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Certified Generative AI for Supply Chain Management CGAISCM
Explore how Generative AI can improve supply chain management through demand forecasting, inventory optimization, logistics, supplier management, production planning, risk management, and sustainability.
2
Days
8
Hours/Day
Live
Training
Course Fee
S$4000
Course Information
Course Overview
Generative AI is transforming supply chain management by enabling organizations to improve operational efficiency, optimize decision-making, reduce costs, and strengthen supply chain resilience. This two-day program provides participants with an understanding of Generative AI and its applications across key supply chain functions including demand forecasting, inventory management, logistics, supplier management, production planning, risk management, customer service, sustainability, and supply chain technology integration.
Course Objectives
- Understand the basics of Generative AI and its application in supply chain management.
- Master demand forecasting and planning using AI-driven techniques.
- Improve inventory management and stock levels using AI simulations.
- Enhance logistics and route optimization using AI-based approaches.
- Improve supplier management and performance with AI-based strategies.
- Improve risk management, scenario planning, and sustainability in supply chains.
- Gain hands-on experience by developing and applying AI models in supply chain processes.
Prerequisites
- Basic knowledge of supply chain management principles.
- No advanced technical skills are required.
- Readiness to learn about artificial intelligence.
Course Outlines
Module 1: Introduction to Generative AI and Supply Chain Management
Topics
- Basics of GANs, VAEs, and Transformers
- Supply chain management fundamentals: procurement, production, and logistics
- Benefits of AI in supply chain management: efficiency and cost reduction
Module 2: Generative AI Techniques and Models
Topics
- GANs and VAEs for synthetic data generation
- Transformer models for supply chain insights
- Combining models for complex tasks
Module 3: Generative AI for Demand Forecasting and Planning
Topics
- Multi-scenario demand forecasting
- Modeling consumer behavior shifts
- Real-time adjustments with IoT integration
- Use Case: Retail - Seasonal demand planning
- Use Case: Food and Beverage - Predicting perishable demand
Module 4: Inventory Optimization and Management
Topics
- Dynamic inventory adjustments with AI
- Simulation models for stock optimization
- Multi-channel inventory strategies
- Use Case: E-commerce - Stock level optimization
Module 5: Logistics and Route Optimization
Topics
- Real-time route changes based on AI predictions
- Fleet management improvements
- Sustainable logistics optimization
- Use Case: Delivery - Efficient routing
Module 6: Supplier Management and Performance Optimization
Topics
- Predicting supplier risks and reliability
- AI-enhanced negotiation strategies
- Supplier diversification via AI
- Use Case: Manufacturing - Supplier selection
Module 7: Production Planning and Quality Control
Topics
- Optimizing production schedules
- Predictive maintenance with AI
- Quality control through anomaly detection
- Use Case: Electronics - Reducing waste
Module 8: Risk Management and Scenario Planning with Generative AI
Topics
- AI for risk forecasting and disruption planning
- Financial risk simulation
- Geopolitical risk analysis
- Use Case: Pharma - Supply chain continuity
Module 9: Customer Service and Experience Enhancement
Topics
- AI-driven customer insights and personalization
- Virtual assistants and customer handling
- Predictive feedback analysis
- Use Case: E-commerce - Enhancing service quality
Module 10: Sustainability and Circular Economy in Supply Chains
Topics
- AI for sustainable practice modeling
- Optimizing recycling and waste reduction
- Reducing carbon footprint
- Use Case: Consumer goods - Sustainability initiatives
Module 11: Ethics, Privacy, and Compliance in AI-Driven Supply Chains
Topics
- Addressing AI biases and fairness
- Data privacy and regulatory compliance
- Ethical AI frameworks
- Use Case: Global SCM - Ethical AI deployment
Module 12: Technology Stack and Integration for Generative AI
Topics
- Tools: TensorFlow, PyTorch, etc.
- Integrating Generative AI with ERP and SCM systems
- Cloud vs. on-premises AI deployment
- Use Case: FMCG - End-to-end visibility
Module 13: Capstone Projects and Hands-On Learning
Topics
- Developing a Generative AI model for supply chain management
- Case study analysis of AI applications
- Designing an AI-driven supply chain strategy
- Capstone Project: Full AI optimization of supply chain processes
Course Outcomes
- Learn to optimize inventory management, demand forecasting, and route planning using Generative AI for enhanced efficiency.
- Master AI tools for supplier evaluation, contract analysis, and cost-effective procurement decisions.
- Apply Generative AI for demand planning, risk assessment, and disruption management in supply chains.
- Acquire practical skills to automate tasks like order processing, scheduling, and warehouse operations.
- Develop strategies to address ethical, privacy, and regulatory concerns in AI-driven supply chain management.
What You'll Learn
Practical hands-on experience
Industry-recognized certification
Real-world case studies
Expert-led live sessions
Comprehensive study materials
Post-training support
Facilities & Equipment
Virtual Training
- Electronic materials
- IT support for software & hardware
- Administrative support
Face-to-Face Training
- Air-conditioned classroom
- Meals & refreshments provided
- Projector & smart board
- Stationery provided
What Learners Say
Real experiences, real results
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