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Learner Reviews & Feedback for Regression Analysis: Simplify Complex Data Relationships by Google

4.7
stars
430 ratings

About the Course

This is the fifth of seven courses in the Google Advanced Data Analytics Certificate. Data professionals use regression analysis to discover the relationships between different variables in a dataset and identify key factors that affect business performance. In this course, you’ll practice modeling variable relationships. You'll learn about different methods of data modeling and how to use them to approach business problems. You’ll also explore methods such as linear regression, analysis of variance (ANOVA), and logistic regression. Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you enhance your data analytics skills to prepare for your career. Learners who complete the seven courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate. By the end of this course, you will: -Explore the use of predictive models to describe variable relationships, with an emphasis on correlation -Determine how multiple regression builds upon simple linear regression at every step of the modeling process -Run and interpret one-way and two-way ANOVA tests -Construct different types of logistic regressions including binomial, multinomial, ordinal, and Poisson log-linear regression models...

Top reviews

EU

Jun 29, 2023

Covers a lot of content, but is well paced and easy to understand. Provides a solid foundation for further learning and exploration in regression analysis.

MC

Jul 12, 2023

For me this course was good. Lots of good information with clear examples and resources to keep digging into.

I recommended for the same reasons.

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51 - 75 of 80 Reviews for Regression Analysis: Simplify Complex Data Relationships

By Riaz K

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Jan 4, 2024

Best course ever

By Anitha m R

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Apr 4, 2024

Awesome content

By Remigiusz M U

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Jun 4, 2023

easy and simple

By BELGACEM G

•

Jul 20, 2023

Merci beaucoup

By Sapna S

•

Sep 6, 2024

best course

By axsh s

•

Jul 19, 2024

very nice

By Iryna R

•

Jun 20, 2024

excellent

By Janier R

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Aug 16, 2023

thank you

By Lucio L G

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Nov 24, 2023

Greattt

By Jae s J (

•

Nov 5, 2023

perfect

By Hiren K

•

Oct 10, 2023

Awesome

By Justin H

•

Nov 27, 2023

Brutal

By Tapas K

•

Nov 15, 2023

Great.

By serigne d l

•

Nov 4, 2023

Good!

By Katherine X

•

Oct 20, 2023

great

By ابراهيم س س ا

•

Sep 4, 2024

Good

By Guorong H

•

Jan 3, 2024

Be prepared to study really hard for this one by yourself. A lot of abstract information in module 4 and 5. Takes a lot of hard work for this one to truly understand every concept. Final project was also challenging and definitely pushes you out of the comfort zone since many concepts not taught, but will accelerate your learning much more than previous course projects which were too easy.

By sisi L

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Jun 26, 2023

This course introduces lots of useful regression models for data analysis. It also includes labs for using python libs to compute these models and interpret results. Absolutely fresh experience for me.

By Nishant B

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Nov 8, 2023

Found it a bit tougher to comprehend. More examples and formulas like the 'Logistic Regression' Module would have helped.

By mohamedsafwt a

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Apr 28, 2023

Extremely challenging incredibly for beginners yet rewarding.

By Karan P

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May 8, 2023

too deeper information. lab was nearly impossibles

By RM T

•

Jun 19, 2024

it's a good course for begginers

By Wassim R

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Jan 8, 2024

Thanks

By DHANUSH K K

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Aug 27, 2024

good

By Moulaye S D

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Nov 11, 2023

I would like to share a few observations. Firstly, the course is heavily focused on statistics, which might be challenging for someone specializing in mathematics. Additionally, in the final project, there is a notable absence of coverage on data engineering, despite appreciating the overall content. Upon completion, the course effectively covers a substantial portion of data science, but it would be beneficial to include more on data engineering.