Education
A curriculum you build through
Four tracks, from AI foundations to agentic systems — hands-on, made for working clinicians, and finished with something you built.
A private community of clinicians and health leaders
Where healthcare learns AI.
A private community of clinicians and health leaders — studying the evidence, building the skills, and shaping how AI enters care.
01The shift
The people who built modern AI keep saying the same thing about healthcare.
“The greatest opportunity offered by AI is … the opportunity to restore the precious and time-honored connection and trust — the human touch — between patients and doctors.”
Eric Topol, MD — Deep Medicine, 2019
“AI won’t replace radiologists — but radiologists who use AI will replace radiologists who don’t.”
Curtis Langlotz, MD, PhD — Stanford
“People should stop training radiologists now.”
Geoffrey Hinton — 2016
The prediction missed. The people who kept learning didn’t — that’s the difference AIMOCS exists for.
81%
of US physicians use AI in their work — it was 38% in 2023.
AMA physician surveys · 2023–2026
51.9% → 38.8%
clinician burnout, 30 days after ambient AI documentation — in a 263-clinician, six-system study.
JAMA Network Open · 2026
40–60%
faster prior-authorization turnaround where agentic AI runs the paperwork behind a human gate.
Reported deployments · 2026
02What AIMOCS is
Study the evidence. Build the skills. Know the people.
Case studies
Evidence from real deployments
What actually shipped in clinical settings, what it changed, and what it cost to get right — studied honestly.
Leaders
The people steering the field, on record
Recorded conversations with the clinicians, operators, and researchers deciding how healthcare adopts AI.
03The curriculum
Four tracks, one deliberate progression.
A track isn't content to consume — it's an investment in how you'll practice for the next decade. Each one is hands-on and ends with something you built.
Track 01
Foundations
What AI is, its vocabulary and limits, and how to reason about it in a clinical context.
You buildA plain-language AI brief for your own team.
Track 02
Machine Learning
How models learn from data, where they fail, and how to read the evidence behind a clinical claim.
You buildA trained model on a real clinical dataset.
Track 03
Deep Learning
The architectures behind today's clinical AI in imaging and language — demystified, then built.
You buildAn imaging or language model you fine-tuned.
Track 04
Agentic AI
Systems that act — how autonomous agents work, and how to deploy them safely in real workflows.
You buildA working agent scoped to a clinical task.
Completing all four earns the gold seal — a typographic credential, carried inside the community.
The tracks are being finalized with the founding class — members shape them and enter first. See the full curriculum →
04Membership
When you're ready
Join the people steering AI in healthcare.
Not ready yet? Follow the work — we'll write when there's something worth reading.