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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
18,485 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

SC

May 5, 2020

I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.

RP

Apr 19, 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.

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2051 - 2075 of 2,890 Reviews for Data Analysis with Python

By Tanmay S

Dec 1, 2019

Best

By Thilini H

Nov 17, 2019

good

By Mahendra S

Nov 9, 2019

cool

By Manea S I

Sep 10, 2019

nice

By Marouane E O

Sep 5, 2019

good

By Jacob J

Aug 12, 2019

good

By Yuan Y

Jul 15, 2019

good

By Miriam R

Mar 27, 2019

good

By Talha P

Mar 26, 2019

good

By Tejpraneeth

Mar 25, 2019

good

By Deleted A

Mar 10, 2019

good

By Mahesh H

Mar 9, 2019

GOOD

By VISHNULAL M

Mar 9, 2019

nice

By Subrahmanyam

Mar 5, 2019

good

By Girish J

Feb 3, 2019

good

By Jimut B P

Sep 22, 2018

nice

By Oyarinu O E

Jun 1, 2024

Yes

By Sai S P

Apr 11, 2022

hhj

By Usman R M

Apr 27, 2019

top

By YANAMADALA P

Apr 3, 2019

gud

By Rex S A

Nov 29, 2022

..

By Yacin A M

Nov 16, 2022

hi

By SHREYANSH J

Feb 3, 2022

gg

By Talha A

Sep 16, 2019

<3

By Hamza o

Oct 6, 2024

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