3D Operating Systems

Build your 3D AI Workflow with the Operating Systems

You don't just want to solve ONE problem. You want to ARCHITECT complete systems.

This is where you go from "I can build X" to "I can design and deploy end-to-end solutions."

🏗️ 3D Reconstructor OS

The Innovation Engine

From images and point clouds to deployable 3D experiences

Build, reconstruct, and visualize accurate 3D environments from raw data.

 

You will architect:

– Automated photogrammetry pipelines (imagery → 3D city models)

 

– Large-scale reconstruction workflows
(cm-level accuracy at scale)


– Generative AI integration (World Models)
(text-to-3D, image-to-3D, Anything-to-3D)


– Nerf and 3D Gaussian Splatting
(automation, video-to-web)


– 3D modeling + optimization
(mesh generation, Blender automation)

Perfect for: innovators who want to create production-ready 3D environments (Surveyors, GIS Analysts, Construction Engineers, Entrepreneur)

🧩 3D Segmentor OS

The Intelligence Forge

From point clouds to intelligent spatial understanding. Learn how to segment, analyze, and classify 3D datasets using Python.

 

You will architect:

– Object detection systems (LiDAR processing, RANSAC, clustering)

 

– Unsupervised segmentation (DBSCAN, k-means, region growing, SegmentAnything 3D)

 

– Advanced analysis (KD-trees, feature engineering, ML integration)

 

– 3D Machine Learning
(Supervised Systems, Labelling loops)

 

– Production applications (client-server architecture, deployment)

Perfect for: those who want to extract meaning and structure from raw 3D data (Data Scientists, Researchers, Robotics Engineers, Urban Planners)

🧠 3D Deep Learning OS

From neural network theory to production 3D AI

From neural network theory to production 3D AI. Master 3D deep learning to build intelligent models from point clouds and spatial data.

 

You will architect:

– Implement neural networks for 3D segmentation and classification
(ANN, CNN, RNN with spatial focus)

 

– Train and evaluate 3D deep learning models
(point-based, (volumetric / voxel architectures)

 

– Use PyTorch + advanced architectures to build your own 3D AI systems
(KPConv, PointNet++, GrowSP, transformers)

 

– Production systems
(end-to-end deployment, cloud integration)

Perfect for: engineers and data scientists who want to move from 2D AI to 3D AI (ML Engineers, AI Researchers, Data Scientists, Tech Founders)

- General feedback -

I've been a fan of your work for almost 1.5 years now! I just registered for your course yesterday, and after going through the modules, I must say I'm pleasantly surprised! A course like this does not exist, and it's awesome !
Client of the 3D Geodata Academy
Parth Singal
New York University (US)
It's very inspiring to meet an academician like you. Finding laser-focused learning journeys has always been challenging, but you managed to do it brilliantly. There were some tools that I didn't think about the significance of i.e. scalar fields features) and it makes a lot of sense after learning this sort of appliance.
Client of the 3D Geodata Academy
Dilan Oguz
TU Berlin (DE)
The course content has very valuable topics to learn and I am really happy for it. I followed the whole course and I love the fact that I can come back anytime to focus more on parts of the point cloud processing workflow. Particularly the Module 3 to deepen my Segmentation and AI knowledge.
Client of the 3D Geodata Academy
Sabor Hamza
Karlsruhe Institute of Technology (DE)
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