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Duration 14 hours
Course Outline
Module 1: AI Fundamentals in Logistics & Supply
- Core concepts of Artificial Intelligence and their practical applications
- The role of AI in fuel distribution: opportunities and strategic impact
- Overview of no-code AI solutions including Excel AI, ChatGPT, and Power BI
- Real-world examples from the transportation and fuel industries
Module 2: Organizing & Analyzing Operational Data
- Recognizing critical logistics and supply datasets (routes, tanks, deliveries)
- Structuring volumetric control and inventory data for AI compatibility
- Data hygiene: cleaning, formatting, and validation techniques in Excel
- Generating insights through dynamic tables and pivot charts
Module 3: AI-Driven Fuel Demand Forecasting
- Understanding demand forecasting and its key influencing factors
- Leveraging Excel’s AI capabilities and ChatGPT for predictive analytics
- Predicting short-term (1–2 week) fuel demand trends
- Practical task: developing a simple forecasting model using existing data
Module 4: Route Planning & Resource Optimization
- Foundations of route optimization and scheduling strategies
- Using AI to recommend optimal routes and delivery sequences
- Applying Excel and ChatGPT for route planning under real-world constraints
- Interactive activity: generating route alternatives for delivery units
Module 5: Cost Estimation & Logistics Optimization
- Identifying cost factors: distance, tolls, fuel usage, and freight
- Employing AI models for accurate logistics cost projection
- Evaluating manual versus AI-assisted cost planning approaches
- Developing cost calculation templates with dynamic input parameters
Module 6: Dashboards & KPI Visualization
- Introduction to Power BI and Excel dashboard capabilities
- Designing visual reports for key logistics and supply KPIs
- Incorporating 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 aggregation tasks
- Utilizing Power Automate or Excel macros for process automation
- Setting up alert systems for inventory or delivery threshold breaches
- Case study: AI-triggered alerts for tank refilling schedules
Module 8: 90-Day AI Adoption Strategy
- Crafting a phased roadmap for AI implementation
- Selecting pilot projects and defining success indicators
- Expanding AI-assisted processes across teams
- Implementing continuous improvement and knowledge-sharing protocols
Wrap-up and Recommended Next Steps
Requirements
- Familiarity with Microsoft Excel or Google Sheets
- No prior background in Artificial Intelligence is necessary
Target Audience
- Professionals in logistics and supply chain within the fuel transportation and retail sector
- Operations and inventory coordinators
- Supervisors and planners responsible for fleet routing and fuel distribution
