AI 101 for teachers — free, and practice-oriented.
Two structured programmes that take teachers from foundational understanding to confident implementation. Eight modules each, built for real classrooms rather than for theory.
A structured, practice-oriented programme that guides teaching staff from foundational understanding to confident implementation. Educators explore what AI is and how institutional policies and real-world cases shape its use, then move into pedagogical opportunities and concrete classroom applications.
It supports instructors in designing AI-integrated activities, addressing ethical, legal and equity considerations, and onboarding students responsibly — culminating in building, implementing and continuously improving an AI-enhanced course.
Equips teachers to introduce AI in age-appropriate, pedagogically sound ways. The programme begins with core concepts, policies and classroom-relevant cases before exploring how AI can support teaching and learning across subjects.
Teachers learn to design engaging AI-supported activities, address ethics, legality and fairness, and guide students toward responsible use — then build and refine their own AI-enhanced course through implementation and evaluation.
Eight modules, in the order you would teach them.
The full course is titled AI for Teaching and Learning in Higher Education. It runs from vocabulary and policy through to a course you have redesigned yourself and evaluated with your own students.
What AI is and is not, in the vocabulary an educator actually needs — AI, machine learning, generative AI — then how institutional policy and real cases shape what you may do with it.
- Key terminology for educators
- AI in a fast-moving world
- Institutional policy and case studies
How AI changes what students need to learn. Critical AI literacy, spotting and correcting a hallucination, and prompt engineering taught through weak-versus-strong worked examples.
- Shifts in the skills students need
- Detecting and correcting hallucinations
- Prompt engineering fundamentals
AI as a co-teacher: generating examples, explanations and simulations, and assisting with formative feedback — walked through step by step, including where the instructor must intervene.
- Examples, explanations, simulations
- Formative feedback support
- A five-step classroom sequence
Four assignment templates you can lift straight into a course, each with an applied example from a different discipline — sociology, microeconomics, educational psychology, media.
- AI-supported drafting and revision
- AI-assisted problem exploration
- Research starter and creative production
Who owns AI-generated content, what happens when a citation is fabricated, how to cite an AI tool, and the FERPA and GDPR essentials that apply the moment student work meets a model.
- Copyright and intellectual property
- Citing AI tools correctly
- FERPA and GDPR essentials
How to set expectations students actually follow: a course-specific policy, concrete acceptable and unacceptable examples, and low-stakes practice that models responsible use.
- A course-specific AI policy
- Acceptable vs unacceptable uses
- Evaluating output for accuracy and bias
A design workshop, not a lecture. Five steps from course goals to aligned assessment, then you redesign one real module or assignment with guidance and peer review.
- Five-step course design workshop
- Redesign one module with guidance
- Peer review and sharing
Running it for real: gathering feedback that tells you something, measuring learning impact rather than satisfaction, and improving the design before the next cohort.
- Pulse checks, micro-surveys, focus groups
- Measuring learning impact
- Iterating for the next semester
Free of charge. Work through it at your own pace, or run it as staff development for a whole department.
Request accessCurriculum built for the age of AI.
Beyond the free courses, we co-create AI-native course content with educators and subject-matter experts.