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Jeanne Beatrix Law

This course expands on the AI for Education (Intermediate) course. Participants will learn quick ways to refine prompt engineering methods for assignments and course design that can be scaled to multiple levels of educational contexts.

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This course expands on the AI for Education (Intermediate) course. Participants will learn quick ways to refine prompt engineering methods for assignments and course design that can be scaled to multiple levels of educational contexts.

This course further provides straightforward and practical definitions, scenarios, and prompt engineering methods with real-time demonstrations in diverse educational learning environments. Participants will be provided tested methods for prompting an AI Assistant, such as GPT to yield useful, relevant, accurate, and ethical outputs. Learners will gain a clear understanding of how to collaborate with an AI Assistant and how to encourage students to do so in ethical ways. Knowing how to describe and collaborate with AI Assistants effectively and rhetorically is a vital skillset to successfully engage with students in all types of learning environments, from secondary to college levels.

This course is a beginning step in learning these skills.

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What's inside

Syllabus

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Provides practical definitions of AI for Education and prompt engineering methods that make course design and assignments more efficient
Develops learners' skills in collaborating with AI Assistants in their work
This course is an initial step in the development of skills for working with AI Assistants in education

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Reviews summary

Practical ai for education ethics

According to students, this course offers a practical and ethical approach to integrating AI into education, focusing on refining prompt engineering methods for various contexts. Learners appreciate the real-time demonstrations and clear guidance on how to encourage ethical AI collaboration among students. While titled 'Advanced', it serves as a foundational step in mastering AI skills for educators, providing immediately applicable strategies for course design and assignments, though some might find it less deeply technical than expected for an 'advanced' course.
Provides up-to-date and applicable AI information.
"The course materials felt very relevant to the current landscape of AI in education."
"I found the content to be quite up-to-date, which is important in such a fast-changing field."
"It directly addresses contemporary challenges of using AI in learning environments."
Teaches effective methods for AI prompting.
"The course really helped me refine my prompt engineering skills for creating better assignments."
"I now feel confident crafting prompts that yield relevant and useful AI responses for educational tasks."
"Learning specific prompt engineering techniques was the highlight, very applicable to my work."
Emphasizes responsible and ethical AI integration.
"It's crucial to teach students about ethical AI, and this course gave me the tools to do it."
"I appreciated the emphasis on ethical outputs and how to guide students in responsible AI collaboration."
"The discussions around ethical considerations in using AI for education were very insightful."
Offers actionable AI methods for educators to apply.
"I learned practical prompt engineering techniques that I could apply in my classroom right away."
"The real-time demonstrations were incredibly helpful for understanding how to use AI in teaching."
"This course provided me with straightforward scenarios for integrating AI ethically into my curriculum."
Provides a solid foundation despite the 'Advanced' title.
"While it's labeled 'Advanced', I felt it was a great starting point for educators new to AI."
"I expected more deep technical content given the 'Advanced' title, but it's more about practical application."
"It's a beginning step as stated, which is good, but the title might set different expectations for some."

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 AI for Education (Advanced) with these activities:
Organize and review course materials
Organizing materials early helps establish good habits for successful learning and better retention.
Show steps
  • Set up a dedicated study space and collect materials
  • Organize syllabus, assignments, and notes
  • Review course schedule and mark important dates
  • Identify necessary resources such as textbooks and online materials
Review AI for Education (Intermediate)
Review the key concepts and methods from the AI for Education (Intermediate) course to ensure a strong foundation for this course.
Browse courses on AI in Education
Show steps
  • Review the course syllabus and materials
  • Summarize the main topics covered in the course
  • Take practice quizzes or review past assignments
Practice Prompt Engineering Techniques
Practice writing effective prompts for AI assistants using real-time demonstrations and examples.
Browse courses on Prompt Engineering
Show steps
  • Use an AI assistant to generate content for different educational tasks
  • Analyze the output and identify areas for improvement
  • Refine the prompts and regenerate content
One other activity
Expand to see all activities and additional details
Show all four activities
Explore AI Assistant Collaboration in Education
Find and follow tutorials on how to effectively collaborate with AI assistants in educational settings.
Browse courses on Education Technology
Show steps
  • Search for online tutorials on AI assistant collaboration
  • Choose a tutorial and follow the instructions
  • Apply the techniques learned to your own teaching or learning experience

Career center

Learners who complete AI for Education (Advanced) will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 49 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 AI for Education (Advanced).
Comprehensive handbook of educational technology. It covers a wide range of topics, including the history of educational technology, the different types of educational technology, and the ways that educational technology can be used to improve teaching and learning.
This classic textbook provides a comprehensive overview of AI, covering fundamental concepts, algorithms, and applications. It serves as a valuable resource for gaining a deeper understanding of the theoretical foundations of AI Assistant technology.
Provides a comprehensive guide to prompt engineering, covering techniques for crafting effective inputs to generative AI models. It's particularly useful for understanding how to obtain reliable and predictable results, which is crucial for both beginners and those looking to deepen their practical skills. This book is valuable as a current reference for anyone working with generative AI.
Provides a critical and material perspective on AI, examining its environmental costs, labor exploitation, and the power structures it reinforces. It is essential reading for understanding the broader societal and political context of AI development and is particularly valuable for those interested in the real-world impacts beyond technical discussions.
Introduces a new way of thinking about data science and AI, drawing on the principles of intersectional feminism. It highlights how power imbalances are embedded in data and algorithms and offers a framework for building more equitable and just data systems. It is highly relevant for understanding bias and fairness in AI.
Practical guide to using technology in the classroom. It covers a wide range of topics, including how to choose and use educational software, how to design and deliver online courses, and how to use technology to assess student learning.
Comprehensive overview of educational technology theory and practice. It covers a wide range of topics, including the history of educational technology, the different types of educational technology, and the ways that educational technology can be used to improve teaching and learning.
Provides a comprehensive overview of the theory and practice of educational design. It covers the entire process of designing learning experiences, from understanding the needs of learners to evaluating the effectiveness of the learning process.
This comprehensive book covers speech and language processing, essential components of AI Assistants. It provides a deep understanding of speech recognition, language modeling, and dialogue systems, enabling readers to develop AI Assistants with advanced speech and language capabilities.
Presents a framework for centering the voices and needs of marginalized communities in the design of technology and AI. It offers practical guidance and case studies for creating more equitable and just technological systems, making it valuable for designers, developers, and policymakers.
Offers a practical, hands-on approach to prompt engineering specifically with ChatGPT. It's an excellent resource for high school and undergraduate students getting started, providing clear examples and exercises. It serves as a useful introductory guide and additional reading to complement foundational AI courses.
Provides a hands-on approach to prompt engineering with a focus on using the OpenAI API. It's particularly relevant for undergraduate students, graduate students, and working professionals who want to programmatically interact with LLMs. It serves as a practical guide for implementing prompt engineering techniques in applications.
Delves into the technical aspects of designing algorithms that are fair, private, and transparent. It is particularly useful for students and professionals with a technical background who want to understand the computational challenges and solutions related to ethical AI. It can serve as a valuable reference for those building AI systems.
Focuses on the creative aspects of prompt engineering and generating diverse language outputs. It's a good fit for students and professionals looking to go beyond basic prompting and explore more advanced techniques for creative content generation. It adds breadth by covering applications in areas like creative writing and podcasting.
Examines the increasing power of algorithms in finance, search, and reputation, highlighting the lack of transparency and accountability. It provides crucial context for understanding the societal implications of opaque algorithmic systems and is valuable for students and professionals across various disciplines.
Co-authored by a co-founder of DeepMind, this book examines the transformative potential of AI and other frontier technologies while also highlighting the immense challenges of controlling them for the benefit of humanity. It provides a recent and insightful perspective on the opportunities and risks ahead.
This guide aims to make prompt engineering accessible with a step-by-step approach. It is well-suited for beginners and those new to the field, including high school students and those in introductory undergraduate programs. It provides practical tips and is useful for gaining a broad understanding of how to formulate effective AI prompts.
Explores the future of educational technology. It discusses the different ways that technology is likely to be used in education in the years to come, and the challenges and opportunities that this will create.
A comprehensive guide aimed at making prompt engineering accessible to a wide audience. It covers various techniques and applications for leveraging AI language models effectively. is useful for high school students through working professionals seeking a thorough introduction and practical guidance.
While this book focuses on deep learning, a subfield of AI, it provides a solid foundation for understanding AI Assistant technology. It delves into deep learning algorithms, architectures, and applications, equipping readers with the technical knowledge necessary for building and evaluating AI Assistants.
Written by a leading AI researcher, this book explores the long-term challenges of ensuring that advanced AI systems remain beneficial to humanity. It provides a comprehensive overview of the control problem and potential solutions, making it relevant for those interested in the future trajectory of AI and its ethical implications.
Explores the relationship between learning theories and educational technology. It discusses how learning theories can be used to inform the design and development of educational technology, and how educational technology can be used to support different learning theories.
Provides a framework for organizations to implement AI responsibly at scale. It addresses the challenges of integrating ethical considerations into business practices and offers guidance on mitigating risks and fostering a culture of responsible AI development and deployment.
This guide offers quick tips and tricks for prompt engineering across different generative AI models, including text and image generation models. It's a practical resource for users who want to improve their immediate results with various AI tools. It's suitable for all levels looking for actionable advice.
This textbook offers a structured approach to understanding AI ethics, covering key concepts, theories, and case studies. It is suitable for students in academic settings and provides a solid foundation for in-depth study of the ethical challenges in AI.
Written by prominent figures from politics, technology, and academia, this book explores the geopolitical and societal implications of AI. It offers a high-level perspective on how AI is transforming global power dynamics and the future of human society, making it relevant for those interested in policy and strategy.
Provides a comprehensive overview of the future of education in China. It valuable resource for anyone involved in educational development in China.
This handbook is geared towards engineers working with LLMs, covering the process from concept to production. It provides a deeper technical understanding of integrating and managing LLMs, which is relevant for prompt engineers working in a development context. It is best suited for graduate students and working professionals.
Explores the role of educational technology in teacher education. It discusses the different ways that technology can be used to prepare teachers for the 21st century classroom, and the challenges and opportunities that this creates.
Explores prompt engineering within the broader context of generative AI and touches upon ethical considerations. It's relevant for all levels, providing a balanced view of the technical aspects and the societal impact of generative AI. It's useful for gaining a broader understanding and considering the responsible use of AI.
While not solely focused on prompt engineering, this book provides a strong foundation in understanding how LLMs work, which is essential for effective prompting. It's suitable for undergraduate and graduate students, offering technical insights into language understanding and generation. It serves as valuable background reading for those wanting to understand the underlying mechanisms of the models they are prompting. Expected publication in September 2024.
This practical guide focuses on implementing machine learning algorithms using popular Python libraries. It provides hands-on experience in building and evaluating machine learning models, which is essential for developing AI Assistants.
Explores natural language processing (NLP), a crucial aspect of AI Assistants. It delves into NLP techniques, algorithms, and applications, providing readers with the knowledge and skills necessary for developing AI Assistants with effective natural language capabilities.
Provides a comprehensive overview of the field of educational psychology. It covers a wide range of topics, including learning theories, motivation, assessment, and classroom management.
Provides a framework for reflective teaching. It helps teachers to understand their own teaching practices and to improve their teaching.
Provides the UNESCO's annual report on the progress towards achieving the Education for All goals. It valuable resource for anyone involved in monitoring educational progress.
This volume offers an interdisciplinary exploration of the long-term future of AI, including potential risks and ethical considerations. It delves into complex topics and computational frameworks, making it suitable for advanced students and researchers interested in the theoretical and philosophical aspects of AI ethics and safety.
Explores the technical and philosophical challenges of building ethical considerations into AI systems. It delves into the feasibility of creating 'moral machines' and the implications of such developments, providing a solid foundation for understanding the ethical dimensions of AI design.
Covers the broader field of AI engineering with a focus on foundation models, which include the LLMs used in prompt engineering. It's relevant for professionals and graduate students interested in the engineering aspects of building AI applications. It provides context on how prompt engineering fits into larger AI systems.
Focuses on the practical aspects of building NLP systems. While prompt engineering specific technique, understanding the entire NLP pipeline is beneficial for professionals. It's a good reference for those looking to implement prompt engineering within larger NLP applications.
For those who want to understand the mechanics of LLMs deeply, this book guides you through building one from scratch. This is highly technical and suitable for advanced undergraduate students, graduate students, and researchers. A deep understanding of LLM architecture is beneficial for advanced prompt engineering techniques.
Is specifically aimed at educators but offers valuable insights into crafting prompts for educational purposes. It's relevant for anyone interested in using prompt engineering in a learning context. It provides practical strategies and examples for a specific application domain.
A foundational text in statistical NLP, this book provides the theoretical background necessary for understanding many of the techniques used in modern LLMs. It's a valuable resource for graduate students and researchers looking to deepen their understanding of the statistical underpinnings of language models. It is more theoretical and serves as a strong reference for advanced learners.
A beginner-friendly guide to using ChatGPT. is ideal for high school students and those new to generative AI who want a straightforward introduction to interacting with models. It focuses on practical usage and good starting point before diving into more complex prompt engineering concepts.
Examines the global AI landscape, with a focus on the rise of AI in China and Silicon Valley. It explores the implications of AI development for businesses, governments, and society, providing insights into the future of AI Assistant technology.

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