Cluster Analysis, Association Mining, and Model Evaluation (Coursera)

What You Will Learn

- Cluster analysis and segmentation

- Collaborative filtering and market basket analysis

- Applications of classification- and regression-type prediction models

Course 3 of 4 in the Data Science Fundamentals Specialization

Syllabus

WEEK 1

Cluster Analysis and Segmentation

Welcome to Module 1, Cluster Analysis and Segmentation. In this module we will explore cluster analysis, a popular unsupervised learning algorithm. We will also review the two major styles of cluster analysis, and discuss potential applications to different industries.

WEEK 2

Collaborative Filtering, Association Rules Mining (Market Basked Analysis)

Welcome to Module 2, Collaborative Filtering, Association Rules Mining, & Market Basket Analysis. In this module we will begin with an explanation of collaborative filtering and association rules mining, and how these techniques are used to make automatic predictions. We will also take a closer look at the various common applications of market basket analysis.

WEEK 3

Classification-Type Prediction Models

Welcome to Module 3, Classification-Type Prediction Models. In this module we will begin with an explanation of how classification-type prediction models are evaluated for performance, and how a confusion matrix can help visualize that performance. We will also discuss the applicability of cluster analysis, and how it can be used to detect rare events such as fraudulent transactions.

WEEK 4

Regression-Type Prediction Models

Welcome to Module 4, Regression-Type Prediction Models. In this module we will review how regression analytics are used for both hypothesis testing and prediction, and how a scatter plot can be leveraged to better understand the relationship between two variables. We will also discuss the differences between correlation analysis and a regression analysis, and a look at simple vs multiple regression.