Learning Path
The full VizLearn curriculum as one ordered journey — from how a program executes all the way to distributed consensus.
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From executable code and shared Git history to production systems and distributed consensus.
Foundations
How a program actually executes — the language every later line speaks.
Data Structures
How data is organized, accessed, and changed — and what each choice costs.
Linear structures
Algorithms
How to search, sort, and optimize over data — by rising thinking difficulty.
Sorting
Shortest paths & optimization
Backtracking
Bit manipulation
Trees & graph traversal
String algorithms
Dynamic programming
Git & Version Control
How code changes become shared, navigable history — from one working tree to a team.
Repository foundations
Collaboration & releases
Branches & integration
History & recovery
Computer Systems
How a program runs on real hardware and networks — bottom-up the machine stack.
Networking
Finale — capstone
Machine representation
Operating systems
Data & Distributed
How systems store data and stay consistent across machines — the professional deep end.
SQL mental models
Distributed systems
Database internals
Finale — capstones
From the math a network runs on to models, training, and agents.
Foundations
How a program actually executes — the language every later line speaks.
Math for AI
The first cross-domain route — just the math a neural network runs on, ending at a real prediction.
Seeing the math
Learning is optimization
Finale — capstone
AI / Models
How models compute, learn, and generate — from a single neuron to the Transformer.
Neural networks
NLP / LLM internals
Evaluation & generalization
Generative & reinforcement
Training dynamics
Classical ML (survey)
AI Agents
How an LLM becomes an agent — the reason-act loop, tools, and a context that must be managed.