Phase 01
Foundations
Programming + CS
Goal
Become dangerous with code before touching advanced AI tooling.
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Progress0%
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Start with Phase 01.
Phase 02
Software Engineering
Build reliable services
Goal
Turn AI ideas into maintainable software.
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Phase 03
Math + Machine Learning
Understand the models
Goal
Build enough mathematical intuition to reason about ML systems.
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Phase 04
Deep Learning
Neural networks
Goal
Understand and train modern neural models.
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Phase 05
LLM Engineering
Build with modern models
Goal
Move from model APIs to robust LLM applications.
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Phase 06
Production AI
Ship and operate
Goal
Turn prototypes into reliable systems.
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Phase 07
Proof of Work
Projects + career
Goal
Turn learning into visible evidence.
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How to use it
Learn → build → prove.
01
Follow the phases in order. Open a checkpoint when you're ready to dive deeper.
02
Use the build checkpoints to turn concepts into working projects.
03
Mark progress locally and use the final phase to turn learning into evidence.
Roadmap notes Read the reasoning behind the sequence
How to use this roadmap
Follow the phases in order. Open a checkpoint for its details, use the linked guides when you need more depth, and build at the project checkpoints instead of waiting until the end.
What this path optimizes for
Strong software fundamentals first, then machine learning, LLM engineering, production AI, and a portfolio that proves you can ship.
Progress rule
You do not need to finish every optional topic before moving forward. Finish the core checkpoints, build the projects, and return to specializations when your goals require them.
Checkpoint