Regression Analysis: Simplify Complex Data Relationships
Master regression techniques and predictive modeling using Python. Learn linear and logistic regression for advanced data analysis.
Master regression techniques and predictive modeling using Python. Learn linear and logistic regression for advanced data analysis.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Google Advanced Data Analytics Professional Certificate program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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What you'll learn
Investigate and model relationships in complex datasets
Perform linear and logistic regression using Python
Evaluate and interpret regression model results
Apply ANOVA and Chi-squared testing methods
Handle categorical variables in regression models
Implement advanced regression techniques for predictive modeling
Skills you'll gain
This course includes:
4 Hours PreRecorded video
27 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 6 modules in this course
This comprehensive course covers advanced regression analysis techniques for data science and analytics. Students learn to model complex data relationships using both linear and logistic regression methods. The curriculum progresses from simple linear regression to multiple regression, ANOVA, and advanced topics like regularization. Through hands-on Python programming, learners develop skills in model construction, evaluation, and interpretation. The course emphasizes practical applications in predictive modeling and statistical analysis.
Introduction to complex data relationships
Module 1 · 2 Hours to complete
Simple linear regression
Module 2 · 7 Hours to complete
Multiple linear regression
Module 3 · 4 Hours to complete
Advanced hypothesis testing
Module 4 · 4 Hours to complete
Logistic regression
Module 5 · 4 Hours to complete
Course 5 end-of-course project
Module 6 · 9 Hours to complete
Fee Structure
Instructor
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