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