Excel: Apply & Evaluate Unsupervised Clustering

This hands-on course empowers learners to apply, analyze, and evaluate unsupervised learning techniques—specifically clustering—using Microsoft Excel. Designed for learners with basic Excel knowledge, the course walks through the entire data clustering pipeline: from preparing and structuring datasets to building and refining logic-based cluster assignments. Learners begin by identifying and selecting relevant data attributes, then construct conditional logic using Excel functions to group entries into meaningful clusters. Through progressive stages, learners extend these clusters across datasets and visualize patterns using scatter plots. The course culminates with a workbook-wide review where students evaluate the effectiveness of their clustering logic and summarize their analytical outcomes. By the end of the course, learners will confidently use Excel as a lightweight yet powerful tool for clustering analysis—without relying on programming or external machine learning platforms

• Apply unsupervised learning techniques using Excel
• Analyze and evaluate clustering results
• Design clustering logic with conditional Excel functions
• Summarize and assess analytical outcomes

• Basic computer and internet skills
• Ability to read instructions and complete practical exercises