As we mentioned last episode, one of the best test spaces for building new AI systems are games. This is because games provide a great framework for an AI to learn an objective and slowly improve. In recent years, AI has made huge strides in games from beating Jeopardy! champions to crushing a five-person team in DOTA 2. Today, we’re going to walk you through creating a Tic Tac Toe bot that uses the minimax algorithm to become undefeatable and we’ll talk about evolutionary neural networks like in SethBling’s MarI/O project. Next week we’ll create our very own game and create an AI to master it!

AIRS is an open source set of online modules and resources in research skills and knowledge. It provides the grounding in research processes with practical tools to support you.

AIRS is a mandatory coursework requirement for Higher Degree Research (HDR) students enrolled in a Doctor of Philosophy (PhD) or Master of Philosophy (MPhil), at the Queensland University of Technology (QUT).

OER Fundamentals are invited to remix this course planning template to design and share their OER project plans, course information and syllabus, and reflection.

aiEDU's AI Toolkits are materials designed to support teachers, parents and other community champions to share the importance of artificial intelligence education and support its adoption in your learning spaces.

The Student Guide to Artificial Intelligence is an initiative of Elon University, in partnership with the American Association of Colleges and Universities (AAC&U). It is a continuation of a 2023 global collaboration that established a statement of principles to guide development of AI policies and practices in higher education. The statement was released at the United Nations Internet Governance Forum in Kyoto, Japan, and was supported by more than 140 higher education organizations, administrators, researchers and faculty members from 48 countries.

This resource includes traditional writing prompts as well as prompts and assignments that utilize AI-generated text. It covers the fields of Creative Writing, Composition, and Business and Technical Writing. 

Artificial intelligence (AI) is increasingly integral to our lives, necessitating proactive education systems to prepare students to be responsible users and co-creators of AI. Integrating AI learning objectives into official school curricula is crucial for students globally to engage safely and meaningfully with AI. The UNESCO AI competency framework for students aims to help educators in this integration, outlining 12 competencies across four dimensions: Human-centred mindset, Ethics of AI, AI techniques and applications, and AI system design. These competencies span three progression levels: Understand, Apply, and Create. The framework details curricular goals and domain-specific pedagogical methodologies.

Grounded in a vision of students as AI co-creators and responsible citizens, the framework emphasizes critical judgement of AI solutions, awareness of citizenship responsibilities in the era of AI, foundational AI knowledge for lifelong learning, and inclusive, sustainable AI design.

AI processes vast information, generates new content, and helps decision-making through predictive analyses. In education, AI has transformed the traditional teacher–student relationship into a teacher–AI–student dynamic.

This shift requires a re-examination of teachers’ roles and the competencies they need in the AI era. Yet, few countries have defined these competencies or developed national programmes to train teachers in AI, leaving many educators without proper guidance.

The AI competency framework for teachers addresses this gap by defining the knowledge, skills, and values teachers must master in the age of AI. Developed with principles of protecting teachers’ rights, enhancing human agency, and promoting sustainability, the publication outlines 15 competencies across five dimensions: Human-centred mindset, Ethics of AI, AI foundations and applications, AI pedagogy, and AI for professional learning. These competencies are categorized into three progression levels: Acquire, Deepen, and Create.

As a global reference, this tool guides the development of national AI competency frameworks, informs teacher training programmes, and helps in designing assessment parameters. It also provides strategies for teachers to build AI knowledge, apply ethical principles, and support their professional growth.

World Education's AI for Learning and Work initiative is dedicated to exploring the intersection of artificial intelligence and education, and how it can shape the future of the way we live and work. On this page, you can access open resources, professional development offerings and opportunities to get involved.

Computer science is about so much more than coding! Learn about AI, machine learning, training data, and bias, while exploring ethical issues and how AI can be used to address world problems.

AI and education are not just topics for industry. The education system should be prepared to identify how best to make use of AI in the classroom, reassure teachers, make them responsible users and start an effective teacher-training program. The goal of this textbook is to give teachers the knowledge necessary for deciding if, where and how AI can help.
• How can artificial intelligence impact learning and teaching in my classroom?
• Can it help me do what I want to do with my students?
• How can it change the dynamics and interactions I have with my students?
• How do I even know when it is being used correctly or incorrectly?
• And, what should I be aware of if I want to put it to good use?
Available in English, French, German, Italian, and Slovenian

This free webinar explored real-world applications of AI in education, from designing digital learning experiences to content creation, instructional design, assessment, and accessibility. It also addressed practical and ethical considerations involved in implementing AI-driven solutions.

Learn about the implementation and practical aspects of Artificial Intelligence and how to write a plan for applying AI in your own organization in a step-by-step manner.

This course is not about difficult algorithms and complex programming; it is a course for anyone interested in learning how to integrate AI into their own organization.

To understand how current Artificial Intelligence applications can be successfully integrated in organizations, we look at different examples. For instance, how ING uses reinforcement learning for personalized dialog management with its customers or how Radboud UMC uses diagnostic image analysis to discover early stages of infectious diseases.

As part of our two-course program ‘AI in Practice’, this course will guide you in the practical aspects of applying AI in your own organization. You will examine typical applications of AI in use already and learn from their experience. These include challenges of implementation, lifecycle aspects, as well as the maintenance and management of AI applications.

The course presents a variety of case studies from actual situations in public organizations and private enterprises in the healthcare, financial, retail and telecommunications sectors. These include Radboud UMC, the Municipality of Amsterdam, ING, Ahold Delhaize and KPN.

‘AI in Practice – Applying AI’ gives you the ammunition to understand the practical aspects required for the implementation of a variety of AI applications in your organization.

This course, AI in Practice: Preparing for AI, is the 1st course of the online education program AI in Practice. The course gives you a kaleidoscope of examples of applications of AI in various organizations, outlines the state of the art in modern AI research, and provides practical tools for integrating AI into your own organization. The program AI in Practice is built from two initial courses, AI in Practice: Preparing for AI and AI in Practice: Applying AI.

The AI in Practice: Preparing for AI course is designed for people who want to apply AI in their own practical situation.

For the experienced manager who wants to know what AI can do for her own organization.
For the data analyst or business consultant who wants to understand how AI can be applied in the business processes of the company for which they work.
For the student who wants to understand how the results of AI research can be translated into practical applications.

Garnet Valley School District in PA established a deep commitment to open education when it first joined the #GoOpen Network over eight years ago to advance an OER initiative. Still on an innovative journey to transform teaching and learning, the district’s Director of Technology and Online Learning and Founder and Executive Director of nonprofit Edvative Learning, Sam Mormando is actively exploring the rapidly evolving landscape of AI technology and reflecting on ways it may be advantageous for education, and specifically, for OER. 

Learn the fundamentals and principal AI concepts about clustering, dimensionality reduction, reinforcement learning and deep learning to solve real-life problems.

Learn the fundamentals of machine learning to help you correctly apply various classification and regression machine learning algorithms to real-life problems.

A one-stop shop to get started on the key considerations about data for AI! Learn how crowdsourcing offers a viable means to leverage human intelligence at scale for data creation, enrichment and interpretation, demonstrating a great potential to improve both the performance of AI systems and their trustworthiness and increase the adoption of AI in general.

Description: Learn how conservationists use AI image recognition to save time identifying how and where to protect endangered species. Build your own species-identifying AI system
Skills/knowledge you'll gain: Conservation
Length: 1-2 hours

Curriculum aligns to:
- NGSS Engineering standards
- ISTE standards
- Common Core ELA/Literacy standards
- Also maps to CSTA standards