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    Course Outline
Module 1: Introduction to AI in Logistics and Supply
- Understanding Artificial Intelligence: concepts and applications
 - AI in logistics and fuel distribution: opportunities and impact
 - No-code AI tools: Excel AI, ChatGPT, Power BI, and others
 - Practical examples from the transportation and fuel industry
 
Module 2: Structuring and Analyzing Operational Data
- Identifying key logistics and supply datasets (routes, tanks, deliveries)
 - Organizing volumetric control and inventory data for AI use
 - Data cleaning, formatting, and validation in Excel
 - Creating dynamic tables and pivot charts for insight generation
 
Module 3: AI-Assisted Forecasting for Fuel Demand
- Understanding demand forecasting and influencing variables
 - Using Excel’s AI features and ChatGPT for predictive analysis
 - Forecasting short-term (1–2 week) fuel demand trends
 - Practical exercise: building a simple forecast model with existing data
 
Module 4: Route Planning and Resource Optimization
- Key concepts in route optimization and scheduling
 - Using AI tools to suggest optimal routes and delivery sequences
 - Applying Excel and ChatGPT for route planning with real constraints
 - Hands-on activity: generating route options for delivery units
 
Module 5: Cost Estimation and Logistics Optimization
- Identifying cost drivers: distance, tolls, fuel consumption, freight
 - Using AI models to estimate logistics costs
 - Comparing manual vs. AI-assisted cost planning
 - Building cost calculation templates with dynamic inputs
 
Module 6: Dashboards and KPI Visualization
- Introduction to Power BI and Excel dashboards
 - Designing visual reports for logistics and supply KPIs
 - Integrating data from volumetric control systems
 - Hands-on: creating a real-time logistics performance dashboard
 
Module 7: Integrating AI into Logistics Workflows
- Automating repetitive reporting and data consolidation tasks
 - Using Power Automate or Excel macros for task automation
 - Creating alert systems for inventory or delivery thresholds
 - Practical example: AI-based alert for tank refill scheduling
 
Module 8: 90-Day AI Adoption Plan for Logistics and Supply
- Building a step-by-step AI implementation roadmap
 - Identifying pilot use cases and success metrics
 - Scaling AI-assisted workflows across teams
 - Establishing continuous improvement and knowledge-sharing practices
 
Summary and Next Steps
Requirements
- Basic proficiency with Microsoft Excel or Google Sheets
 - No prior experience with Artificial Intelligence required
 
Audience
- Logistics and supply professionals in the fuel transportation and sales industry
 - Operations and inventory coordinators
 - Supervisors and planners managing fleet routes and fuel delivery
 
             14 Hours