Academic programs are the School’s structured study pathways. Each program is a defined sequence of subjects built for a particular professional context rather than a general survey of artificial intelligence. All are non-degree professional-learning programs subject to human academic review.
Five programs are offered. They differ in the tasks they prepare you for, not in difficulty tier, so the right choice follows from the work you actually do rather than from how advanced you consider yourself.
Artificial Intelligence Foundations
The entry program, and the one most learners should start with regardless of seniority.
Foundations covers what these systems are, how they work in outline, and why that matters practically. It examines the history of the field to explain why current systems look the way they do, the mechanics of machine learning at conceptual level, and the specific reasons generative models produce fluent text without verifying it. It establishes the vocabulary the other programs assume.
The core competency built here is evaluative rather than operational: the ability to look at AI output and form a reasoned view about whether it can be relied upon. Learners finish able to explain, to a non-technical colleague, what a given tool is doing and where it will fail. Relevant subjects are listed in the course catalog.
AI for Research
Built for researchers, doctoral candidates, and research staff integrating AI into method.
This program treats AI as an instrument subject to methodological scrutiny like any other. It covers literature search and review support, source verification, evidence organization, academic writing assistance, and the disclosure requirements that apply when AI has contributed materially to a research output.
The central problem it addresses is fabricated citation. AI systems generate references that are correctly formatted, plausibly titled, attributed to real authors in relevant fields, and entirely nonexistent. The program teaches verification as a mandatory step rather than a precaution, and covers how to document AI contribution so that a reviewer can assess it. Related institutional work is published through the Research Center and KBA13 Publishing.
AI for Education
Built for lecturers, teachers, curriculum designers, and academic administrators.
The program covers AI-assisted teaching preparation, material development, differentiated explanation, and feedback support, alongside the harder institutional questions: assessment integrity when every student has access to generative tools, what constitutes legitimate student use, how to design assessment that remains meaningful, and what an institutional policy should actually say.
It deliberately avoids both available extremes. Prohibition is unenforceable and teaches students to conceal use. Unrestricted permission abandons the assessment of individual capability. The program works through the harder middle position, which requires redesigning what is assessed rather than policing how it is produced.
AI for Government
Built for civil servants, policy analysts, and public-sector professionals.
Public-sector AI use carries obligations that private use does not: accountability for decisions affecting citizens, transparency, records requirements, procurement discipline, and data protection under law. The program covers AI-assisted policy analysis, drafting, document review, and consultation processing, always within those constraints.
Substantial attention goes to what should not be automated. Discretionary decisions affecting individual rights, entitlements, or legal status require human reasoning that can be explained and challenged. Teaching officials to recognize that boundary is more valuable than teaching them to draft faster. Analytical governance requirements overlap with those taught by the School of Intelligence & Strategic Studies.
AI Strategy and Innovation
Built for professionals responsible for how AI is adopted across an organization rather than in their own work.
The program covers readiness assessment, identifying which functions genuinely benefit, workflow redesign, capability building, governance structures, and evaluation of whether an adoption actually delivered. It treats AI adoption as an institutional change problem in which the technology is rarely the constraint.
The recurring finding is that organizations attempt to automate processes they have never documented, and that clarifying the process delivers most of the benefit before any tool is introduced. Learners are taught to reach and defend the conclusion that a given function should not be automated. Institutional implementation support is delivered separately by KBA13 Consulting and the AI Laboratory.
Common conditions
Every academic program is non-degree. Completion confers no academic credit, SKS, ECTS, degree, or government accreditation. Where a program leads to a credential, requirements and verification are set out under professional programs.
Every program is knowledge-first: written explanation, worked examples, exercises on real tasks, and assessed applied work. Video is supplementary.
Every program requires human academic review. No assessment outcome or certificate is generated automatically, and no AI-generated factual claim enters assessed work unverified.
Every program teaches responsible use inside method rather than as a separate module, on the principle that governance treated as an afterthought becomes paperwork.
Choosing a program
Take Foundations first unless you already understand why these systems fabricate. Then take the program matching your work: research method, teaching and assessment, public policy, or organizational adoption.
Senior leaders who need framing rather than operational skill are usually better served by the executive programs, which are compressed and decision-focused. Practitioners who want a documented credential should read the certificate tracks under professional programs and work backwards to subjects.
Organizations training a team should consider a private cohort, which allows applied work to address the organization’s own processes. Enquiries go through the proposal request process. The School’s scope and position are set out on the about the School page, and practical tooling is covered under AI tools.