SPSS: Apply & Evaluate Cluster Analysis Techniques

This foundational course equips learners with the conceptual knowledge and practical skills needed to perform cluster analysis—an essential unsupervised machine learning technique—using SPSS. Through a blend of theoretical exploration and hands-on implementation, learners will define, differentiate, apply, and evaluate key clustering methodologies, including hierarchical methods, k-means clustering, and Two-Step cluster analysis. In Module 1, learners will examine the fundamental concepts of cl

• Explain clustering concepts and differentiate hierarchical, k-means, and two-step methods
• Apply preprocessing and clustering techniques in SPSS to segment data
• Evaluate cluster quality using BIC/AIC criteria, dendrograms, and silhouette scores

• Basic statistics knowledge
• Familiarity with SPSS or statistical software