Learning Path

Learning Path

The full VizLearn curriculum as one ordered journey — from how a program executes all the way to distributed consensus. Lit lessons are live; the rest are on the way.

28 / 121 lessons live

01

Foundations

How a program actually executes — the language every later line speaks.

0/7

Execution model

  • Execution TraceSoon
  • Variables & MutationSoon
  • Arrays & IndexingSoon
  • Loops & InvariantsSoon

Abstraction

  • Recursion & the Call StackSoon
  • Big-O by Counting StepsSoon
  • State MachinesSoon
02

Data Structures

How data is organized, accessed, and changed — and what each choice costs.

7/14

Linear structures

  • Array ListSoon

Hashing

Trees & priority

  • Tree BasicsSoon
  • AVL TreeSoon
  • Red-Black TreeSoon
  • TrieSoon

Graphs & sets

  • Union-FindSoon
  • Graph RepresentationSoon
03

Algorithms

How to search, sort, and optimize over data — by rising thinking difficulty.

10/34

Search patterns

  • Linear SearchSoon
  • Two PointersSoon
  • Sliding WindowSoon

Sorting

  • Heap SortSoon
  • Radix SortSoon
  • Sorting Comparison LabSoon

Trees & graph traversal

  • Tree TraversalSoon
  • Topological SortSoon
  • Connected ComponentsSoon

Shortest paths & optimization

  • DijkstraSoon
  • A* SearchSoon
  • Minimum Spanning TreeSoon

String algorithms

  • KMP String MatchingSoon
  • Rabin-KarpSoon
  • Suffix ArraySoon

Backtracking

  • N-QueensSoon
  • PermutationsSoon
  • Sudoku SolverSoon

Dynamic programming

  • Coin ChangeSoon
  • Longest Common SubsequenceSoon
  • Edit DistanceSoon
  • KnapsackSoon

Bit manipulation

  • Bitwise BasicsSoon
  • Bit TricksSoon

Applied

04

AI / Models

How models compute, learn, and generate — from a single neuron to the Transformer.

7/32

Linear foundations

  • Vectors & Dot ProductSoon
  • Linear ClassifierSoon

Neural networks

  • PerceptronSoon
  • Loss FunctionSoon
  • Softmax & Cross-EntropySoon
  • Training LoopSoon
  • Recurrent Neural NetworkSoon

NLP / LLM internals

  • Word EmbeddingsSoon
  • Attention MechanismSoon
  • Positional EncodingSoon
  • Transformer BlockSoon
  • Next-Token PredictionSoon
  • Decoding StrategiesSoon

Classical ML (survey)

  • Linear RegressionSoon
  • Logistic RegressionSoon
  • k-Nearest NeighborsSoon
  • Decision TreeSoon
  • Support Vector MachineSoon
  • K-Means ClusteringSoon
  • Principal Component AnalysisSoon

Generative & reinforcement

  • AutoencoderSoon
  • Diffusion ModelsSoon
  • GANSoon
  • Q-LearningSoon
  • Policy GradientSoon
05

Computer Systems

How a program runs on real hardware and networks — bottom-up the machine stack.

4/23

Machine representation

  • Binary NumbersSoon
  • Two's ComplementSoon
  • Floating PointSoon
  • Boolean LogicSoon

CPU & memory

  • Instruction ExecutionSoon
  • CPU PipelineSoon
  • Branch PredictionSoon
  • Cache HierarchySoon

Operating systems

  • Virtual MemorySoon
  • Page ReplacementSoon
  • Threads & SynchronizationSoon
  • File SystemsSoon

Networking

  • DNS ResolutionSoon
  • Congestion ControlSoon
  • TLS HandshakeSoon
  • HTTP Request LifecycleSoon

Compilers

  • Lexer & ParserSoon
  • AST & Code GenerationSoon
  • Virtual MachineSoon
06

Data & Distributed

How systems store data and stay consistent across machines — the professional deep end.

0/11

Database internals

  • IndexingSoon
  • B+ TreeSoon
  • LSM TreeSoon
  • MVCCSoon

Distributed systems

  • Consistent HashingSoon
  • Two-Phase CommitSoon
  • Raft ConsensusSoon

Capstones

  • URL → Rendered PageSoon
  • SQL Query → Disk ReadSoon
  • Handwritten Digit → PredictionSoon
  • Message → Distributed ConsensusSoon