AI Courses for K-12
AI training for districts — compliance, child safety, instructional design, and the professional development that reaches every teacher.
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The Short Answer
ibl.ai publishes ten AI courses for k-12, 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 k-12?
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.
The K-12 AI Compliance Stack: FERPA, COPPA, and CIPA
The three federal rules governing AI in a district, what each requires of a vendor, and the deployment architecture that satisfies all three at once.
Safe AI Tutoring for Minors: Guardrails and Escalation
Building a tutoring agent for children — content moderation, self-harm escalation, grooming-pattern detection, and the mandatory-reporter workflow behind it.
AI Lesson Planning Aligned to State Standards
Generate standards-aligned lessons that survive a curriculum audit — grounded on your state's standards, your adopted materials, and your scope and sequence.
AI in the IEP Process: Drafting, Compliance, and the Human Signature
Cut IEP paperwork without ceding a legally binding decision — drafting present levels, goal writing, and the IDEA requirements no agent can satisfy for you.
Academic Integrity and Assessment in K-12
What to do when every student has a writing machine — grade-band policy, assessment redesign, and why detection tools create more problems than they solve.
Teaching AI Literacy: A K-12 Scope and Sequence
A vertically-aligned AI literacy progression from elementary through high school — what to teach at each band, and the activities that make it concrete.
District AI Procurement: Evaluating Vendors and Contracts
A procurement process a school board will approve and a privacy officer will sign — evaluation rubric, contract clauses, and the questions vendors dodge.
AI for Family Communication and Translation
Reach every family in their own language — translation quality, tone, cultural appropriateness, and the legal obligations translation triggers.
Data Governance for District AI: From SIS to Agent
The data plumbing behind district AI — rostering, identity, retention, and the governance that stops an agent reading records it should never see.
Training Every Teacher on AI in One Semester
A district-scale professional development plan — cohort structure, coaching model, artifacts, and the measurement that tells you whether it worked.
Which frameworks and regulations do these courses cover?
Across the k-12 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 k-12?
10 courses covering 1EdTech OneRoster, 1EdTech interoperability, CIPA, COPPA, CTE frameworks, District academic integrity policy and more — for example: The K-12 AI Compliance Stack: FERPA, COPPA, and CIPA; Safe AI Tutoring for Minors: Guardrails and Escalation; AI Lesson Planning Aligned to State Standards. 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 k-12 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 k-12 teams that cannot send work to a public AI tool.
How much does AI training for k-12 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 k-12 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 K-12 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.