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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
19,572 ratings

About the Course

Analyzing data with Python is a key skill for aspiring Data Scientists and Analysts! This course takes you from the basics of importing and cleaning data to building and evaluating predictive models. You’ll learn how to collect data from various sources, wrangle and format it, perform exploratory data analysis (EDA), and create effective visualizations. As you progress, you’ll build linear, multiple, and polynomial regression models, construct data pipelines, and refine your models for better accuracy. Through hands-on labs and projects, you’ll gain practical experience using popular Python libraries such as Pandas, NumPy, Matplotlib, Seaborn, SciPy, and Scikit-learn. These tools will help you manipulate data, create insights, and make predictions. By completing this course, you’ll not only develop strong data analysis skills but also earn a Coursera certificate and an IBM digital badge to showcase your achievement....

Top reviews

AM

Apr 16, 2023

Thanks for course! I met some errors, described them in your forms. I liked every models, but the final assignment was not interesting. I think it can be done better, with decisions and conclusions.

MW

Nov 11, 2021

Good Course. Very good overview of Python libs -Pandas, Numpy, Matplotlib, Scipy, Scikitlearn and Seaborn. I really enjoyed learning about them and seeing the usage. Highly recommended course.

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2126 - 2150 of 3,106 Reviews for Data Analysis with Python

By Pankaj S

Jun 23, 2020

great

By Fernando P

May 13, 2020

Nice!

By saiganesh g

May 11, 2020

Happy

By Mauro M M R

Mar 23, 2020

great

By kuncoro a n

Jan 18, 2020

goood

By Diego B

Dec 18, 2019

great

By Arnab C

Aug 15, 2019

best!

By Kathleen P

Dec 31, 2018

Great

By BHUMIKA H S

Dec 14, 2025

good

By สิริภัสสร์ ป I

Nov 21, 2025

well

By Akash G

Nov 10, 2025

Good

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Oct 30, 2025

good

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Aug 29, 2025

good

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Aug 23, 2025

good

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Aug 2, 2025

good

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Jul 25, 2025

Good

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Jul 23, 2025

Good

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Jul 23, 2025

good

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Jul 21, 2025

good

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Jul 10, 2025

good

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Jun 22, 2025

good

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Apr 4, 2025

good

By Md H R

Mar 25, 2025

best

By Geetha K

Mar 18, 2025

good

By Niladri P

Feb 26, 2025

Good