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AI+ Supply Chain™
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Module 1: Introduction to Artificial Intelligence in Supply Chain
Module 1: Introduction to Artificial Intelligence in Supply Chain
1.1 Introduction: AI in Supply Chain
1.2 Introduction To AI in Supply Chain Management
1.3 Definition and Components (elements) of a Supply Chain AndKeytribution, and Logistics Processes in SCM: ProcureProduction, Disment,
1.4 AI Driven Supply Chain Networks And Upstream and Downstream Flows And Importance of SCM in Modern Businesses
1.5 Challenges in Traditional Supply Chains Common Challenges - Demand Forecasting, Inventory Management, and Supplier Management
1.6 Impact of Globalization and E-commerce on Supply Chains
1.7 AI Transformation with Supply Chains
1.8 AI Applications in Demand Forecasting
1.9 Ethical and Practical Considerations in AI-driven SCM
1.10 Responsible AI
1.11 Best Practices for Overcoming Challenges - Change Management, Upskilling, and Stakeholder Engagement
1.12 Summary: AI in Supply Chain
Quiz
Module 2: Advanced AI Techniques for Supply Chain
Module 2: Advanced AI Techniques for Supply Chain
2.1 Introduction: Advanced AI Techniques for Supply Chain
2.2 Introduction to ML in SCM
2.3 Types of ML Algorithms - Supervised, Unsupervised, and Reinforcement Learning
2.4 Key Applications in SCM - Demand Forecasting, Inventory Management, and Logistics Optimization
2.5 Comparing classical AI with modern AI techniques like ML and Deep Learning (DL)
2.6 Understanding Expert Systems
2.7 Knowledge Representation, Inference Engines, and Rule-based Reasoning
2.8 Creating a Rule-based System for Order Processing or Inventory Management
2.9 AI Techniques for Image and Text Processing
2.10 Applications of Image Processing - Quality control, Warehouse automation, and Visual inspections
2.11 Image and Text Analysis
2.12 Building a Simple Image Classification Model for Defect Detection
2.13 Integrating Multimodal AI (images and text) for Comprehensive Supply Chain Insights
2.14 Summary: Advanced AI Techniques for Supply Chain
Quiz
Module 3: Generative AI in Supply Chain Management
Module 3: Generative AI in Supply Chain Management
3.1 Introduction: Generative AI in Supply Chain Management
3.2 Introduction to Generative AI
3.3 Types of Generative Models
3.4 Applications of Generative AI in SCM
3.5 How Generative AI can be used for Supply Chain Design, Optimization, and Simulation?
3.6 Revenue Management with Generative AI
3.7 Demand Forecasting using Generative AI
3.8 Applications in Retail, Manufacturing, and Distribution for Predicting Demand Fluctuations
3.9 Introduction to Transformers
3.10 LSTM Architectures and Their Role in Generative AI
3.11 Comparison between LSTM and Transformer Architectures for Sequential Data
3.12 Summary: Generative AI in Supply Chain Management
Quiz
Module 4: Supply Chain Digitization
Module 4: Supply Chain Digitization
4.1 Introduction: Digital Technologies for Supply Chain Sustainability
4.2 Overview of Digitization in Supply Chain Management
4.3 The Role of Digital technologies - AI, IoT, Blockchain, and Big Data
4.4 The Impact of Industry 4.0 on Supply Chain Digitization
4.5 Integration Technologies - EDI, Cloud Computing, and Collaborative platforms
4.6 Push-Pull Strategies in Supply Chains
4.7 Advantages and Challenges of Push-Pull Models
4.8 Definition and Importance of Supply Chain Resiliency
4.9 Supply Chain Planning in the Digital Age
4.10 Overview of Supply Chain Planning
4.11 Overview of Sustainability Challenges in Global Supply Chains
4.12 Digital Technologies for Supply Chain Sustainability
4.13 Summary: Digital Technologies for Supply Chain Sustainability
Quiz
Module 5: Intelligent Driven Supply Chain Management
Module 5: Intelligent Driven Supply Chain Management
5.1 Introduction: Intelligent Driven Supply Chain Management
5.2 Key technologies - Machine Learning, Natural Language Processing, Computer Vision, and Robotics in SCM
5.3 Applications: Demand forecasting, Inventory optimization, Supplier risk assessment
5.4 The role of information flow, physical flow, and financial flow in SCM.
5.5 Implementing AI in Supply Chain Management
5.6 Challenges and solutions - Data quality, system integration, change management
5.7 Prompt Engineering in SCM: Introduction to prompt engineering
5.8 How to craft effective prompts for various AI applications
5.9 Types of Prompting - Zero-shot, few-shot, and fine-tuned prompting.
5.10 AI, 5G, and the Smart Supply Chain
5.11 The role of 5G in enabling real-time data exchange and IoT integration
5.12 AI-driven decision-making
5.13 Summary: Intelligent Driven Supply Chain Management
Quiz
Module 6: Industry Aspects of Advanced SCM
Module 6: Industry Aspects of Advanced SCM
6.1 Introduction: Industry Aspects of Advanced SCM
6.2 Overview and Key processes in Industrial SCM: Procurement, Production, Distribution, and Logistics
6.3 Common limitations and challenges faced in traditional supply chain management
6.4 Disruptive Technologies in Supply Chain - Cloud Computing: Artificial Intelligence (AI), Machine Learning (ML), Generative AI (Gen AI) Robotics, Block Chain, Quantum Computing
6.5 The strategic importance of AI and Gen AI in modernizing supply chains
6.6 Industry-Leading Use Cases and Examples
6.7 Industry-specific applications in sectors like retail, manufacturing, healthcare, and logistics
6.8 Ethical concerns - Data privacy, algorithmic bias, and job displacement
6.9 Technical challenges - Data integration, system interoperability, and scalability
6.10 Resistance to change - Cultural and organizational barriers to AI adoption
6.11 Implementation Recommendations
6.12 Summary: Industry Aspects of Advanced SCM
Quiz
Module 7: Policies of Logistics Management in Supply Chain with AI
Module 7: Policies of Logistics Management in Supply Chain with AI
7.1 Introduction: Policies of Logistics Management in Supply Chain with AI
7.2 Strategic importance of supply chain management (SCM) in organizational success
7.3 Supply Chain and General Business Strategy Alignment
7.4 Aligning supply chain objectives with overall business goals
7.5 Key Strategies for warehousing in AI Driven SCM
7.6 Strategic Logistics Alliances
7.7 Building and managing strategic alliances in logistics
7.8 Emerging trends in transportation technology and their effects on SCM
7.9 Information Technology (IT) for Supply Chain Management
7.10 Global Supply Chains and UN's Sustainable Development Goals
7.11 Aligning supply chain strategies with the UN's Sustainable Development Goals (SDGs)
7.12 Summary: Policies of Logistics Management in Supply Chain with AI
Quiz
Module 8: Supply Chain Masterclass with AI Assistance
Module 8: Supply Chain Masterclass with AI Assistance
8.1 Introduction: Supply Chain Masterclass with AI Assistance
8.2 An Overview: Criteria for selecting strategic suppliers using AI-driven tools
8.3 Techniques for managing and enhancing supplier relationships
8.4 Demand Forecasting Model: Step-by-step guide to creating an AI-driven demand forecasting model
8.5 Predictive Analytics for Demand Forecasting
8.6 Autonomous Vehicles and Drones in Logistics
8.7 The impact of autonomous vehicles and drones on supply chain logistics
8.8 IoT and AI - A Synergistic Approach in Logistics
8.9 How IoT and AI work together to enhance supply chain visibility and efficiency
8.10 Block chain and AI Integration in Supply Chain
8.11 Future Trends - AI, 5G, and the Smart Supply Chain
8.12 Summary: Supply Chain Masterclass with AI Assistance
Quiz
Additional Module - AI Agents For Supply Chain
AI Agents Supply Chain
Resources
AI+ Supply Chain Blueprint
AI+ Supply Chain Detailed Curriculum
AI+ Supply Chain Tools
AI+ Supply Chain Resources and References
AI CERTs Exam Guidelines
AI CERTs Exam Guidelines
AI+ Supply Chain Examination
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AI+ Supply Chain™
