Supply Chain Analytics and AI Optimization Training Course

Course overview

Supply chains generate vast data, orders, inventory, shipments, supplier performance, but much of it goes unused while decisions rely on gut feel. Supply chain analytics extracts insight from that data, and AI takes it further: forecasting demand, optimizing inventory and routes, and flagging risk before it disrupts. Used well, it cuts cost and raises service at the same time.

This course shows how. It covers supply chain analytics and AI optimization, demand forecasting with AI, logistics and inventory optimization, real-time visibility and risk management, and building resilient, sustainable supply chains. It is built for supply-chain and operations professionals who want to use data and AI with judgment, not for data scientists.

Why this matters

Volatile demand, disruption, and cost pressure make supply chain decisions harder and more consequential, and the organizations that use their data well respond faster and waste less. Those that do not carry excess inventory, miss demand, and are blindsided by disruption.

Analytics and AI matter because the data to decide better already exists; the skill is turning it into action. Professionals who can forecast, optimize, and see risk coming give their supply chains a real edge. This course builds that capability.

What you will be able to do afterwards

By the end of the course, participants should be able to:

• Explain how analytics and AI improve supply chains.
• Apply AI to demand forecasting.
• Optimize logistics and inventory.
• Use real-time visibility to manage risk.
• Build more resilient, sustainable supply chains.

Course outline

Unit 1: Introduction to supply chain analytics

The course opens with the data opportunity.

• The data supply chains generate.
• From reporting to insight to decisions.
• Where AI adds value.
• Documented examples.

Unit 2: Demand forecasting with AI

This unit covers predicting demand.

• Machine learning for forecasting.
• Handling volatility and seasonality.
• Improving forecast accuracy.
• Acting on forecasts.

Unit 3: Logistics and inventory optimization

This unit covers optimizing the flow.

• Inventory optimization.
• Route and network optimization.
• Balancing cost and service.
• Analytics in decisions.

Unit 4: Real-time visibility and risk management

This unit covers seeing and responding.

• Real-time supply-chain visibility.
• Detecting and predicting risk.
• Responding to disruption.
• Data for decisions.

Unit 5: Building resilient and sustainable supply chains

The final unit covers the bigger goal.

• Resilience through analytics.
• Sustainability and efficiency.
• Scaling analytics and AI.
• A roadmap to take back.

How the course is delivered

The course is led through structured explanation, worked examples with data, documented case studies, and group discussion of how analytics and AI improve supply chains. Participants examine forecasts, optimization scenarios, and visibility tools and work through the decisions involved. For the logistics-AI focus, it connects to AI Applications in Logistics Planning and Optimization.

Who should attend

This course suits supply-chain and operations managers, planning and analytics staff, logistics and procurement professionals, and managers adopting analytics. It works for those new to supply-chain analytics and for experienced staff who want to add AI and use data more deliberately. Comfort with data helps; no coding is required.

About EuroQuest International Training

EuroQuest International Training was founded in 2015 by a team with more than 25 years of combined experience in professional training. The institute has delivered over 1,000 courses to more than 15,000 participants, and is headquartered in Bratislava, Slovakia, with training hubs in Dubai, London, Barcelona, Istanbul, Vienna, Paris, and Geneva. Courses are designed and reviewed by practitioners and updated to reflect current practice in each field.

Frequently asked questions

Do I need a data-science background?

No. The course explains analytics and AI in plain terms and focuses on applying them and interpreting results, rather than on building models. Comfort with data is enough.

Does it cover demand forecasting?

Yes. A dedicated unit covers demand forecasting with AI, including handling volatility and seasonality and acting on forecasts.

How does it address resilience?

The final unit focuses on building resilient, sustainable supply chains, using visibility and analytics to anticipate and respond to disruption.

Related courses

• Predictive Analytics and Demand Forecasting in Logistics
• Big Data Management and Predictive Logistics Planning
• Demand Planning and Forecasting in Supply Chain Management
• Supply Chain and Logistics Optimization

Register for this course

To reserve a place or ask about scheduling and city options for the Supply Chain Analytics and AI Optimization course, use the registration and enquiry options on this page and the EuroQuest team will follow up with the details you need.