Data-driven optimization isn’t just theory—it’s a competitive advantage. This short course equips data analysts with practical optimization techniques that deliver measurable business impact.
Learners will build routing models to reduce logistics costs, implement elasticity-driven dynamic pricing strategies, and evaluate solution robustness under demand uncertainty. The course blends hands-on Gurobi optimization with Excel-based simulations to ensure skills translate directly into real-world ROI.
By the end of this course, you will be able to:
Apply mixed-integer programming to minimize logistics costs under delivery constraints
Build price-elasticity models that simulate dynamic pricing scenarios
Evaluate optimization sensitivity to demand forecasting errors
Validate pricing compliance with business guardrails
This course is unique because it combines hands-on Gurobi modeling with real Excel-based simulations, delivering immediately applicable skills that translate into measurable ROI.
To be successful in this project, you should have a background in basic statistics, Excel proficiency, and familiarity with business analytics concepts.
Overview
Syllabus
- Module 1: Supply-Chain Optimization - Foundation
- Learners will apply mixed-integer programming to minimize logistics costs under delivery-time constraints and report savings %.
- Module 2: Dynamic Pricing - Core Application
- Learners will build a price-elasticity model and simulate revenue impact of dynamic-pricing rules, achieving ≥5% projected uplift.
- Module 3: Pricing Constraint Systems - Strategic Implementation
- Learners will evaluate compliance with pre-set pricing guard-rails (floor/ceiling) and adjust rules accordingly.
- Module 4: Sensitivity Analysis - Assessment
- Learners will evaluate sensitivity of the optimized plan to demand-forecast errors using a what-if analysis.
Taught by
Hurix Digital