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Duration 14 hours
Course Outline
Module 1: Introduction to AI in Logistics and Supply
- Exploring Artificial Intelligence: core concepts and applications
- AI in logistics and fuel distribution: key opportunities and impact
- No-code AI tools: Excel AI, ChatGPT, Power BI, and more
- Real-world examples from the transportation and fuel industry
Module 2: Structuring and Analyzing Operational Data
- Identifying critical logistics and supply datasets (routes, tanks, deliveries)
- Organizing volumetric control and inventory data for AI utilization
- Data cleaning, formatting, and validation techniques in Excel
- Building dynamic tables and pivot charts to generate insights
Module 3: AI-Assisted Forecasting for Fuel Demand
- Understanding demand forecasting and its key influencing variables
- Utilizing Excel’s AI capabilities and ChatGPT for predictive analysis
- Predicting short-term (1–2 week) fuel demand trends
- Practical exercise: creating a basic forecast model using existing data
Module 4: Route Planning and Resource Optimization
- Fundamental concepts in route optimization and scheduling
- Employing AI tools to recommend optimal routes and delivery sequences
- Applying Excel and ChatGPT for route planning under real-world constraints
- Hands-on activity: generating route options for delivery units
Module 5: Cost Estimation and Logistics Optimization
- Identifying cost drivers: distance, tolls, fuel consumption, and freight
- Utilizing AI models to estimate logistics costs
- Comparing 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 dashboards
- Designing visual reports for logistics and supply KPIs
- Integrating data from volumetric control systems
- Hands-on: building 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
- Setting up alert systems for inventory or delivery thresholds
- Practical example: implementing an AI-based alert for tank refill scheduling
Module 8: 90-Day AI Adoption Plan for Logistics and Supply
- Creating a step-by-step roadmap for AI implementation
- Identifying pilot use cases and defining success metrics
- Scaling AI-assisted workflows across teams
- Establishing practices for continuous improvement and knowledge sharing
Summary and Next Steps
Requirements
- Basic familiarity with Microsoft Excel or Google Sheets
- No previous experience with Artificial Intelligence is necessary
Target Audience
- Logistics and supply professionals in the fuel transportation and sales industry
- Operations and inventory coordinators
- Supervisors and planners responsible for fleet routes and fuel delivery
