Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7

stars

19,059 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.

Jul 29, 2020

AN excellent course. Hands-on training on the cloud makes an individual really involved. So far the best online course I have ever taken, and I have learned Python programming a lot from this course.

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2151 - 2175 of 3,001 Reviews for Data Analysis with Python

By Mahesh H

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Mar 9, 2019

GOOD

By VISHNULAL M

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Mar 9, 2019

nice

By Subrahmanyam

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Mar 5, 2019

good

By Girish J

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Feb 3, 2019

good

By Jimut B P

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Sep 22, 2018

nice

By Oyarinu O E

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Jun 1, 2024

Yes

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Apr 11, 2022

hhj

By Usman R M

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Apr 27, 2019

top

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Apr 4, 2019

gud

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