Foundations
Python, machine learning, and the engineering practice AI work assumes.
FluxForce Institute for Responsible Engineering
Engineers who can build AI — and prove it’s safe to run.
From Python foundations to production agent systems, taught with the evaluation, governance and sovereignty practice that real deployments demand.
- Practitioner-ledFaculty who ship production AI
- Artifact requiredNo completion-only certificates
- India-wideLive online and on-campus
- Governance built inEvaluation, security, sovereignty
Where do you start?
For college students
Build a portfolio employers can interrogate — foundations through capstone.
For working professionals
Move into AI systems work on evenings and weekends, without a degree detour.
For enterprise teams
Upskill your engineers to build and govern AI without failing an audit.
For executives
Half-day briefings on AI exposure, governance duty and sovereignty options.
What responsible engineering means here
Four disciplines, taught as code
Not a principles page. Each of these shows up in your build, and is assessed.
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01
Evaluation
A golden dataset built from real failures, deterministic assertions, and evals running in CI — so a prompt change cannot silently ship a regression.
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02
Governance
Approval gates where a wrong action is irreversible, confidence thresholds that escalate instead of guessing, and audit trails someone else can read months later.
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03
Security
You attack your own agent first: prompt injection, tool abuse, scope escalation. Everything your system reads is untrusted input.
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04
Sovereignty
Which workloads can leave your boundary and which cannot — open-weight models, residency law, and the cost of running it yourself.
Curriculum
Four tracks
Core AI Engineering
LLM engineering, retrieval, agent systems, and running them in production.
Responsible & Sovereign
Evaluation, governance, red-teaming, local models and data residency.
Applied & Capstone
Industry electives, campus bootcamps, and the assessed capstone track.
Programs
What you can study
Agentic AI for Enterprise Teams
Six weeks for engineering teams, delivered against your own systems and constraints. Same agentic engineering as the open cohort, taught…
AI Capstone + Internship Track
Eight weeks building one substantial system against a real brief, with weekly review and a final defence to a technical…
AI Governance for Boards & CXOs
A half-day briefing for boards and leadership teams: where AI exposure sits, what you are accountable for, what evidence to…
AI Security & Agent Red-Teaming
Three weeks attacking AI systems — your own first. Prompt injection direct and indirect, tool abuse, scope escalation, data exfiltration,…
AI Systems in Production
Six weeks on operating AI systems after launch: tracing, cost control, model routing, incident response, and the deployment patterns that…
Applied AI Electives
Two-week electives applying the core curriculum to one domain — financial services, healthcare, public sector or energy. Same engineering, different…
Cohorts forming
These open as cohorts fill. Register interest and we confirm dates and fees first.
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Register interest
Agentic AI Engineering
12 weeks · Intermediate · Live online
Why FIRE
Taught by practitioners
The curriculum comes from people who ship production AI systems, not from tutorial writers. Every pattern we teach has failed somewhere real first.
Every course ends in an artifact
You leave with working systems on your own GitHub — not a completion certificate and a folder of notebooks.
Governance is built in
Evaluation, guardrails and red-teaming are assessed coursework, not an afterword. That is the whole difference.
FAQ
Before you ask
Do I need an AI background to start?
No, but you need to program. If you write Python confidently, start with LLM engineering or the agentic track. If not, Python for AI Engineering has no prerequisites beyond a programming course.
Is this live or recorded?
Live, with recordings for review. Code review and capstone assessment are live — that is where most of the learning happens.
Do you guarantee placement?
No, and we would be sceptical of anyone who does. We provide portfolio review, interview preparation, and introductions where there is a genuine fit. The artifacts do the work.
Is FIRE an accredited university?
No. FIRE issues certificates of completion backed by assessed artifacts. We are not a university and do not award degrees or diplomas, and we will never imply otherwise.
What do fees look like?
Fee structures are being finalised. Register your interest and you will get the full breakdown before committing to anything.
Can you train my team?
Yes — enterprise cohorts are delivered on-site or virtually, built around your own systems, under your NDA.