AI Courses for Higher Education
AI training for the people who actually run a campus — advising, enrollment, faculty development, research administration, and the policy that governs all of it.
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The Short Answer
ibl.ai publishes ten AI courses for higher education, each a complete specification — module outlines, learning outcomes, assessment design, hands-on labs, and cited primary sources. Request access to run one with your cohort. They run on infrastructure where you own all the code and the data, model-agnostic across any LLM, with no per-seat pricing.
On ibl.ai you own all the code and the data, run it model-agnostic across any LLM, and pay with no per-seat pricing — so you can deploy anywhere, from your own cloud to a fully air-gapped network.
Every course publishes its full design below — module outlines, learning outcomes, assessment, and the primary sources it is grounded in.
Which AI courses are available for higher education?
Each course below publishes its complete design — an eight-module outline with objectives and hands-on activities, a capstone, assessment criteria, the agents it uses, and the primary sources it is grounded in. Open any one to read the full specification.
FERPA-Compliant AI: Deploying Agents on Student Data
Run AI agents against your SIS and LMS without a vendor ever seeing a student record — the school official exception, vendor DPAs, and the architecture FERPA implies.
AI Academic Advising at Scale: Design and Guardrails
Build an advising agent that handles degree audits and registration at 20,000-student scale without ever giving a student wrong graduation advice.
Enrollment and Yield AI: Agents Across the Funnel
Deploy AI across inquiry, application, admit, and melt — where agents lift yield, where they damage trust, and how to keep the funnel on infrastructure you own.
AI Tutoring That Improves Outcomes, Not Just Engagement
Design a tutoring agent that produces measurable learning gains — Socratic scaffolding, answer-withholding, misconception detection, and honest outcome measurement.
Assessment Redesign for the AI Era
Detection does not work. Rebuild assessment around what AI cannot fake — process, oral defense, local context, and in-class artifacts — with department-ready rubrics.
Writing a Campus AI Policy That Survives Accreditation
Draft institutional AI policy a regional accreditor, a general counsel, and a faculty senate will each accept — with the governance to keep it current.
RAG on Institutional Knowledge: Catalogs, Policies, Handbooks
Retrieval-augmented generation over the documents a campus runs on — chunking a catalog, versioning policy, and stopping the agent citing a 2019 handbook.
AI for Research Administration: Grants, IRB, and Compliance
Use AI across proposal development, IRB review, and post-award compliance without exposing pre-publication research or violating sponsor terms.
The Campus AI Cost Model: Per-Seat vs Owned Infrastructure
The real arithmetic of campus AI — per-seat licensing at 20,000 students versus token pricing versus self-hosting, with a model you run on your own headcount.
Faculty AI Literacy: A Six-Week Teach-the-Teacher Program
A ready-to-run faculty development program — six sessions, artifacts, and a facilitator guide — that moves a department from anxiety to designed AI use.
Which frameworks and regulations do these courses cover?
Across the higher education catalog, courses are grounded in the primary text of each of the following — the regulation or standard itself, not a summary of it.
What ships with every course?
Facilitator guide
Session-by-session running order, discussion prompts, and the questions that reliably derail a room.
Learner workbook
Exercises, checklists, and the templates each module's activity produces.
Hands-on lab environment
A sandboxed ibl.ai deployment so exercises run against real agents, not screenshots.
Assessment bank
Scenario questions and rubric criteria mapped to each stated learning outcome.
Source bibliography
Every primary regulation and standard cited on this page, linked and dated.
Why run AI training on a platform you own?
You own the course, not a licence to it
Course content, learner data, and the platform run inside your perimeter — you own all the code and the data.
Model-agnostic delivery
Run the course's AI components on any LLM — Claude, GPT, Llama, Gemini, Command — and switch anytime.
No per-seat training licences
Usage-based or self-hosted, so cost tracks actual use rather than headcount.
Deploy anywhere
Cloud, private VPC, on-premise, or fully air-gapped — including for cohorts that cannot use public AI tools.
Frequently asked questions
What AI courses does ibl.ai offer for higher education?
10 courses covering 34 CFR Part 99, Academic integrity policy, FERPA, IRB / Common Rule, ISO/IEC 42001, ITAR and more — for example: FERPA-Compliant AI: Deploying Agents on Student Data; AI Academic Advising at Scale: Design and Guardrails; Enrollment and Yield AI: Agents Across the Funnel. Each publishes its full design: modules, learning outcomes, assessment, and the primary sources it is grounded in.
How do we get access to these courses?
Request access and we will set it up for your cohort — hosted by ibl.ai, or running against your own deployment. Tell us which courses, the group size, and whether it needs to run inside your own perimeter.
Can we run higher education AI training on our own infrastructure?
Yes. ibl.ai is model-agnostic and deploy-anywhere — cloud, private VPC, on-premise, or fully air-gapped — and you own all the code and the data. Cohort data and anything learners upload stay inside your perimeter, which matters for higher education teams that cannot send work to a public AI tool.
How much does AI training for higher education cost?
There is no per-seat pricing — you pay for usage, or self-host and pay only for the infrastructure, so a large rollout does not cost one licence per person. 1.6M+ users across 400+ organizations run the platform this way, including NVIDIA, MIT, and Syracuse University.
Who are these higher education courses written for?
Practitioners rather than general audiences — each course names its audience and prerequisites explicitly, and levels range across foundational, intermediate, advanced.
Request access to the Higher Education courses
Tell us about your cohort and we will confirm timing — or discuss running any of these against your own ibl.ai deployment, where you own all the code and the data.