Cluster Analysis- Theory & workout using SAS and R

Course Overview

What does this course tell?
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About the course - Cluster analysis is one of the most popular techniques used in data mining for marketing needs. The idea behind cluster analysis is to find natural groups within data in such a way that each element in the group is as similar to each other as possible. At the same time, the groups are as dissimilar to other groups as possible. Course materials- The course contains video presentations (power point presentations with voice), pdf, excel work book and sas codes. Course duration- The course should take roughly 10 hours to understand and internalize the concepts. Course Structure (contents) The structure of the course is as follows. Part 01 - cluster analysis theory and workout using SAS - Motivation – Where one applies cluster analysis. Why one should learn cluster analysis? How it is different from objective segmentation (CHAID / CART ) Statistical foundation and practical application: Understand Different type of cluster analysis Cluster Analysis – high level view Hierarchical clustering – Agglomerative or Divisive technique Dendogram – What it is? What does it show? Scree plot - How to decide about number of clusters How to use SAS command to run hierarchical clustering When and why does on need to standardize the data? How to understand and interpret the output Non-hierarchical clustering (K means clustering). Why do we need k means approach How does it work? How does it iterate? How does it decide about combining old clusters? How to use SAS command to run hierarchical clustering When and why does on need to standardize the data? How to understand and interpret the output Part 02 - Learn R syntax for hierarchical and non hierarchical clustering Part 03 - Cluster analysis in data mining scenario Part 04 - Assignment on cluster analysis

We considered the value of this course from many aspects, and finally summarized it for you from two aspects: skills and knowledge, and the people who benefit from it:
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What skills and knowledge will you acquire during this course?
By taking this course on Cluster Analysis - Theory & Workout using SAS and R, the learner will acquire the following skills and knowledge:
1. Understanding of cluster analysis: The learner will gain a clear understanding of the concept of cluster analysis and its application in data mining for marketing needs. They will learn how cluster analysis helps in finding natural groups within data.
2. Different types of cluster analysis: The learner will be introduced to different types of cluster analysis, including hierarchical clustering and non-hierarchical clustering (K-means clustering). They will understand the differences between these approaches and when to use each one.
3. Statistical foundation and practical application: The learner will gain a solid foundation in the statistical principles underlying cluster analysis. They will also learn how to apply cluster analysis in practical scenarios, such as customer segmentation.
4. Interpretation of output: The learner will learn how to interpret the output of cluster analysis, including dendrograms, scree plots, and cluster assignments. They will understand how to make decisions about the number of clusters and how to standardize the data for accurate analysis.
5. SAS and R programming: The learner will acquire practical skills in using SAS and R programming languages for running cluster analysis. They will learn the syntax and commands required to perform hierarchical and non-hierarchical clustering.
6. Data mining scenario: The learner will explore the application of cluster analysis in data mining scenarios. They will understand how cluster analysis can be used to uncover patterns and insights in large datasets.
7. Assignment on cluster analysis: The course includes an assignment on cluster analysis, allowing the learner to apply their knowledge and skills to a real-world problem.
Who will benefit from this course?
This course on Cluster Analysis will benefit individuals and professionals in the field of data mining, marketing, and data analysis. Specifically, those who are interested in understanding and applying cluster analysis techniques to identify natural groups within data will find this course valuable.
Professionals working in marketing and data mining will benefit from learning cluster analysis as it is a popular technique used for marketing needs. By understanding cluster analysis, they will be able to identify target groups and tailor marketing strategies accordingly.
Individuals working in data analysis and research will also benefit from this course as cluster analysis is a powerful tool for exploring and understanding patterns within data. By learning cluster analysis, they will be able to uncover hidden insights and make data-driven decisions.
The course materials, including video presentations, pdfs, excel workbooks, and SAS codes, provide a comprehensive learning experience. The course duration of approximately 10 hours allows individuals to understand and internalize the concepts effectively.
The course structure covers various aspects of cluster analysis, including theory, practical application, and hands-on exercises. Participants will learn about different types of cluster analysis, such as hierarchical clustering and non-hierarchical clustering (K-means clustering). They will also learn how to use SAS and R to perform cluster analysis and interpret the results.