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Online Machine Learning Tutorial: Customer segmentation with K-means

Event artwork for Online Machine Learning Tutorial: Customer segmentation with K-means

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About this event

What to expect

Learn practical customer segmentation using the K-means clustering algorithm in this hands-on Python tutorial. Hosted by Aurelie, a recent MSc Artificial Intelligence graduate from the University of Limerick, this online session guides you through building a real machine learning model using Scikit-Learn and a publicly available dataset.

What You'll Learn

This tutorial takes you through the complete machine learning workflow for customer segmentation:

  • Data exploration and cleaning — understand your dataset before diving into modeling
  • Data preprocessing — prepare data for optimal model performance
  • K-means clustering implementation — build and train the model using Scikit-Learn
  • Practical application — work with a real-world dataset (the specific dataset will be revealed during the session)

You'll receive a complete Jupyter notebook containing all the code, detailed explanations, and the libraries used. The hands-on format means you'll be coding alongside Aurelie throughout the session.

Format and Requirements

The tutorial takes place live via Zoom and uses Google Colab, which means zero setup required — no installations, no environment configuration, just sign in with a Google account and start learning. This approach removes technical barriers and lets you focus entirely on understanding the machine learning concepts.

What you need:

  • A laptop with internet connection
  • A Google account for accessing Google Colab
  • The Zoom link (provided before the event)

Who Should Attend

This session welcomes anyone interested in machine learning and customer segmentation. Some familiarity with Python or another programming language is helpful but not essential — Scikit-Learn's high-level API handles much of the complexity, and Aurelie guides you through each step with clear explanations. Whether you're exploring AI for the first time or looking to add clustering techniques to your data science toolkit, this tutorial provides practical, hands-on experience.

What You'll Take Away

Beyond learning K-means clustering, you'll leave with a reusable Jupyter notebook that serves as a template for your own customer segmentation projects. The notebook structure and methodology can be adapted to different datasets and business scenarios, making this knowledge immediately applicable to real-world problems.

Aurelie runs monthly machine learning and deep learning tutorials,

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