We may earn an affiliate commission when you visit our partners.
Course image

Artificial intelligence (AI) is everywhere, so young people need to understand what it is and how it might affect them. But what do you need to know to help them learn what AI systems can do and make informed decisions about how they can ethically take advantage of this technology?

Read more

Artificial intelligence (AI) is everywhere, so young people need to understand what it is and how it might affect them. But what do you need to know to help them learn what AI systems can do and make informed decisions about how they can ethically take advantage of this technology?

In this three-week course from the Raspberry Pi Foundation, you'll learn about the different types of AI tools that are available, and how they may affect the world of work and learning. You'll find out about the types of problems that AI tools can help to solve, try some out for yourself, and consider how you can discuss the risks, opportunities, and ethical considerations surrounding AI technology with young learners.

This course is part of Experience AI, a free educational programme developed in collaboration by the Raspberry Pi Foundation and Google DeepMind. Experience AI provides cutting-edge resources on AI and machine learning for teachers and their students aged 11 to 14.

What's inside

Learning objectives

  • Over the next 3 weeks, you will:
  • Build your knowledge about the types of ai systems, both predictive and generative.
  • Evaluate the impacts of ai tools on work and education, and how you and your learners can ethically use ai tools.
  • Investigate the types of problems that ai tools can help to solve and recognise their limitations.
  • Consider the risks of using ai tools, and how you can help mitigate these risks for your learners.
  • Prompt an ai "chatbot" and an image generator, and discover how knowing more about how these tools work can help you improve their outputs.

Syllabus

The course will cover:
How artificial intelligence moved from being a sci-fi plot point to real-life systems and tools
What machine learning is, and how it enables AI systems and models
Read more

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Examines various types of AI tools, their features, and applications
Introduces ethical considerations and risks associated with AI tools, enhancing learners' responsible use and understanding
Provides practical experience in using AI tools like chatbots and image generators, fostering hands-on learning
Delves into the technical foundations of AI, including machine learning and its role in enabling AI systems
Suitable for educators and learners interested in developing a comprehensive understanding of AI and its implications
May require foundational knowledge in technology or computer science for optimal comprehension

Save this course

Create your own learning path. Save this course to your list so you can find it easily later.
Save

Reviews summary

Ai for educators: clear, ethical, practical

According to learners, this course provides a largely positive experience, offering a clear and accessible introduction to AI specifically for educators. Students appreciate how the course demystifies complex AI concepts and makes them approachable for teaching teens. A significant strength highlighted is the practical focus, including hands-on activities with chatbots and image generators and insights into prompt engineering. Many reviewers found the emphasis on ethical considerations and risks to be particularly valuable and relevant. While some intermediate learners noted that certain topics felt a bit surface-level, the course is consistently praised as an excellent foundational resource, especially for those new to AI who wish to effectively teach these concepts in a classroom setting. The content is considered current and highly relevant for today's educational landscape.
Offers valuable practical experience with modern AI tools.
"I particularly appreciated the focus on ethical considerations and the hands-on activities with chatbots and image generators."
"The hands-on examples of using AI tools were incredibly helpful."
"The content on prompt engineering for LLMs was very current."
Covers crucial ethical considerations and risks of AI.
"I particularly appreciated the focus on ethical considerations and the hands-on activities with chatbots and image generators."
"The ethical discussions were particularly valuable."
"I did appreciate the emphasis on safety and ethical use, which is crucial for young learners."
Provides strategies for teaching AI to young learners.
"It gave me the confidence to discuss complex topics with my students."
"The course gives practical examples and helps you think about how to apply these ideas in the classroom. It's truly geared towards teaching..."
"It's not just about understanding AI, but specifically about how to *teach* it to a younger audience."
Simplifies complex AI concepts for educators.
"The content is well-structured, easy to understand, and highly practical."
"The Raspberry Pi Foundation has done a great job explaining complex concepts simply."
"The course demystifies AI and makes it approachable for anyone, especially educators who need to convey these ideas to students."
Some wish for more advanced content or interactivity.
"I wish there were more advanced resources or challenges for those who want to dive deeper after completing the course."
"Could perhaps benefit from more interactive quizzes."
"My only suggestion would be to update examples regularly as AI technology evolves so quickly."
Excellent for novices, but may lack depth for those with prior AI knowledge.
"My only minor critique is that some parts felt a bit surface-level for someone who already knew a little about AI..."
"...but it's perfect for complete beginners in this area."
"The course is fine for an absolute beginner, but if you have any prior knowledge of AI, you might find it too basic."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Teach Teens Computing: Understanding AI for Educators with these activities:
Review Machine Learning Basics
Start the course with a thorough understanding of the fundamental principles and terminology of machine learning, which will greatly aid in your comprehension of the course materials.
Browse courses on Machine Learning
Show steps
  • Review your notes and textbooks from previous coursework in machine learning.
  • Complete online tutorials or practice exercises to refresh your memory on key concepts.
Compile AI Resources
Organize and expand your knowledge by gathering relevant resources on AI, enhancing your understanding of the subject matter.
Show steps
  • Search and collect articles, tutorials, and videos related to AI concepts and applications.
  • Create a digital or physical compilation of these resources for easy reference.
Practice with AI Tools
Get hands-on experience with different types of AI tools to reinforce your learning and build confidence.
Browse courses on AI Tools
Show steps
  • Use online platforms or libraries to experiment with image generators.
  • Engage with chatbots to test their capabilities and explore natural language processing.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Attend an AI Workshop
Deepen your understanding of specific AI topics by attending workshops led by experts in the field.
Show steps
  • Research and identify AI workshops that align with your interests.
  • Register for and participate in the workshops to gain hands-on experience and insights.
Explore AI Applications
Gain a broader perspective on the usage of AI in various industries and domains to understand its potential impact.
Browse courses on AI Applications
Show steps
  • Follow online tutorials or attend webinars on the applications of AI in different sectors.
  • Research and read case studies of successful AI implementations.
Discuss AI Ethics
Engage in discussions with peers to explore the ethical implications of AI and foster responsible decision-making.
Browse courses on AI Ethics
Show steps
  • Join online forums or discussion groups dedicated to AI ethics.
  • Organize or participate in study groups to delve deeper into the ethical considerations surrounding AI.
Develop an AI-Powered Solution
Apply your knowledge to create a practical AI-based solution, demonstrating your understanding and problem-solving skills.
Show steps
  • Identify a problem or challenge that AI could potentially solve.
  • Design and develop an AI-powered solution to address the identified problem.
  • Test and evaluate the performance of your solution.

Career center

Learners who complete Teach Teens Computing: Understanding AI for Educators will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Teach Teens Computing: Understanding AI for Educators.
The premier applied machine learning masterwork, taking practitioners through intuitive concept breakdowns, production-grade Scikit-Learn workflows, and deep neural architecture implementations.
Written by a leading AI researcher, this book addresses the critical challenge of ensuring that AI systems are designed to be beneficial and aligned with human values. It explains the potential risks of advanced AI and proposes a new foundation for AI development. is highly relevant to contemporary discussions on AI safety and ethics and is accessible to a broad audience.
A timeless mathematical masterpiece that provides an uncompromising Bayesian and probabilistic foundation for linear classifiers, graphical models, kernel methods, and sampling algorithms.
Explores the potential impacts of AI on the future of humanity, covering a wide range of societal, philosophical, and ethical implications. It is written for a general audience and provides a broad overview of the opportunities and challenges presented by advanced AI. It's a must-read for anyone interested in the broader context and future directions of AI, offering valuable perspective beyond the technical aspects.
The definitive mathematical and theoretical canon of statistical learning, establishing the rigorous analytical foundations of regularized regression, tree ensembles, and high-dimensional inference.
Considered a foundational text in natural language processing, this book provides a deep dive into the subject, essential for understanding the linguistic underpinnings of chatbots. It's widely used in undergraduate and graduate NLP and computational linguistics courses, offering both theory and application. is invaluable for building a solid background in the field.
A distilled practitioner field guide outlining best practices for the entire machine learning lifecycle, from problem formulation and feature engineering to model deployment and monitoring.
This practical guide explores Large Language Models (LLMs), which are integral to the latest generation of chatbots. It provides hands-on examples and explanations of how LLMs work for language understanding and generation. is highly relevant for those interested in contemporary chatbot development.
Co-authored by a co-founder of DeepMind, this recent book explores the transformative impact of AI and other frontier technologies on society and the challenges of controlling them. It discusses the concept of the “containment problem” and the potential implications for the future. provides a contemporary perspective on the challenges and opportunities presented by advanced AI.
Delivers an end-to-end systems architecture guide for building reliable production ML systems, addressing data engineering trade-offs, real-time feature computation, and model drift mitigation.
Provides best practices and techniques for creating and improving conversational AI, including incorporating generative AI. It covers planning for continuous improvement and evaluating user experience, making it a valuable resource for building reliable and effective enterprise-level chatbots. This practical guide for developers and designers.
Bridges linear algebra, multivariable calculus, vector geometry, and probability directly to fundamental machine learning algorithms like PCA, Gaussian mixture models, and support vector machines.
Offers a critical examination of the broader societal and environmental impacts of AI. It reveals the hidden costs and power structures behind AI technologies, going beyond the technical aspects to explore its political and environmental dimensions. This is an important read for gaining a comprehensive understanding of AI's real-world consequences and is relevant to discussions on ethical and responsible AI.
Focuses on the user experience (UX) design of conversational interfaces, including chatbots and voice assistants. It emphasizes understanding user needs and designing intuitive and effective conversational flows. This is essential reading for anyone involved in the design aspect of chatbots.
Provides the monumental mathematical foundation of modern neural networks, connecting deep representation learning, backpropagation dynamics, and sequence modeling to empirical machine learning.
This textbook provides a comprehensive overview of the field of AI. It covers a wide range of topics, including the history of AI, the different types of AI, and the applications of AI. It valuable resource for anyone interested in learning more about AI.
Instructs data scientists on applied model evaluation, cross-validation, hyperparameter tuning, and pipeline construction through Scikit-Learn maintainers Andreas Müller and Sarah Guido.
Provides a practical guide to using generative AI, covering the different techniques and tools available. It is written by two leading experts in the field, Josh Patterson and Adam Gibson.
Delves into applying deep learning techniques to NLP problems. Given the prevalence of deep learning in modern chatbots and LLMs, this book is crucial for understanding the underlying technology driving more advanced conversational AI. It covers concepts like neural networks and their application in NLP tasks.
Explores the ethical implications of AI from a philosophical perspective. It discusses topics such as the nature of consciousness, free will, and moral responsibility in the context of AI. It thought-provoking read for anyone interested in the deeper ethical questions surrounding AI.
Explores the potential risks of AI and the need to develop strategies to mitigate them. It discusses the concept of superintelligence and the potential for AI to surpass human intelligence. It thought-provoking read for anyone interested in the future of AI and its impact on humanity.
Focuses on the process of building and evaluating predictive models in practice. It covers various modeling techniques and emphasizes important considerations like data preprocessing, feature selection, and model tuning. It valuable resource for practitioners and students interested in the practical aspects of predictive AI.
Offers a practical introduction to NLP using the Natural Language Toolkit (NLTK) in Python. It's a helpful resource for those who want to get hands-on with NLP concepts and build basic language processing applications, which are fundamental to chatbot development. This book is particularly useful for beginners and those with a programming background.
Investigates the engineering realities of running automated ML pipelines in production, addressing data drift detection, automated retraining loops, telemetry infrastructure, and continuous validation.
Provides a comprehensive guide to generative AI, covering both fundamental principles and practical applications in an enterprise context. Understanding generative AI is essential for working with the latest chatbot technologies. It's a relevant resource for those looking to apply generative AI in real-world scenarios.
This classic and highly-regarded book on reinforcement learning, a key area in AI focused on how agents learn to make decisions. It covers fundamental concepts and algorithms in a clear and accessible manner. It is suitable for advanced undergraduate and graduate students and primary reference for researchers in the field. is essential for understanding learning algorithms in AI.
Focuses on the practical aspects of building NLP systems for real-world applications, including chatbots. It covers the NLP pipeline and various use cases, providing valuable insights for developing functional conversational AI. It's a good resource for those interested in the implementation details.
Details cloud-native DevOps architectures for orchestrating automated machine learning lifecycles, integrating CI/CD triggers, model registry synchronization, and automated hyperparameter sweep workers.
Focuses on the engineering aspects of building AI applications, particularly with the use of foundation models. It provides practical guidance for professionals and engineers on developing and deploying AI systems. It is highly relevant to contemporary AI practices and offers valuable insights into the practical challenges of bringing AI to life.
This concise book provides a fast-paced introduction to language models, including the fundamentals of transformer architectures and LLMs. It's a good resource for quickly grasping the core concepts behind the language models that power modern chatbots. It is suitable for those with some ML background.
Guides engineers step-by-step through implementing, training, and fine-tuning complete generative transformer architectures in pure PyTorch, providing crystal-clear low-level insight into modern models.
Provides an accessible overview of the different approaches to machine learning, explaining the major paradigms and their potential to create a universal learning algorithm. It good book for gaining a broad understanding of the various techniques used in AI and how they relate to each other. It's suitable for readers with some technical background but is generally accessible.
Demystifies practical transformer model implementation through the Hugging Face ecosystem, showing how to fine-tune, optimize, and deploy attention architectures across diverse machine learning tasks.
Provides insights into the global landscape of AI development, focusing on the competition between the US and China. It discusses the technological advancements, economic implications, and societal impacts of AI from a geopolitical perspective. This book is valuable for understanding the real-world context and global trends in AI, particularly for professionals and those interested in the business and policy aspects.
Provides a guide to getting started with building chatbots, covering technological implementation and user experience. It's suitable for beginners who want to learn the basics of creating chatbots for various platforms. It's a practical entry point into the field.
Presents ten futuristic short stories illustrating the potential impact of AI on various aspects of human life by 2041, followed by analysis from AI expert Kai-Fu Lee. It offers a thought-provoking and accessible look at potential near-future scenarios shaped by AI. This book is good for gaining imaginative insights into the potential societal applications and implications of AI.
Combines interactive Jupyter notebooks with rigorous mathematical explanations to teach machine learning practitioners how modern neural architectures are designed, implemented, and trained.
Save
Feature engineering, the process of creating relevant features from raw data, critical step in building effective predictive models. provides practical guidance and techniques for this essential task, directly improving the performance of predictive AI systems.
Provides a look at the current state of AI and its potential impact on society. It discusses topics such as the use of AI in healthcare, education, and transportation. It valuable resource for anyone interested in learning more about AI and its potential impact on our lives.
Provides a business-oriented perspective on data science and predictive analytics. It focuses on the fundamental principles of data mining and how to think analytically to extract value from data. It is particularly useful for understanding the business context and applications of predictive AI.
Provides a look at the global race for AI supremacy. It discusses the strengths and weaknesses of the AI programs in China, the United States, and other countries. It valuable resource for anyone interested in the geopolitical implications of AI.
Provides a thought-provoking exploration of the future of generative AI, discussing its potential benefits and risks. It is written by Gary Marcus, a leading researcher in the field.
Written by a pioneer in causal inference, this book provides a more philosophical and accessible exploration of causality and its importance in artificial intelligence and data science. It is valuable for understanding the theoretical underpinnings and the potential of causal reasoning in predictive AI.
This comprehensive handbook covers a wide range of NLP techniques, from classical to statistical approaches, and explores various applications. It serves as a valuable reference tool for understanding different methods used in building NLP systems, including those relevant to chatbots. is suitable for researchers and practitioners seeking a broad overview of the field.
Provides a business-oriented perspective on generative AI, discussing its potential impact on industries and how companies can use it to gain a competitive advantage. It is written by three leading experts in the field, Thomas Davenport, Rajeev Ronanki, and Nitin Mittal.
Unifies computer science, evolutionary biology, and neuroscience to synthesize the five foundational tribes of machine learning, giving practitioners a panoramic interdisciplinary view of learning algorithms.
Offers a unique economic perspective on artificial intelligence, framing it as a reduction in the cost of prediction. It helps to understand the economic implications and strategic opportunities created by advancements in predictive AI. It is particularly relevant for managers and executives.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Teach Teens Computing: Understanding AI for Educators.
Generative AI with Large Language Models
Most relevant
Gen AI - RAG Application Development using LangChain
Most relevant
Principles and Technologies of 5G Mobile Networks
Most relevant
Getting Started with Generative AI: Unboxing the Future
Most relevant
Building Generative AI-Powered Applications with Python
Most relevant
Amazon Bedrock - The Complete Guide to AWS Generative AI
Most relevant
Generative AI using OpenAI API for Beginners
Most relevant
Generative AI for Beginners
Most relevant
AWS Amazon Bedrock & Generative AI - Beginner to Advanced
Most relevant

edX Buyer Protection & Guarantee

Verified partner policies & purchase protections

World-Class University Partner
Free Trial & Audit

Free Audit Track Available

Free audit track available for most courses, giving open access to video lectures, course readings, and assignments at no charge.

Return & Refund Policy

14-Day Full Refund Window

14-day full refund available up to 14 days after course start or 14 days after payment (whichever comes second, up to 6 months max), provided verified certificate has not yet been earned.

Buyer Protections

Verified Academic & Industry Partner

University-backed credentials authored by elite institutions like Harvard, MIT, and Oxford, with tamper-proof certificate verification.

Key Purchase Protections
Free audit track for open learning access
14-day money-back guarantee on verified certificates
Prestigious university credentials (Harvard, MIT)
Automatic unenrollment refund process via dashboard
OpenCourser Verified Partner Policy details last reviewed: 2026-10-22
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser