Applying quantum machine learning and variational circuits to supply chain demand forecasting problems.
Full-day workshop on quantum-enhanced demand forecasting for logistics. Covers eight algorithm approaches including VQCs, quantum kernels, QBMs, and amplitude estimation applied to SKU-level demand planning, safety stock, and promotional uplift modelling.
Course content is structured into sessions below. Each session is configurable to your organisation's environment, threat model, and objectives.
| # | Session | Topics |
|---|---|---|
| 1 | Classical Forecasting Limits and Quantum Opportunity Where traditional time-series methods break down in logistics demand planning | |
| 2 | Quantum Algorithms for Demand Forecasting Eight approaches from kernel methods to variational circuits |
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| Break | ||
| 3 | Feature Engineering and Data Pipelines for Quantum Models Encoding logistics data into quantum-compatible representations |
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| 4 | Interactive Demonstration Quantum forecasting model construction on a simulated logistics dataset |
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| Break | ||
| 5 | NISQ Constraints and Honest Benchmarks What current hardware can and cannot do for production forecasting |
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| 6 | Integration and Adoption Framework Connecting quantum forecasting research to production planning systems | |
| 7 | Q&A and Action Planning | |
Training courses are designed and delivered by QSECDEF in collaboration with subject specialists. All instructors have direct experience in quantum technologies and security.
Course design and delivery
QSECDEF brings expertise in post-quantum cryptography, quantum computing strategy, and defence-grade security assessment. Our membership spans 900+ organisations and 1,500+ professionals working at the intersection of quantum technologies and critical infrastructure security.
Get in touch to discuss scheduling, group pricing, and how this course can be configured to your organisation's needs.
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