Build Spatial AI Systems You Actually Ship
I'll take you from raw point clouds to a deployed app in under 30 days. No black boxes. No rented infrastructure. Just code you own and judgment you keep.
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Meet Dr. Florent Poux
Author & Researcher
O'Reilly author, ISPRS Dangermond awardee, 50+ peer-reviewed papers.
Industry Leader
Engineers from Meta, Airbus, Trimble and CNRS run my code in production.
Field Pioneer
15 years in the field. From archaeology to LiDAR to neural architectures.
Founder
I build the tools I teach. My stack is what I actually ship, not what looks good on a slide.
Three entry points. Pick the one that fits.
Learn
Build
Scale
The Learning Path
Four doors. Start anywhere.
Professionals at Leading Companies
Trust Our Training
Real results from real professionals.
Researcher
Technical University of Madrid
ML Engineer
PropTech Startup
Civil Engineer → Spatial AI Lead
Industry Updates
3D Point Cloud Labeling from Photos with Python (and why AI can’t design it for you)
3D Pipeline Architecture: A Founder’s Blueprint
It was a Tuesday when I got the call. A €40,000 project was completely stalled, burning cash every hour. The...
Multi-View Engine for 3D Generative AI Models (Python Tutorial)
Generate perfect multi-view 3D training data without cameras. Mathematical algorithms create optimal viewpoints for Gaussian Splatting in minutes, not days....
3D Scene Graphs for Spatial AI with NetworkX and OpenUSD
Learn to build intelligent 3D scene graphs from point clouds using Python, NetworkX, and OpenUSD. Complete tutorial access with LLM...
3D Reconstruction Pipeline: Photo to Model Workflow Guide
The 3D Reconstruction pipeline, to get from 2D photographs to 3D models follows a structured path. This path consists of...
Synthetic Point Cloud Generation of Rooms: Complete 3D Python Tutorial
Frequently Asked Questions
What's the difference between the Program and the Library?
Do I need a PhD or advanced mathematics background?
Can I use this for commercial projects?
Yes. Full commercial license included with the Program. Use all code in your products, consulting work, or internal systems. Only restriction: you can’t resell the course itself as training material.
How long does it take to complete the Program?
Is there a refund policy?
What tech stack do you use?
Python, PyTorch, Open3D, NumPy for core AI. FastAPI, Docker, React Three Fiber for deployment. Everything is production-grade and industry-standard. Every system includes complete code repositories and deployment scripts.
Do I need a GPU?
Recommended for deep learning systems (4, 5, 6). I provide Google Colab notebooks (free GPU) for all GPU-intensive modules. You can complete the entire program without owning a GPU.
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