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.
Excel: Apply & Evaluate Unsupervised Clustering
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Recently updated!
September 2025
Assessments
7 assignments
Taught in English
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There are 2 modules in this course
This module introduces learners to the foundational steps required to prepare data and implement clustering workflows in Excel. It covers understanding and formatting datasets, selecting relevant variables, and progressively building clustering logic using Excel functions. Learners will explore both initial and advanced clustering strategies to construct meaningful groupings and analyze structured patterns in data through conditional logic and iterative refinement.
What's included
9 videos4 assignments
This module focuses on the final stages of clustering using Excel, where learners apply, verify, and visualize their clustering logic. Through iterative enhancements and scatter plot construction, students will learn how to visually validate cluster groupings and complete the analytical process. The module concludes with a comprehensive review and consolidation of all clustering activities, ensuring learners can confidently assess and present their results.
What's included
5 videos3 assignments
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