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Graduate

PGDip in Artificial Intelligence in Education (entry in January 2027)

For professionals working in education, policy and technology interested in developing competency as research-informed leaders in the field.

Part time

Opening soon

Applications are expected to open soon. Check this page regularly for updates.

Closed to applications

Expected length
12 months
Expected start date
January 2027
English language level
Standard level required
Looking up at the Radcliffe Camera

About the course

Applicants applying to this course on or before the deadline of 6 November 2026, will be considered for a January 2027 start. The course information on this page is for the 2026-27 academic year. Information for entry in the 2027-28 academic year (starting autumn 2027) is on a separate course page. Please apply for the start date that you would prefer. 

The PGDip Artificial Intelligence (AI) in Education responds to the global need for a credible and prestigious degree qualification designed to provide professionals across education, policy, and the technology industry with critical literacy, research training, and applied expertise to lead AI in education. 

Artificial Intelligence (AI) is rapidly reshaping education at all levels. Yet rarely is such a qualification embedded in the department of education to draw on the expertise of those who understand pedagogical best practice. 

This interdisciplinary course draws on the expertise of Computer Scientists, Engineers and Data Scientists from across the University of Oxford to support the core teaching team in the Department of Education. Drawing on Oxford’s expertise in research, pedagogy, and policy engagement, this course will empower you to set the global standard for rigorous, ethical, and considered practice in AI and education.

Who is the course for?

  • Educators: classroom teachers, school leaders, and higher education professionals who are increasingly required to lead the integration and evaluation of AI-powered tools into pedagogy, assessment, and education systems.
  • Policy-makers and system leaders including professionals in government agencies, local authorities, NGOs, and international organisations responsible for shaping education policy and regulatory frameworks in response to AI.
  • Educational technology (EdTech) professionals including product designers, managers, and strategists seeking to align innovation with sound pedagogy, ethical frameworks, and regulatory requirements.


A key feature of this course is your opportunity to learn alongside professionals from other sectors. The global challenges related to AI in education demand an interdisciplinary, cross-sector approach. You will develop cross-sector understanding of AI in education enhanced through collaborative projects. In addition, as a result of enrolling in this course, you will benefit from:

  • Prestigious, globally recognised degree qualification from the University of Oxford.
  • Applied professional focus with outputs directly applicable to practice (eg. school strategies, policy briefs, product roadmaps).
  • Access to a thriving, global professional network during your course and as alumni. 

On completing your studies, you should feel more confident to lead AI and digital transformation as a research-informed, interdisciplinary and collaborative endeavour. 

Course structure

This section provides an overview of the course structure, while details of the individual course components are provided below.

The course consists of three summatively assessed modules, and a one-week residential which will be formatively assessed. An optional research skills module will be available for the duration of the course and can be studied independently at your own pace.

With the exception of the residential induction week and the independent study, all modules are delivered online through Canvas, the University’s online learning platform. 

Sessions will be pre-recorded and posted weekly, and you will engage with them at your own pace over the week. Typically, each session will consist of a pre-recorded lecture, accompanied by a mix of pre- and post-lecture readings, forum discussions, quizzes and activities. You should expect to spend about ten hours per week engaging directly with the module materials. Module leads will convene a live Q&A session on Microsoft Teams at least once per term. 

Work on your independent study will begin with discussions with your supervisor at the start of the course, and will be your sole focus of the third term and the long vacation. Typically, this will involve engaging in background reading, collecting data (in your school or setting), and writing up.

You will need to be employed, or have regular and practical access as a volunteer, consultant, etc, to an appropriate professional context. Many of the activities will ask you to reflect on the relationship between your learning and that relevant context. Your independent study may focus on your professional context and/or the learners in them.

You will be entitled to attend the department’s regular seminars and weekly public lectures (the latter are streamed live and recorded for viewing later).

Core components

You will attend a residential week and take three core modules. 

Option modules

You will have the opportunity to take a non-assessed module on research skills.

Course details

Entry requirements

For entry in 2026-27

Funding and costs

College preference

Before you apply

Completing your application

Contact details