Supply chains are becoming increasingly complex, global, and data-intensive. Volatile demand, disruptions, sustainability requirements, rising logistics costs, and customer expectations are forcing organisations to move beyond traditional planning tools toward AI-enabled, adaptive supply chains.

Artificial Intelligence (AI), particularly Machine Learning, Large Language Models (LLMs), and Generative AI, is transforming how organisations forecast demand, manage inventory, optimise transportation, monitor suppliers, and respond to disruptions in real time. Today, supply chain professionals—not just data scientists—can directly use AI tools to analyse data, generate insights, summarise operational reports, support decision-making, and improve coordination across functions.

This course provides a practical, business-focused introduction to AI for supply chain professionals. Participants will learn AI fundamentals, understand how AI technologies interconnect, and gain hands-on experience with leading AI tools such as ChatGPT, Gemini, Copilot, Perplexity, Grok, Claude, Manus, DeepSeek, Qwen, and NotebookLM. The emphasis is on real-world supply chain use cases, responsible AI usage, and measurable operational improvements, without requiring programming skills.

Data Wrangling & Exploratory Data Analysis with Python

Data wrangling and exploratory data analysis (EDA) are essential steps in any data science or analysis project. This four-day course is designed for beginners and provides a comprehensive foundation in data preparation and exploration using Python. Participants will learn to clean, transform, and gain insights from real-world datasets, making them well-equipped for data-driven decision-making.

Machine Learning – Unsupervised Learning

Unsupervised learning is a fascinating field of machine learning that discovers patterns, structures, and relationships within data without the need for labeled examples. This three-day course, designed for beginners, offers a comprehensive introduction to unsupervised learning techniques. Participants will gain a solid understanding of clustering, dimensionality reduction, and anomaly detection.

Data Storytelling

Data storytelling is a critical skill for conveying data-driven insights in a compelling and meaningful way. This three-day course, designed for beginners, focuses on teaching the art and science of data storytelling. Participants will learn how to structure, visualize, and present data to engage and inform their audience effectively.