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$20

Quantum Optimization for AI

Build a quantum annealing pipeline for combinatorial optimization — choose feature selection or graph partitioning, solve with simulated annealing, and optionally connect to D-Wave hardware.

"Select the optimal 8 features from 30 — annealing beats greedy by 5% accuracy"

6 Modules

Each module builds on the previous one. By the end, you have a complete production system.

  1. 1

    Foundations

    Brute-force QUBO solver + energy landscape

  2. 2

    QUBO Formulation

    Feature selection + graph partition QUBOs

  3. 3

    Use Case Lab

    Problem-specific QUBO (student choice)

  4. 4

    Annealing Solver

    SA solver with convergence analysis

  5. 5

    Pipeline App

    Interactive Next.js dashboard

  6. 6

    Production & D-Wave

    Benchmarks + portfolio piece

Production patterns you'll master

QUBO FormulationSimulated AnnealingBenchmarkingD-Wave IntegrationVisualization

Synthetic data included

  • Classification dataset (30 features)
  • Social network graph (50 nodes)
  • Pre-computed MI scores
  • Correlation matrices
  • Community ground truth

What you walk away with

Shareable portfolio

A public URL showing your module timeline, patterns mastered, and completion status.

All the code

Download everything as a ZIP — pipelines, guardrails, deployment configs. Yours forever.

Module walkthrough

Each module documented with deliverables and the production pattern you implemented.

Ready to build your quantum optimization for ai?

First course free. $20 per course after that.