AI for Logistics & Supply Chain

Course outline and learning expectations

This is a tutor-led course. The outline shows what your tutor will cover; teaching materials and examinations are provided directly to enrolled students.

What you will learn

• Explain major logistics and supply chain challenges affecting Uganda, East Africa and Africa
• Prepare, clean and explore imperfect logistics, delivery and inventory data
• Represent road and delivery networks using nodes, edges, distances, travel times and operational constraints
• Build and evaluate a simple route-optimisation model for delivery operations
• Create demand forecasts using baseline, time-series and machine-learning methods
• Apply inventory concepts such as service levels, safety stock, reorder points and forecast-driven replenishment
• Build and assess a model for predicting delivery delays without data leakage
• Evaluate AI approaches to informal addresses, geocoding, clustering and dynamic last-mile routing
• Predict warehouse stock levels and identify potential stockout or overstock risks
• Select suitable evaluation metrics for forecasting, classification, regression and optimisation tasks
• Apply privacy, safety, fairness and human-review principles when using operational and location data
• Develop and present a logistics optimisation prototype for a realistic African business context

Modules

1. 1

   African Logistics Context and Data Challenges

   Examine logistics constraints and data realities across Uganda, East Africa and Africa, including incomplete road information, informal addresses and variable operating conditions.

   Regional transport and supply chain contextRoad and location data gapsInformal addressingOperational data sourcesLogistics performance indicatorsData quality, privacy and safety
2. 2

   Route Optimisation Fundamentals

   Model delivery networks and build practical route-planning solutions under realistic business constraints.

   Graph and network conceptsShortest-path methodsVehicle routing problemsCapacity and time-window constraintsOR-Tools and NetworkXRoute validation and human overrides
3. 3

   Demand Forecasting for Supply Chains

   Forecast product, order or shipment demand using transparent baselines, time-series methods and introductory machine learning.

   Forecasting problem definitionTrends and seasonalityMoving averages and exponential smoothingFeature-based forecastingMAE, RMSE and percentage-error measuresForecast uncertainty
4. 4

   Inventory Optimisation

   Connect demand forecasts to practical replenishment and stock-control decisions.

   ABC inventory analysisService levelsSafety stockReorder pointsEconomic order quantityStockout and overstock trade-offsForecast-driven replenishment
5. 5

   Predicting Delivery Delays

   Build models that estimate whether a delivery may be late or how long a delay may be.

   Delay definitions and target variablesRoute, distance and operational featuresClassification and regression approachesMissing dataData leakage preventionModel evaluation and explainability
6. 6

   Last-Mile Delivery Challenges and AI Solutions

   Assess AI-assisted approaches for delivery in dense urban areas, peri-urban communities and locations with informal addresses.

   Geocoding and location descriptionsDelivery-zone clusteringDynamic routingEstimated arrival timesProof-of-delivery dataDriver safety and customer privacyHuman escalation procedures
7. 7

   Warehouse and Stock-Level Prediction

   Use warehouse movement data to anticipate stock levels and support replenishment decisions.

   Receipts, issues and balancesInventory accuracyStock-level forecastingStockout-risk indicatorsAnomaly detectionWarehouse dashboardsModel monitoring
8. 8

   Capstone: Logistics Optimisation Prototype

   Design, build, test and present a delivery route optimiser for a small Kampala-based delivery or courier business.

   Problem definitionData collection and cleaningBusiness and road constraintsOptimisation modelMap or dashboard interfacePerformance testingPrivacy and safety reviewDocumentation and presentation