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Duration 14 hours
Course Outline
Module 1: Introduction to AI in Logistics and Supply
- Fundamentals of Artificial Intelligence: key concepts and applications
- The role of AI in logistics and fuel distribution: potential opportunities and impact
- Overview of no-code AI tools: Excel AI, ChatGPT, Power BI, and others
- Real-world examples from the transportation and fuel sectors
Module 2: Organizing and Analyzing Operational Data
- Identifying critical logistics and supply datasets (routes, tanks, deliveries)
- Structuring volumetric control and inventory data for AI processing
- Cleaning, formatting, and validating data within Excel
- Generating insights through dynamic tables and pivot charts
Module 3: AI-Assisted Forecasting for Fuel Demand
- Comprehending demand forecasting and key influencing factors
- Applying Excel’s AI capabilities and ChatGPT for predictive analysis
- Predicting short-term (1–2 week) fuel demand trends
- Practical exercise: developing a basic forecast model using existing data
Module 4: Route Planning and Resource Optimization
- Essential concepts in route optimization and scheduling
- Leveraging AI tools to recommend optimal routes and delivery sequences
- Utilizing Excel and ChatGPT for route planning under real-world constraints
- Hands-on task: creating route options for delivery units
Module 5: Cost Estimation and Logistics Optimization
- Recognizing cost drivers: distance, tolls, fuel consumption, and freight
- Employing AI models to calculate logistics costs
- Evaluating manual versus AI-assisted cost planning methods
- Developing cost calculation templates with dynamic inputs
Module 6: Dashboards and KPI Visualization
- Introduction to Power BI and Excel dashboarding
- Creating visual reports for logistics and supply KPIs
- Integrating data from volumetric control systems
- Hands-on project: building a real-time logistics performance dashboard
Module 7: Integrating AI into Logistics Workflows
- Automating routine reporting and data consolidation tasks
- Utilizing Power Automate or Excel macros for process automation
- Setting up alert systems for inventory or delivery thresholds
- Case study: implementing an AI-based alert for tank refill scheduling
Module 8: 90-Day AI Adoption Plan for Logistics and Supply
- Constructing a phased AI implementation roadmap
- Selecting pilot use cases and defining success metrics
- Expanding AI-assisted workflows across teams
- Establishing practices for continuous improvement and knowledge sharing
Summary and Next Steps
Requirements
- Familiarity with Microsoft Excel or Google Sheets
- No previous experience with Artificial Intelligence is necessary
Target Audience
- Logistics and supply professionals working in the fuel transportation and sales sector
- Operations and inventory coordinators
- Supervisors and planners responsible for fleet routes and fuel delivery
