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Duration 14 hours
Course Outline
Module 1: Intro to AI in Logistics and Supply
- Foundations of Artificial Intelligence: concepts and use cases
- AI in logistics and fuel distribution: potential benefits and impact
- No-code AI tools: Excel AI, ChatGPT, Power BI, and more
- Real-world examples from the transport and fuel sectors
Module 2: Organizing and Analyzing Operational Data
- Recognizing essential logistics and supply datasets (routes, tanks, deliveries)
- Preparing volumetric control and inventory data for AI utilization
- Cleaning, formatting, and verifying data within Excel
- Generating dynamic tables and pivot charts for analytical insights
Module 3: AI-Driven Forecasting for Fuel Demand
- Insights into demand forecasting and key influencing factors
- Utilizing Excel’s AI capabilities and ChatGPT for predictive analysis
- Predicting short-term (1–2 week) fuel demand patterns
- Practical task: constructing a simple forecast model using existing data
Module 4: Route Planning and Resource Optimization
- Core principles of route optimization and scheduling
- Using AI tools to propose optimal routes and delivery orders
- Applying Excel and ChatGPT for route planning with actual constraints
- Practical activity: generating route alternatives for delivery units
Module 5: Cost Estimation and Logistics Optimization
- Identifying cost factors: distance, tolls, fuel usage, freight
- Employing AI models to calculate logistics costs
- Evaluating manual vs. AI-assisted cost planning
- Creating cost calculation templates with dynamic inputs
Module 6: Dashboards and KPI Visualization
- Overview of Power BI and Excel dashboards
- Designing visual reports for logistics and supply KPIs
- Connecting data from volumetric control systems
- Practical 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 or delivery limits
- Practical scenario: AI-based alerts for tank refill scheduling
Module 8: 90-Day AI Adoption Plan for Logistics and Supply
- Creating a phased AI implementation roadmap
- Defining pilot use cases and key performance indicators
- Expanding AI-assisted processes across teams
- Establishing ongoing improvement and knowledge-sharing initiatives
Conclusion and Next Steps
Requirements
- Familiarity with Microsoft Excel or Google Sheets
- No previous experience with Artificial Intelligence is necessary
Target Audience
- Logistics and supply specialists in the fuel transportation and sales sector
- Operations and inventory coordinators
- Supervisors and planners responsible for fleet routes and fuel distribution
