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Duration 14 hours
Course Outline
Module 1: Introduction to AI in Logistics and Supply
- Understanding Artificial Intelligence: key concepts and practical applications
- AI in logistics and fuel distribution: exploring opportunities and impact
- No-code AI tools: Excel AI, ChatGPT, Power BI, and other solutions
- Real-world examples from the transportation and fuel sectors
Module 2: Structuring and Analyzing Operational Data
- Identifying essential logistics and supply datasets (routes, tanks, deliveries)
- Preparing volumetric control and inventory data for AI processing
- Data cleansing, formatting, and validation using Excel
- Generating insights through dynamic tables and pivot charts
Module 3: AI-Assisted Forecasting for Fuel Demand
- Understanding demand forecasting and key influencing factors
- Utilizing Excel’s AI capabilities and ChatGPT for predictive analysis
- Predicting short-term (1–2 week) fuel demand trends
- Practical exercise: constructing a simple 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
- Using Excel and ChatGPT for route planning with real-world constraints
- Practical activity: generating route options for delivery units
Module 5: Cost Estimation and Logistics Optimization
- Identifying cost drivers: distance, tolls, fuel consumption, and freight
- Applying AI models to estimate logistics costs
- Evaluating manual vs. AI-assisted cost planning approaches
- Creating 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
- Practical exercise: building a real-time logistics performance dashboard
Module 7: Integrating AI into Logistics Workflows
- Automating repetitive reporting and data aggregation tasks
- Using Power Automate or Excel macros for process automation
- Setting up alert systems for inventory or delivery thresholds
- Practical example: AI-driven alerts for tank refill scheduling
Module 8: 90-Day AI Adoption Plan for Logistics and Supply
- Developing a phased AI implementation roadmap
- Selecting pilot use cases and defining success metrics
- Expanding AI-assisted workflows across teams
- Implementing continuous improvement and knowledge-sharing strategies
Summary and Next Steps
Requirements
- Familiarity with Microsoft Excel or Google Sheets
- No previous experience with Artificial Intelligence is required
Target Audience
- Logistics and supply chain professionals in the fuel transportation and sales sector
- Operations and inventory coordinators
- Supervisors and planners responsible for fleet routing and fuel delivery
