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 leading this transformation with its cutting-edge GPU architectures and software ecosystems, such as the H100 Tensor Core GPU and CUDA platform, which optimize the development and deployment of generative models.
NVIDIA NIM enhances the efficiency and scalability of AI inference tasks, enabling rapid deployment and iteration across various computing environments and accelerating advancements in generative AI applications.
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 that are 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) that are 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:
- Module 1: Introduction to Generative AI
- Module 2: Word Embeddings, Tokens, and NLP
- Module 3: Large Language Models and the Transformer
- Module 4: LLM Scaling Laws and LLM Families
- Module 5: Multimodal Learning and Its Applications
- Module 6: Diffusion Models in Generative AI
- Module 7: Model Training (Pre-Training, Instruction Following, and PEFT)
- Module 8: LLM Orchestration
- Module 9: Scaling Model Training to Distributed Workloads
Through a collaboration with Google, educators also get access to free Google Colab credits to run the lab notebooks in preparation for teaching the course.
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.
LLM technical certification discounts for students
The Generative AI Teaching Kit also includes access to a 50% discount on the NVIDIA-Certified Associate: Generative AI LLMs certification exam and the NVIDIA-Certified Associate: Generative AI Multimodal certification exam for educators to distribute to students.
It also includes access to both exams free of charge for educators. Both exams are online and proctored remotely, include 50-60 questions, and have a 60-minute time limit.
These technical certifications validate students’ expertise in generative AI, offering a competitive advantage in the job market. They can open doors to exciting career opportunities across AI-driven industries.
The NCA Generative AI LLMs certification is an entry-level credential that validates the foundational concepts for developing, integrating, and maintaining AI-driven applications using generative AI and large language models (LLMs) with NVIDIA solutions.
The NCA Generative AI Multimodal certification is an entry-level credential that validates the foundational skills needed to design, implement, and manage AI systems that synthesize and interpret data across text, image, and audio modalities.
NVIDIA recommends that students take these exams after completing the Generative AI Teaching Kit.
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