Masterclasses · Intermediate
Machine Learning for Supply Chain
Forecasting, inventory optimisation and control-tower analytics — taught on data that looks like your ERP, not Kaggle.
Planners and supply-chain analysts learn to build and operate ML-assisted planning: demand forecasting with hierarchical reconciliation, safety-stock optimisation, exception intelligence and the change-management to make planners trust the models.
Who it's for
Demand planners, SC analysts, logistics and procurement leads.
Tools & stack
What you'll walk away with
- Build hierarchical demand forecasts and measure them honestly
- Optimise inventory policies against service-level targets
- Design exception-driven control-tower workflows
- Run forecast-value-add reviews that stick
Curriculum
01Forecasting
- Baselines before ML
- Feature-rich models
- Hierarchical reconciliation
- FVA discipline
02Inventory & network
- Safety stock economics
- Multi-echelon views
- Scenario simulation
- Lab: policy tuning
03Control tower
- Exception detection
- Agentic triage patterns
- Planner UX
- Capstone
Pricing
Value-based
Two-part: a one-time enablement fee plus a per-seat rate that falls as the cohort grows.
Indicative rate card · ≈ ₹7,999/hr · $200/hr
Seats limited
Choose a cohort
New cohort dates announced weekly — enrol now and pick your dates with an advisor.
Pay by PO · nothing upfront · net 30 days · GeM & tender-ready
Or reserve a seat online
₹7,999deposit
Reserves your seat & dates. Balance invoiced per your engagement.
Secure · Razorpay · full refund 7+ days before start
Every enrolment includes
- • Qube copilot access throughout
- • All session recordings & materials
- • Graded applied project with review
- • Verifiable certificate on completion
- • 30-day post-programme support
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