AI for Operations & Supply Chain
A practical guide to how AI extends rules-based automation, where it earns its keep in operations, and how to deploy it alongside the systems you already run.
Building and Testing Your First Model
A step-by-step walkthrough of training a prediction model, evaluating whether it works, and interpreting the results, explained in plain English with no math required.
Choosing Your First AI Project
How to pick a problem that AI can actually solve, frame it as a prediction the system can learn from, and set yourself up for a first project that delivers visible value.
Is Your Data Actually Ready? A Practical Audit
A hands-on guide to auditing your operations data, finding the gaps that matter most, and deciding which AI project to tackle first based on what your data can actually support.
What "Learning from Data" Actually Means
A practical explanation of how AI systems learn from historical data, what that process looks like in an operations context, and why your existing data is the raw material for better predictions.
The Difference Between Rules-Based Automation and AI
If you have worked in operations for any length of time, you have already used automation. This lesson explains the fundamental distinction between the rules-based systems that power modern operations and the AI systems that are about to raise the ceiling.