Exploring the fascinating world of AI requires a solid educational foundation. This section provides a curated collection of free online courses, tutorials, and learning resources to help your AI Club members gain theoretical knowledge and practical skills in various AI domains.
The first step in preparing for an AI-enhanced world is to understand what AI is, how it works, and the ethical issues related to AI. From there, focus on AI’s potential impact on various aspects of society — including economics and employment. Then, dive into building your own AI if you want to go deeper.
Here are some resources to help you plan your AI Club’s learning journey.
Curated Workshops
The AI Pedagogy Project’s AI Starter Guide and the Large Language Model Tutorial are great places to get started.
While these resources were developed primarily for educators, they work equally well for a student-led AI Club.
In addition, each of these resources have AI workshops and sessions for students. Some are coding based, but many don’t require any coding knowledge. And some are even sessions that can be done without a computer or internet connection.
- aiEDU: aiEDU is a non-profit that creates equitable learning experiences that build foundational AI literacy.
- AI for Education: Curriculum, prompts, resources, and more for educators interested in using AI in and outside the classroom
- AI Literacy Lessons for Grades 6–12 (Common Sense Media): Quick lessons (20 minutes or less) to give students an intro to AI , its potential risks and benefits, and how to think critically to be ethical and responsible users of AI.
- AI Pedagogy Project: The AI Pedagogy Project, created by the metaLAB (at) Harvard and FU Berlin, seeks to demystify AI, encouraging critical engagement and creative AI applications in education.
- DAILy Curriculum: The DAILy curriculum, developed by a team of researchers at MIT RAISE, features 4 units for hands-on and computer-based activities on AI concepts, ethical issues in AI, creative expression using AI, and how AI relates to your future
- Day of AI: Developed by a team of researchers at MIT RAISE, these free resources are designed to be taught by educators with little or no technology background. Activities are organized by age group (elementary, middle school, and high school) and can be run in 30-minute to 1-hour time blocks.
- MIT AI Ethics Curriculum for Middle School Students: Developed by a team of researchers at MIT RAISE, the AI & Ethics Project has developed an open source curriculum for middle school students on artificial intelligence and its ethical implications.
- RAISE Playground: A block-based programming platform that lets anyone use machine learning models, robotics, and AI engines to make projects.
- TeachAI: TeachAI, a collaboration between Code.org and other organizations, provides a toolkit for schools working on AI guidance policies.
- Teaching with AI, by Open.AI: Open.AI, the creator of ChatGPT, has published an online guide for educators using generative AI in their classroom—including suggested prompts, an explanation of how ChatGPT works and its limitations, the efficacy of AI detectors, and bias.
Online Courses and Tutorials for AI Clubs
Here is a curated list of high-quality online courses and tutorials from reputable sources like Coursera, edX, and DataCamp. Your faculty advisor may be able to get your AI Club free access to DataCamp courses. These resources cover a wide range of AI topics and cater to different learning styles:
AI Basics
- DataCamp AI Fundamentals Course: an intro into AI, ChatGPT, large language models (LLMs), and machine learning (ML)
- DataCamp Generative AI Course: this no-coding course covers generative AI, its development, ethical considerations, future prospects, and how to effectively leverage and collaborate with these powerful content creation tools.
- DataCamp AI Ethics Course: a comprehensive overview of ethical considerations in AI, covering principles, strategies for fair and equitable systems, bias minimization, key issues, user trust, and hands-on exercises to craft ethical AI by design.
- DeepLearning AI for Everyone: offers comprehensive training in AI for anyone, covering common AI terminology, practical applications, project building, team collaboration, and ethical considerations.
- Google AI for Anyone: a course for anyone to learn what AI is and how it works.
- Google Introduction to Generative AI: introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods.
- Google Introduction to Responsible AI: introductory-level microlearning course aimed at explaining what responsible AI is, why it’s important, and how Google implements responsible AI in their products.
Learn to Design AI
- DataCamp Machine Learning Fundamentals with Python: start to learn machine learning basics with Python, starting with supervised learning with the scikit-learn library, how to cluster, transform, visualize, and extra insights from data using unsupervised learning and scipy, and fundamentals of neural networks and deep learning models using PyTorch.
- HarvardX: CS50’s Introduction to Artificial Intelligence with Python: learn to use machine learning in Python in this introductory course on artificial intelligence.
Educational Videos and Lectures for AI Clubs
Complement your learning with engaging video content from renowned experts and institutions. These video resources provide visual explanations, examples, and insights into AI concepts:
Ted Talks on AI
- How we teach computers to understand pictures | Fei Fei Li
- Why AI Will Spark Exponential Economic Growth | Cathie Wood | TED
- How AI Could Empower Any Business | Andrew Ng | TED
- How to Keep AI Under Control | Max Tegmark | TED
- How AI Could Save (Not Destroy) Education | Sal Khan | TED
- Leadership in the Age of AI | Paul Hudson and Lindsay Levin | TED
- Why AI Is Incredibly Smart and Shockingly Stupid | Yejin Choi | TED
Other Videos on AI
- The 7 Types of AI – And Why We Talk (Mostly) About 3 of Them
- Google’s AI Course for Beginners (in 10 minutes)!
- What are Generative AI models?
- Introduction to Generative AI
- AI vs Machine Learning
- Neural Networks Explained in 5 minutes
- Natural Language Processing In 5 Minutes | What Is NLP And How Does It Work? | Simplilearn
- What is NLP (Natural Language Processing)?
- Machine Learning vs Deep Learning
- Computer Vision Explained in 5 Minutes | AI Explained
- Andrew Ng: Opportunities in AI – 2023
Longer videos on AI
- What is generative AI and how does it work? – The Turing Lectures with Mirella Lapata
- What’s the future for generative AI? – The Turing Lectures with Mike Wooldridge
- What is Artificial Intelligence? with Mike Wooldridge
- From artificial intelligence to hybrid intelligence – with Catholijn Jonker
- What are the different types of Artificial Intelligence?
Books and Reading Materials for AI Clubs
For those who prefer traditional reading materials, here are some books, research papers, and articles on AI topics and other future:
- The Algorithm by Hilke Schellmann (2024)
- AI Needs You: How We Can Change AI’s Future and Save Our Own by Verity Harding (2024)
- AI 2041: The Visions for our Future by Kai-Fu Lee and Chen Qiufan (2021)
- Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell (2019)
- Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor by Virginia Eubanks (2018)
- If Then: How the Simulmatics Corporation Invented the Future by Jill Lepore (2020)
- Impromptu: Amplifying Our Humanity Through AI by Reid Hoffman (2023)
- The Coming Wave: Technology, Power, and the Twenty-first Century’s Greatest Dilemma by Mustafa Suleyman (2023)
- The Future Is Faster Than You Think: How Converging Technologies Are Disrupting Business, Industries, and Our Lives by Peter H. Diamandis and Steven Kotler (2020)
- Recoding America Why Government Is Failing in the Digital Age and How We Can Do Better by Jennifer Pahlka (2023)
- Techlash: Who Makes the Rules in the Digital Gilded Age? by Tom Wheeler
- The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI by Fei-Fei Li (2023)
Coding Project Ideas and Code Repositories for AI Clubs
Hands-on projects are crucial for solidifying your AI knowledge and skills. Explore our collection of project ideas, templates, and code repositories to kickstart your own AI creations.
Google Colaboratory
Google Colaboratory (“Colab”) allows anybody to write and execute python code through the browser, and is especially well suited to machine learning, data analysis and education. More technically, Colab is a hosted Jupyter Notebook service that requires no setup to use and provides free access to computing resources, including GPUs and TPUs. Here are some Colab projects and tutorials to start with:
- AlphaFold: Predict the structure of a protein
- Generating Piano Music with Transformer
- Handwritten Digit Recognition using Convolutional Neural Networks
- Predict Shakespeare with Cloud TPUs and Keras
- Text Classification with Movie Reviews
- Twitter Pulse Checker
Remember, these resources are just starting points for your AI Club. We encourage you to continuously explore, experiment, and stay updated with the latest developments in the rapidly evolving field of AI.