Course Prerequisites:
Foundational knowledge of supply chain concepts, processes, and operations.
A general understanding of Artificial Intelligence, including machine learning and data analytics, is recommended.
Prior experience with business management or technical tools, such as ERP systems or data analysis software, will be beneficial.
Strong analytical and problem-solving skills are essential to understand and apply AI-driven techniques in supply chain scenarios.
Modules:
Module 1: Introduction to Artificial Intelligence in Supply Chain
1.1 Overview of Artificial Intelligence in Supply Chain Management (SCM)
1.2 Transforming Supply Chains with AI
1.3 Ethical Implications of AI in Supply Chains
Module 2: Advanced AI Techniques for Supply Chain
2.1 Basic Concepts and Principles of AI
2.2 Expert Systems in SCM
2.3 Integrating Images and Text in Supply Chain AI
Module 3: Generative AI in Supply Chain Management
3.1 The Origin of Generative AI
3.2 Generative AI in Revenue Management and Demand Forecasting
3.3 Transformer and LSTM Architectures in Generative AI
Module 4: Supply Chain Digitization
4.1 Introduction to Supply Chain Digitization
4.2 Supply Chain Integration and Push-Pull Strategies
4.3 Supply Chain Resiliency, Planning and Sustainability
Module 5: Intelligent Driven Supply Chain Management
5.1 Introduction to Smart SCM
5.2 Employing Smart SCM and Prompt Engineering
5.3 Future Trends of Smart SCM
Module 6: Industry Aspects of Advanced SCM
6.1 Introduction to Industrial SCM
6.2 Business Value from AI and Gen AI in Supply Chain
6.3 Risks and Challenges of Adopting AI and Gen AI in Industrial SCM
Module 7: Policies of Logistics Management in Supply Chain with AI
7.1 Role of Supply Chain Management in the Organization
7.2 Warehousing Strategy for Efficient Supply Chain Management
7.3 Technical Coverage of SCM with Multi-Dimensional Aspects
Module 8: Supply Chain Masterclass with AI Assistance
8.1 Supplier Selection and Relationship Management with AI
8.2 Mastering Advancements in SCM with Modern Artefacts