Advanced Statistics and Data Mining for Data Science

Description

Data Science is an ever-evolving field. Data Science includes techniques and theories extracted from statistics, computer science, and machine learning. This video course will be your companion and ensure that you master various data mining and statistical techniques.

The course starts by comparing and contrasting statistics and data mining and then provides an overview of the various types of projects data scientists usually encounter. You will then learn predictive/classification modeling, which is the most common type of data analysis project. As you move forward on this journey, you will be introduced to the three methods (statistical, decision tree, and machine learning) with which you can perform predictive modeling. Finally, you will explore segmentation modeling to learn the art of cluster analysis. Towards the end of the course, you will work with association modeling, which will allow you to perform market basket analysis.

This course uses SPSS v25, while not the latest version available, it provides relevant and informative content for legacy users of SPSS.

About the Author :

Jesus Salcedo has a Ph.D. in Psychometrics from Fordham University. He is an independent statistical and data mining consultant and has been using SPSS products for over 20 years. He is a former SPSS Curriculum Team Lead and Senior Education Specialist who has written numerous SPSS training courses and trained thousands of users.

What You Will Learn!

• Get familiar with advanced statistics and data mining techniques
• Differentiate between the various types of predictive models
• Master linear regression
• Explore the results of a decision tree
• Work with neural networks
• Understand when to perform cluster analysis and when to use association modeling

Who Should Attend!

• This course is suitable for developers who want to analyze data, and learn data mining, and statistical techniques in depth.

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