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Machine Learning and AI Foundations: Clustering and Association Course

Machine Learning and AI Foundations: Clustering and Association Course
Data Science

Machine Learning and AI Foundations: Clustering and Association Course

Unsupervised learning is a type of machine learning where algorithms parse unlabeled data. The focus is not on sorting data into known categories but uncovering hidden patterns.

Unsupervised learning plays a big role in modern marketing segmentation, fraud detection, and market basket analysis. This course shows how to use leading machine-learning techniques—cluster analysis, anomaly detection, and association rules—to get accurate, meaningful results from big data.

Instructor Keith McCormick reviews the most common clustering algorithms: hierarchical, k-means, BIRCH, and self-organizing maps (SOM). He uses the same algorithms for anomaly detection, with additional specialized functions available in IBM SPSS Modeler. He closes the course with a review of association rules and sequence detection, and also provides some resources for learning more.

Click here to enroll in Machine Learning and AI Foundations: Clustering and Association, the best course out there for beginners by the top instructors of LinkedIn Learning.

Machine Learning and AI Foundations: Clustering and Association Course

All exercises are demonstrated in IBM SPSS Modeler and IBM SPSS Statistics, but the emphasis is on concepts, not the mechanics of the software.

Earn a sharable certificate

Share what you’ve learned, and be a standout professional in your desired industry with a certificate showcasing your knowledge gained from the course.

  • Showcase on your LinkedIn profile under “Licenses and Certificate” section
  • Download or print out as PDF to share with others
  • Share as image online to demonstrate your skill

Start your free trial month at LinkedIn Learning (if you haven’t already), and enroll in Machine Learning and AI Foundations: Clustering and Association.

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