Loading…
FluxForce Institute for
Responsible Engineering
Igniting core…
000%
Programs
Four tracks — foundations, core AI engineering, responsible engineering, and sovereign AI. Every program ends in a working artifact you own.
Four tracks
The curriculum
FIRE runs four tracks. Foundations covers Python, machine learning and the engineering practice AI work assumes. Core builds LLM and agent systems. Responsible Engineering covers evaluation, governance and security. Sovereign AI covers local models, data residency and the trade-offs against frontier APIs.
Most people take one track. Engineers switching into AI usually start in Foundations and finish with the agentic capstone. Enterprise teams typically start in Core or Responsible Engineering, delivered against their own systems.
Every program
Three things, regardless of level.
You build something that runs.
You write the evaluation that proves it works.
You leave with the artifact on your own GitHub, not a completion certificate.
That is deliberate. A certificate says you attended. A working agent with a test harness and a failure analysis says you can do the job — and it is what a technical interviewer will actually ask you to walk through.
Choose your path
Honest terms
We do not guarantee placement, and we would be sceptical of anyone who does. We are not a university and we do not award degrees or diplomas. What we award is a certificate of completion issued by FIRE, and the artifacts you built to earn it.
Tell us your background and we'll point you to the right entry point.