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Duration 14 hours
Course Outline
Module 1: Introduction to AI in Logistics and Supply
- Understanding Artificial Intelligence: core concepts and real-world applications
- The role of AI in logistics and fuel distribution: opportunities and impact
- Overview of no-code AI tools: Excel AI features, ChatGPT, Power BI, and others
- Case studies from the transportation and fuel industries
Module 2: Structuring and Analyzing Operational Data
- Identifying critical logistics and supply datasets (routes, tanks, delivery records)
- Preparing volumetric 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-Assisted Forecasting for Fuel Demand
- Understanding demand forecasting and key influencing variables
- Utilizing Excel’s AI capabilities and ChatGPT for predictive analysis
- Projecting short-term (1–2 week) fuel demand trends
- Practical exercise: constructing a basic forecast model using existing data
Module 4: Route Planning and Resource Optimization
- Key principles in route optimization and scheduling
- Using 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
- Employing AI models for logistics cost estimation
- Comparing manual planning versus AI-assisted cost analysis
- Developing 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 KPIs
- Integrating data from volumetric control systems
- Hands-on session: building a real-time logistics performance dashboard
Module 7: Integrating AI into Logistics Workflows
- Automating routine reporting and data consolidation tasks
- Using Power Automate or Excel macros for task 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
- Developing a step-by-step AI implementation roadmap
- 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
- Familiarity with Microsoft Excel or Google Sheets
- No prior experience with Artificial Intelligence is required
Target Audience
- Logistics and supply chain professionals in the fuel transportation and retail sectors
- Operations and inventory coordinators
- Supervisors and planners responsible for fleet routing and fuel distribution
