Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7

stars

18,518 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 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.

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.

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By 21083010111 I R A

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Oct 21, 2022

good

By Aravind R

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Oct 15, 2022

good

By JAIPRAKAS G

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Oct 10, 2022

good

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Oct 6, 2022

good

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Jul 15, 2022

tuyệt

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Sep 6, 2021

great

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Feb 18, 2021

10/10

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Feb 16, 2021

Great

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Jan 26, 2021

great

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Oct 13, 2020

Great

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Aug 4, 2020

Great

By Pankaj S

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Jun 24, 2020

great

By Fernando P

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May 13, 2020

Nice!

By saiganesh g

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May 11, 2020

Happy

By Mauro M M R

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Mar 23, 2020

great

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Jan 18, 2020

goood

By Diego B

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Dec 18, 2019

great

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Aug 15, 2019

best!

By Kathleen P

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Dec 31, 2018

Great

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Nov 23, 2024

good

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Nov 20, 2024

good

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Nov 18, 2024

Good

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Oct 9, 2024

good

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Oct 6, 2024

Good

By TILAK K

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Sep 11, 2024

good