AI+ Supply Chain™
AP-710
Transforming Supply Chain ManagementAI+ Supply Chain™ course provides a thorough examination of how Artificial Intelligence (AI) is changing supply chain management, covering basic concepts up to advanced uses. It includes key subjects like AI methods for improving supply chains, the impact of generative AI on developing strategies, and the digitalization of supply chain operations. The course also delves into decision-making guided by AI, applications specific to various industries, and the incorporation of AI into managing logistics. The last module offers a practical workshop where participants can utilize AI concepts for actual supply chain problems, getting them ready to spearhead AI-based advancements in their companies.
Certification Duration: 8 hours (1 Day)
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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
8
Examination
1
50 MCQs
90 Minutes
Passing Score
70%
Certification Modules
- 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
- 2.1 Machine Learning in Supply Chain
- 2.2 Expert Systems in SCM
- 2.3 Integrating Images and Text in Supply Chain AI
- 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
- 4.1 Introduction to Supply Chain Digitization
- 4.2 Supply Chain Integration and Push-Pull Strategies
- 4.3 Supply Chain Resiliency, Planning and Sustainability
- 5.1 Introduction to Smart SCM
- 5.2 Employing Smart SCM and Prompt Engineering
- 5.3 Future Trends of Smart 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
- 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
- 8.1 Supplier Selection and Relationship Management with
AI - 8.2 Mastering Advancements in SCM with Modern Artefacts
Certification Modules
- 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
- 2.1 Machine Learning in Supply Chain
- 2.2 Expert Systems in SCM
- 2.3 Integrating Images and Text in Supply Chain AI
- 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
- 4.1 Introduction to Supply Chain Digitization
- 4.2 Supply Chain Integration and Push-Pull Strategies
- 4.3 Supply Chain Resiliency, Planning and Sustainability
- 5.1 Introduction to Smart SCM
- 5.2 Employing Smart SCM and Prompt Engineering
- 5.3 Future Trends of Smart 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
- 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
- 8.1 Supplier Selection and Relationship Management with
AI - 8.2 Mastering Advancements in SCM with Modern Artefacts
Tools
LeewayHertz (ZBrain)
C3.ai
Coupa (LLamasoft)
Zebra (Workcloud Demand Intelligence Suite)
Exam Objectives
Supply Chain Digitization
Learners will gain skills in applying AI to digitize and automate supply chain operations, enhancing overall efficiency and enabling data-driven decision-making.
AI for Logistics Management
Expertise in integrating AI to enhance logistics planning, warehousing, and transportation, leading to streamlined operations and cost reduction.
Smart Supply Chain Management (SCM)
Learners will acquire knowledge of intelligent SCM systems powered by AI, enabling real-time monitoring, automation, and optimization of supply chain functions.
AI-Driven Supply Chain Optimization
Ability to implement AI techniques such as machine learning and predictive analytics to optimize supply chain processes, including demand forecasting, inventory management, and logistics.
Career Opportunities Post-Certification
Median Salaries
$55000
With AI Skills
$70,000
% Difference
27
Supply Chain Automation Specialist
Focuses on automating supply chain functions such as procurement, logistics, and inventory management through AI-powered tools.
AI Supply Chain Strategist
Develops and implements AI-driven strategies to improve supply chain efficiency, cost-effectiveness, and resilience.
Supply Chain Data Scientist
Utilizes AI and data analytics to gather insights from supply chain data, predicting trends, optimizing performance, and solving operational challenges.
AI Procurement Specialist
Use AI tools to improve procurement strategies by optimizing supplier evaluation and reducing costs effectively.
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Get CertifiedFrequently Asked Questions
You’ll learn about predictive analytics, machine learning for demand planning, and AI-driven logistics management.
You’ll work on projects like optimizing warehouse operations and forecasting supply chain disruptions using AI.
Retail, manufacturing, and logistics industries can significantly benefit from AI-driven supply chain improvements.
You’ll use tools like AI-based optimization software and predictive analytics platforms.
This course teaches how AI can be used to optimize supply chain operations, including demand forecasting and inventory management.
