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Learner Reviews & Feedback for Introduction to Data Science in Python by University of Michigan

4.5
stars
27,255 ratings

About the Course

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses. This course should be taken before any of the other Applied Data Science with Python courses: Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Network Analysis in Python....

Top reviews

RA

Nov 19, 2016

Although the tests can be a bit fiddly, this is a great course if you already have a bit of background with Python and/or data cleaning. Lecture and tutorial videos are lean and information-dense.

ME

Jul 27, 2020

Quizzes were very challenging and interesting. I learned alot. The main drawback in this course is that the materials are insufficient to answer the assignments.And some questions were not so clear.

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5976 - 5989 of 5,989 Reviews for Introduction to Data Science in Python

By Rajat J

•

Apr 7, 2020

Very rushed through.

By Abdullah A

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Nov 12, 2025

old and fucked up

By Divyanshu K M

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Aug 13, 2021

not for beginners

By Delight B K

•

Aug 10, 2020

too comprehensive

By Youjong K

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May 27, 2022

Too difficult

By Haris I

•

Sep 2, 2020

Impractical

By Abdulrahman A

•

Dec 3, 2024

bad course

By Andrew K

•

Jan 19, 2022

Too quick

By Atheer B A

•

Aug 21, 2024

not good

By Hafiz M

•

Aug 22, 2024

wrong

By JULIO E M G

•

Sep 22, 2021

hjhjh

By Tarun

•

Aug 4, 2020

easy

By Raju C

•

Oct 2, 2023

Bad

By Eren K

•

Feb 1, 2023

ew