Course Overview

  • Comprehensive Learning: Covers logistics, operations, and supply chain digitisation
  • Advanced Supply Strategies: Develop innovative supply strategies and workflows
  • Sector-Specific Solutions: Tailored sessions for real-world, sector-specific challenges
  • Lead AI Supply Efficiency: Prepares learners to lead in AI-led supply chain efficiency

Certification overview:

Included Items: Instructor-led OR Self-paced course + Official exam + Digital badge

Certificate Duration:

  • Instructor-Led: 1 day (live or virtual)
  • Self-Paced: 8 hours of content

Prerequisites: Foundational knowledge of supply chain; prior experience with business management or technical tools, such as ERP systems or data analysis software, will be beneficial.

Exam Format: 50 questions, 70% passing, 90 minutes, online proctored exam

Why this certification matters:

Leverage AI for Smarter Supply Chain Operations: Learn how AI tools can optimise logistics, reduce costs, and improve supply chain efficiency from end to end. Optimise Demand Forecasting with AI: Use AI-driven analytics to predict demand, streamline inventory management, and reduce stockouts or overstocking. Stay Ahead in AI-Powered Supply Chain: As industries increasingly adopt AI, professionals with AI supply chain expertise are in high demand to drive innovation and efficiency. Enhance Decision-Making with Predictive Analytics: Master AI algorithms to analyse supply chain data and make informed, real-time decisions to improve overall operations.

Who should enrol:

Supply Chain Professionals: Enhance your supply chain management skills by integrating AI tools for improved forecasting, inventory management, and process optimisation.

Logistics & Operations Managers: Learn to leverage AI for optimising logistics, route planning, and warehouse management to enhance operational efficiency and reduce costs.

Procurement Experts: Use AI to improve supplier selection, demand forecasting, and inventory replenishment, streamlining procurement processes.

Business Leaders: Drive innovation in your supply chain by adopting AI technologies to automate workflows, predict demand, and optimise end-to-end operations.

Students & New Graduates: Gain a competitive advantage in the supply chain field by mastering AI tools and techniques that are transforming global logistics and supply chain management.

Tools You'll Master

LeewayHertz (ZBrain)

C3.ai

Coupa (LLamasoft)

Zebra (Workcloud Demand Intelligence Suite)

Certification Modules

Module 1: Fundamental Concepts of Supply Chain Management

1.1 SCOR Model and Core Processes (Plan, Source, Make, Deliver, Return, Enable)

1.2 Key Functions: Procurement, Inventory Management, Logistics, Warehousing, Demand Forecasting, Risk, and Resilience

1.3 Global Challenges: Volatility, Sustainability, Nearshoring, and ESG

1.4 KPIs and Performance Measurement

1.5 Activity: Analyse and Map a Real-World Supply Chain

Module 2: AI Concepts, Techniques, and Tools for SCM

2.1 AI/ML Fundamentals – Supervised & Unsupervised Learning, Predictive & Prescriptive Analytics, Optimisation, Reinforcement Learning

2.2 Key Techniques – Neural Networks, Computer Vision, NLP, Digital Twins, Edge AI

2.3 AI Tools for SCM

2.4 Data Foundations – IoT, Real-Time Data Pipelines, Data Quality & Governance

Module 3: LLM and Generative AI Applications in SCM

3.1 LLM/GenAI Fundamentals and Enterprise Integration

3.2 Use Cases – Demand Planning Assistance, Contract Analysis, Supplier Communication, Scenario Simulation, Report Generation, Synthetic Data

3.3 Chat-Based Copilots for Planners and Knowledge Management

3.4 Limitations and Best Practices (Hallucinations, Grounding, Integration)

3.5 Tools – Enterprise GPT-like Models, LangChain/LlamaIndex, Amazon Business Assistant, Custom GenAI Workflows

Module 4: Ethical Considerations and Responsible AI in SCM

4.1 Bias in Forecasting/Procurement, Transparency, and Explainability

4.2 Privacy, Security, Regulatory Compliance

4.3 Job Displacement, Upskilling, and Human-AI Collaboration

4.4 Sustainability & ESG – AI for Ethical Sourcing and Carbon Tracking

4.5 Governance Frameworks and Risk Management

Module 5: Supply Chain Digitisation, Orchestration, and Intelligent Systems

5.1 Digitisation – ERP + SCM Platforms, Cloud Integration, Blockchain for Traceability, APIs

5.2 Orchestration – Control Towers, Real-Time Visibility, Data Pipelines, Digital Twins

5.3 Intelligent & Smart SCM – Predictive/Prescriptive Analytics, Autonomous Exception Management, Robotics + Computer Vision, Edge AI

5.4 Human + AI Collaboration Models

Module 6: Industrial Applications, Case Studies, and Business Value

6.1 Applications Across Industries

6.2 Real-World ROI – Efficiency Gains, Cost Reduction, and Resilience Improvements

6.3 Implementation Best Practices

6.4 Case Studies from Blue Yonder, Kinaxis, Oracle, and Others

Module 7: Strategic SCM, Logistics Policies, and Sustainability

7.1 Logistics Policies, Trade Regulations, Tariffs, and Geopolitical Risks

7.2 Strategic Network Design: Optimisation, Resilience, Nearshoring, and Friendshoring

7.3 Sustainable SCM: Circular Economy, Green Logistics, and AI-Driven ESG Reporting

7.4 Organisational Transformation and Leadership in AI-Enabled Supply Chains

7.5 Case Studies

Module 8: Agentic AI and the Future of Autonomous Supply Chains

8.1 Agentic AI Concepts: Autonomous Goal-Oriented Agents, Multi-Agent Systems, and Reasoning-Action Loops

8.2 Applications: Autonomous Replenishment, Risk Mitigation, Supplier Onboarding, Dynamic Rerouting, and End-to-End Orchestration

8.3 Tools & Platforms: Kinaxis Maestro Agents, Oracle AI Agents, Blue Yonder Cognitive Agents, Custom Builds, and Automation Anywhere

8.4 Architectures, Guardrails, and Human Oversight

8.5 Future Outlook for 2026+: From Copilots to Semi-Autonomous Operations

8.6 Capstone Project: Design and Prototype a Multi-Agent Workflow for a Supply Chain

8.7 Case Studies

Optional Module: AI Agents in Supply Chain

1. What Are AI Agents

2. What Are AI Agents in Logistics and Supply Chain

3. Applications & Trends of AI Agents in Supply Chain

4. How Does an AI Agent Work

5. Core Characteristics of AI Agents

6. Key Advantages of AI Agents in Logistics and Supply Chain

7. Types of AI Agent

8. Case Studies

9. Hands-on Experiment

Frequently Asked Questions

What core industry problems does the AI+ Supply Chain™ Self Paced Learning V3 training solve?

This course is engineered to help you solve real-world operational inefficiencies by integrating advanced machine learning tools into your daily workflow. You will learn to automate tedious data processing, construct predictive models, and optimize systemic outputs specific to this domain. By learning these practical automation skills, you immediately boost your daily professional output and elevate your long-term career value.

Are the tools and software platforms taught in this course accessible to beginners?

The curriculum is structured logically to support clean career progression, moving from essential concepts to advanced configurations. While technical tracks introduce deeper code integrations, our industry-specific modules utilize user-friendly enterprise interfaces and pre-trained prompt systems. This balanced approach ensures you can comfortably master the curriculum, acquire highly sought-after skills, and earn your digital record badge without frustration.

How will completing this self-paced course help upgrade my professional CV?

Completing this training demonstrates to modern employers that you possess practical, forward-looking expertise in artificial intelligence integration. Your profile will stand out with specialized technical capabilities, showing you can actively deploy automation, reduce operational costs, and manage digital workflows. This enables you to confidently pursue high-tier promotions, transition into modern tech roles, and take your career to the absolute next level.

AI+ Supply Chain Practitioner™

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£149.00

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