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Course Outline

Introduction to AI in Supply Chain and Logistics

  • Current trends in intelligent logistics systems
  • Comparing AI with traditional analytics in supply chain management
  • Essential technologies and platforms

AI for Demand Forecasting

  • Applying machine learning to time-series forecasting
  • Managing seasonality and trend elements
  • Enhancing prediction accuracy through historical data analysis

Inventory Optimization and Replenishment

  • Predicting stock levels using AI
  • Calculating safety stock and reorder points
  • Integrating AI with ERP and WMS systems

Route Optimization and Fleet Intelligence

  • Shortest path algorithms and delivery route planning
  • Dynamic route planning considering traffic conditions
  • AI-assisted transport scheduling

Warehouse Automation and Robotics

  • Automating picking, sorting, and storage with AI
  • Utilizing computer vision for shelf monitoring
  • Coordinating operations with AGVs and robotic arms

Real-Time Analytics and Dashboarding

  • Creating live dashboards with Tableau and Python
  • Tracking KPIs via real-time data streams
  • Implementing alerts and exception handling mechanisms

Case Study and Capstone Project

  • Evaluating a multi-node supply chain scenario
  • Implementing forecasting and routing models
  • Developing a data-driven logistics optimization strategy

Recap and Future Steps

Requirements

  • Familiarity with core supply chain or logistics operational processes
  • Practical experience utilizing data analysis or business intelligence platforms
  • Foundational knowledge of programming or scripting languages

Target Audience

  • Supply chain analysts
  • Logistics managers
  • Industrial planners
 21 Hours

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