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Duration 14 hours
Course Outline
Module 1: Introduction to AI in Logistics and Supply
- Core AI concepts and their applications
- The role of AI in logistics and fuel distribution: opportunities and strategic 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 volume control and inventory data for AI integration
- Data cleaning, formatting, and validation techniques in Excel
- Generating insights through dynamic tables and pivot charts
Module 3: AI-Driven Forecasting for Fuel Demand
- Understanding demand forecasting and key influencing variables
- Leveraging Excel’s AI capabilities and ChatGPT for predictive analytics
- Predicting short-term (1–2 week) fuel demand trends
- Practical exercise: developing a simple forecasting model using existing data
Module 4: Route Planning and Resource Optimization
- Fundamental concepts in route optimization and scheduling
- Using AI tools to recommend optimal routes and delivery sequences
- Applying Excel and ChatGPT to plan routes considering real-world constraints
- Hands-on activity: generating route alternatives for delivery units
Module 5: Cost Estimation and Logistics Efficiency
- Identifying key cost factors: distance, tolls, fuel consumption, and freight
- Utilizing AI models for logistics cost estimation
- Contrasting manual cost planning with AI-assisted approaches
- Creating cost calculation templates with dynamic inputs
Module 6: Dashboards and KPI Visualization
- Introduction to Power BI and Excel dashboard creation
- Designing visual reports for logistics and supply chain KPIs
- Incorporating data from volume control systems
- Hands-on session: building a real-time logistics performance dashboard
Module 7: Integrating AI into Logistics Workflows
- Automating routine reporting and data aggregation tasks
- Leveraging Power Automate or Excel macros for process automation
- Setting up alert systems for inventory levels or delivery thresholds
- Practical example: implementing AI-based alerts for tank refill scheduling
Module 8: 90-Day AI Adoption Plan for Logistics and Supply
- Constructing a phased AI implementation roadmap
- Defining pilot projects and success metrics
- Expanding AI-assisted workflows across teams
- Fostering 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 chain specialists in the fuel transport and retail sectors
- Operations and inventory coordination staff
- Supervisors and planners overseeing fleet management and fuel delivery
