11 B. Resources for Further Learning and Implementation

• Educators will find additional materials and guidance to continue exploring and implementing GenAI.

Part 1: Generative AI Resources

A curated list of resources tailored for educators and learners aiming to delve deeper into the nuances of generative models and their applications:

1. OpenAI’s GenAI Models OpenAI provides comprehensive documentation and guides on utilizing OpenAI’s GenAI models (GPT-4, DALL·E etc.). These resources offer insights into the capabilities, ethical use, and integration of various into various applications. OpenAI Platform Guide
2. Deep Learning Specialization by Andrew Ng on Coursera This specialization provides an in-depth understanding of deep learning, including a course specifically dedicated to sequence models which are foundational for understanding generative AI technologies like GPT-3 and beyond. Deep Learning Specialization
3. Hugging Face Course on Transformers Hugging Face offers a free course that dives into transformers, the architecture behind many of the leading generative AI models today. This course covers the theory and practical implementation of transformers in various NLP tasks. Transformers Course
4. Google’s Machine Learning Crash Course with TensorFlow APIs While this course covers a broad range of machine learning principles, it includes specific modules on neural networks that are essential for understanding generative AI. It’s a great resource for educators looking to integrate AI into their curriculum. Machine Learning Crash Course
5. Stanford University’s NLP with Deep Learning Course Stanford’s course offers an advanced look into natural language processing with a focus on deep learning. It covers the latest in generative models, including transformers and GPT-like architectures. NLP with Deep Learning
6. AI For Everyone by deeplearning.ai on Coursera While broader in scope, this course includes important discussions on the implications and possibilities of generative AI in society. It’s a valuable resource for educators looking to discuss the broader impacts of AI technologies. AI For Everyone
7. Arxiv’s Latest Research Papers on Generative AI Arxiv.org is a repository of electronic preprints (known as e-prints) approved for publication after moderation, where the latest research on generative AI and related fields is frequently published. It’s a great resource for staying up-to-date with the cutting-edge advancements in GenAI. Arxiv Generative AI

These resources above are intended to provide educators and learners with a comprehensive toolkit for understanding, exploring, and implementing generative AI in various contexts, fostering a deep and nuanced understanding of this transformative technology.

Part 2: AI-in-General Resources

This is a selection of resources that provide comprehensive insights, tools, and guidelines for exploring and implementing generative AI technologies in educational settings.

1. OpenAI’s Educational Resources OpenAI offers a wide range of resources designed to introduce educators and students to the principles and applications of artificial intelligence, including generative AI. These resources cover foundational concepts, bias, limitations, and integration examples in various contexts.
2. Kaggle’s Micro-Courses Kaggle, a platform for data science and machine learning competitions, offers micro-courses that cover a range of topics from Python programming to machine learning and deep learning. These courses are practical and hands-on, allowing educators to gain skills in data science and AI application.
3. MIT OpenCourseWare’s Introduction to Deep Learning MIT’s OpenCourseWare provides a comprehensive introduction to deep learning and its applications, including generative models. This course is freely available and includes lectures, assignments, and exams from the actual MIT course. Introduction to Deep Learning
4. NVIDIA Deep Learning AI Playground NVIDIA offers an interactive platform for experimenting with deep learning models, including generative AI. This playground allows educators and students to visualize and understand how neural networks work and how they can be applied to generate text, images, and more. NVIDIA AI Playground
5. Hugging Face’s Transformers Library The Hugging Face Transformers library is a comprehensive resource for natural language processing (NLP), including tools and models for text generation, translation, and analysis. It’s an invaluable resource for educators looking to integrate advanced NLP and generative AI into their curriculum. Hugging Face Transformers
6. Google AI Education Google offers a range of educational resources and tools to help understand and apply AI technologies. This includes courses, guides, and tools tailored to various skill levels, from beginners to advanced practitioners. Google AI for Education About Google AI
7. AI4ALL Open Learning AI4ALL Open Learning provides resources aimed at increasing diversity and inclusion in AI education. Their materials are designed to make AI more accessible and understandable to high school students, with a focus on empowering underrepresented groups in the field. AI4ALL Open Learning
8. Fast.ai Fast.ai offers practical deep learning courses for coders, aiming to make deep learning more accessible to a broader audience. Their courses cover a range of topics, including how to build and deploy generative AI models. Fast.ai Courses
9. TensorFlow Tutorials TensorFlow, an open-source machine learning framework by Google, provides a comprehensive set of tutorials that cover the basics of machine learning to more advanced topics such as generative AI. TensorFlow Tutorials

These resources above collectively provide a solid foundation for educators seeking to expand their knowledge and advance their skills in generative AI, facilitating its incorporation into educational environments for enhanced learning experiences.