Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7

stars

19,480 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

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.

May 8, 2021

I love the practicality of this course. It's not just learning theories but you actually follow along. You only need a good computer and you learn serious staff taught in the best way possible.

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2751 - 2775 of 3,086 Reviews for Data Analysis with Python

By Germán G

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Mar 17, 2022

so so

By Sakhumzi D

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Sep 8, 2021

Decent

By KIRTAN K

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Oct 13, 2022

good

By moh a

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Sep 29, 2022

very

By Asmita K

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Jul 1, 2025

nice

By Dhruv R

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Mar 24, 2025

Nice

By Arpita D

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Nov 19, 2024

good

By LOKESH F

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Sep 11, 2024

nice

By SACHIN.S

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Apr 1, 2024

nice

By Dheeraj D

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Mar 29, 2024

good

By Sweeti S

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Feb 2, 2023

good

By Hesham M R

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Nov 10, 2022

easy

By Motlatsi M

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Dec 23, 2020

BEST

By Landyn C O

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Oct 6, 2020

good

By David H

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Mar 7, 2020

good

By Oseyi K

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Jul 12, 2019

good

By Abhi 0

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Apr 23, 2019

good

By Vigneshwaran P

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Mar 13, 2019

good

By Ayo S

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Oct 23, 2018

Good

By Sandesh L

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Sep 13, 2022

wow

By Momin P

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May 22, 2022

By vic l

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Oct 17, 2021

By Shubham S

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Mar 9, 2022

By Isaac S

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Jul 5, 2020

By MAHESH K W

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Jan 21, 2020