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

4.5
stars
27,249 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

PB

Dec 29, 2019

It is a great course to get started in the field of data science. It just require basic knowledge of python. This course teaches you basics of numpy and pandas and how to apply them in data science

ME

Jul 26, 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 - 5988 of 5,988 Reviews for Introduction to Data Science in Python

By Abdullah A

•

Nov 11, 2025

old and fucked up

By Divyanshu K M

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Aug 13, 2021

not for beginners

By Delight B K

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Aug 9, 2020

too comprehensive

By Youjong K

•

May 26, 2022

Too difficult

By Haris I

•

Sep 1, 2020

Impractical

By Abdulrahman A

•

Dec 2, 2024

bad course

By Andrew K

•

Jan 18, 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 21, 2021

hjhjh

By Tarun

•

Aug 3, 2020

easy

By Raju C

•

Oct 2, 2023

Bad

By Eren K

•

Feb 1, 2023

ew