanding LLMs and generative AI more broadly. Key concepts of LLMs are then examined using NVIDIA GPUs, tools, and services, as well as open-source libraries and frameworks. A simple pretraining exercise of a GPT model shows basic training processes in the cloud.

The kit also covers diffusion models to explore the application of generative AI in image and video generation. Multi-modal LLM architectures are then introduced, with a focus on optimizing various LLM architectures during fine-tuning using the NVIDIA NeMo framework. Advancements in inference and the refinement of tools like chatbots are also discussed, using NVIDIA NIM, NeMo Guardrails, TensorRT, and TensorRT-LLM to enhance efficiency and scalability in production environments.

The Generative AI Teaching Kit contains focused modules that combine theory, algorithms, programming, and examples. This first release includes the following modules:

• Introduction to Generative AI
• Diffusion Models in Generative AI
• LLM Orchestration

More modules will be available in future releases of the kit.

This content is valuable for educators across various fields, especially in computer science and engineering. Its modular design enables instructors to tailor the course to meet the specific needs of their students and create a customized learning experience. Select professors from around the world have already been given early access to first-release modules.

“I’m eager to integrate the Generative AI Teaching Kit in my AI in Materials Engineering class,” said Mohadeseh Taheri-Mousavi, assistant professor in the Materials Science and Engineering department at Carnegie Mellon University. “The comprehensive lecture notes with well-structured coding labs with examples from various fields, and associated online courses with certificates, will provide my students with the cutting-edge resources to deeply understand the broad applications of generative AI techniques in various fields.”

Professor Payam Barnaghi from the Department of Brain Sciences at Imperial College London uses LLMs and generative AI in his research using electronic health records and healthcare data. “NVIDIA Generative AI Teaching Kit content is a wonderful resource for students learning the latest developments in AI and machine learning,” said Barnaghi. “As a result of having early access to the first modules, I plan to use this content as the basis for teaching advanced topics in my machine learning for neuroscience courses.”

Given the fast-paced advancements in generative AI, educators can expect the teaching materials to be updated over time. NVIDIA is dedicated to offering high-end educational resources and welcomes feedback to continuously improve the content.

Get Started

Educators can access the first release of the Generative AI Teaching Kit and other kits for free by joining the NVIDIA DLI Teaching Kit Program.

About the NVIDIA Deep Learning Institute

The NVIDIA Deep Learning Institute (DLI) offers resources for diverse learning needs, from learning materials to self-paced and live training to educator programs. Individuals, teams, organizations, educators, and students can now find everything they need to advance their knowledge in AI, accelerated computing, accelerated data science, graphics, simulation, and more.

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