LEARNING PATH 03
Prepare for AI systems
Use a model. Understand the systems that run it.
Start with complexity, memory hierarchies, CPUs, and concurrency before studying AI execution systems. See where model theory fits into the wider learning path.
For learners interested in the computers behind AI, retrieval, and inference performance
Read the first lesson →Where should you start when investigating slow inference or retrieval?
Suggested reading order
Check the prerequisites listed in each lesson as you go.
Where this path leads
These lessons are being prepared. Explore their objectives on the map.
- Vectors, Matrices, and Linear MapsKnowledge map
- Conditional Probability, Random Variables, and DistributionsKnowledge map
- Supervised Learning, Models, and Loss FunctionsKnowledge map
- Tokenization, Self-Attention, and TransformersKnowledge map
- Vector Search, Chunking, and Retrieval-Augmented GenerationKnowledge map