Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7

stars

18,985 ratings

About the Course

Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge....

Top reviews

Apr 20, 2019

perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.

Jan 31, 2022

This is totally one of the hardest course I've ever taken on Coursera. It's packed with knowledge I did not know before. Definitely recommended for people who want to learn data analysis with Python.

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2651 - 2675 of 2,985 Reviews for Data Analysis with Python

By Bhavesh J

•

Jun 22, 2020

informaive

By NEERAJ G

•

Aug 21, 2024

very easy

By Vipin G

•

Mar 31, 2024

it's good

By Omer. K

•

Oct 11, 2021

excellent

By Daniel F V V

•

Aug 24, 2020

Good job

By Bayu T P

•

Aug 21, 2023

so good

By Isaac N

•

Dec 3, 2019

Thank's

By Veronica S

•

Apr 6, 2019

not bad

By Ezzeldin A H

•

Jul 19, 2023

V.GOOD

By Germán G

•

Mar 18, 2022

so so

By Sakhumzi D

•

Sep 8, 2021

Decent

By KIRTAN K

•

Oct 13, 2022

good

By moh a

•

Sep 29, 2022

very

By Dhruv R

•

Mar 24, 2025

Nice

By Arpita D

•

Nov 19, 2024

good

By LOKESH F

•

Sep 11, 2024

nice

By SACHIN.S

•

Apr 1, 2024

nice

By Dheeraj D

•

Mar 29, 2024

good

By Sweeti S

•

Feb 2, 2023

good

By Hesham M R

•

Nov 10, 2022

easy

By Motlatsi M

•

Dec 23, 2020

BEST

By Landyn C O

•

Oct 6, 2020

good

By David H

•

Mar 7, 2020

good

By Oseyi K

•

Jul 12, 2019

good

By Abhi 0

•

Apr 23, 2019

good