Help Center

Straight Answers

The questions I hear most, answered the same way I'd answer them on a call.

Getting Started

What is the 3D Geodata Academy?

The Academy is where I teach the full 3D AI chain. Point clouds, photogrammetry, neural rendering, spatial AI. Structured paths, real projects, and a community where I’m active every week.

Which learning path should I choose?

Start with the free mission. It takes you from a raw LiDAR scan to a classified point cloud in 15 minutes. After that you’ll know which path fits you, and I’ll point you to the right track.

Do I need prior programming experience?

Intermediate Python helps. If you’re brand new to Python I include the basics you need for 3D processing. The path adapts to where you actually are.

How long does it take to complete a learning track?

You get clarity from episode 1. Your first working artifact ships in 15 minutes. A focused week full-time covers the accelerator. At 10 hours a week it runs under 30 days. Lifetime access, so you come back whenever you need to.

Programs & Pricing

What's included in The Guild membership?

The 3D AI Architect Program has three tiers. Foundation (EUR 1,497) is the full path at your own pace. Professional (EUR 2,497) adds deep-dive tracks, .exe apps, and access to my services. Architect (EUR 3,997) adds private sprints with me and portfolio reviews. All lifetime. All founding prices.

Can I purchase courses individually?

Yes. Every course in the Library can be bought individually. If you want more than two or three, the Library subscription or the full Program is cheaper.

Is there a free trial available?

Yes. The free mission gives you 4 full episodes, real datasets, a pre-configured stack and the first chapters of my ebook. No credit card. That’s the best way to see how I actually teach.

What's your refund policy?

90-day refund after applying the material. Use the work. If it doesn’t deliver, email me and I send the money back. No forms.

Technical Requirements

What software and tools do I need?

Python 3.10+, VS Code, Open3D, CloudCompare, a handful of packages I pin in the stack. Everything is open source. Every course lists the exact setup up front.

What are the hardware requirements?

16GB RAM is a sane minimum today. For deep learning episodes a CUDA GPU helps but isn’t mandatory. I provide Colab notebooks (free GPU) for everything heavy.

Can I use Mac or Linux?

Yes. Windows, macOS and Linux all work. Platform-specific notes where they matter.

Do you provide datasets for practice?

Yes. Every course comes with real datasets. LiDAR, photogrammetry, and the kind of noisy scans you actually meet in the field. No toy data.

Learning Experience

How are the courses structured?

Each course is videos plus notebooks plus a real project. Theory lands only when it turns into code. I track your progress so you always know the next step.

Can I get help when I'm stuck?

Yes. The Spatialetics community is where I answer questions every week. Program members get priority. Library students get forum access and docs. Architect tier gets a private channel with me.

Are there certifications?

Yes, completion certificates. Share them on LinkedIn if you want. Honestly, the artifacts you build matter more than any badge.

How often is content updated?

Updates land as the field moves. Free for existing students, forever. Major new modules roughly every quarter.

Community & Support

How can I connect with other learners?

The Spatialetics community is where students share work, ask questions, and hire each other. I’m active there. Program members get study groups and occasional live sessions.

Can I showcase my projects?

Yes. The Use Cases page is built from student work. Submit yours in the community. The best ones become full case studies.

Do you offer corporate training?

Yes. See the Enterprise page. I run intensive sprints, team programs and multi-month capability builds. Email me and we’ll scope it.

How do I stay updated with new content?

Sunday newsletter for the weekly note. Blog for deep dives. Spatialetics community for real-time conversation.

Book & Resources

What's in the '3D Data Science with Python' book?

3D Data Science with Python, O’Reilly. 18 chapters, 420 pages, 200+ code examples, real case studies. The full chain from raw point cloud to deployed AI system.

Is the book included with course purchases?

The book stands on its own. It pairs well with the Program, but you don’t need the Program to get full value out of it.

Can I access the book digitally?

PDF, EPUB, and paper. Whatever fits how you read.

How is the Library different from the courses?

PDF, EPUB, and paper. Whatever fits how you read.