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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

Skills you'll practise

QUBO FormulationSimulated AnnealingBenchmarkingD-Wave IntegrationVisualization

Practice data included

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

How this certificate is scored

Your certificate shows how many of your written answers met the rubric below, checked by an AI grader. Anyone who checks your certificate sees it.

  • You answer 6 short questions, one for each module, in your own words (at least 40 words each).
  • An AI grader checks each answer against what its module asks for: it must answer the question, use the course's practice case specifically, and be correct.
  • To pass, at least 5 of the 6 answers must meet that bar. The certificate says the answers were graded by AI.

The rubric

  1. Module 1, Foundations: Brute-force QUBO solver + energy landscape.
  2. Module 2, QUBO Formulation: Feature selection + graph partition QUBOs.
  3. Module 3, Use Case Lab: Problem-specific QUBO (student choice).
  4. Module 4, Annealing Solver: SA solver with convergence analysis.
  5. Module 5, Pipeline App: Interactive Next.js dashboard.
  6. Module 6, Production & D-Wave: Benchmarks + portfolio piece.

What you walk away with

Shareable portfolio

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

Everything you build

Download all your work as a ZIP file. It is yours to keep.

Module walkthrough

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

Ready to start Quantum Optimization for AI?

First course free. $20 per course after that.