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

4.5
stars
26,999 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

SI

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overall the good introductory course of python for data science but i feel it should have covered the basics in more details .specially for the ones who do not have any prior programming background .

GS

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This course was fast paced but the material was interesting and not to complex. I can only recommend this course to anyone interested in Data Science and who already has a basic knowledge of Python.

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4576 - 4600 of 5,937 Reviews for Introduction to Data Science in Python

By Swapnil G

Dec 13, 2016

Assignments needs slight polishing. Otherwise course delivers what it promises.

By Shalha M B

Jan 25, 2022

This courser is one of the best course to learn data science according to me.

By Lionel P

Aug 24, 2021

Very good course. Sometimes the quiz questions were ambiguous. But it is fine.

By Ahmad B S

Jan 18, 2021

Very good course. I'd give it 5 if the assignment requirements are more clear.

By alvaro e a g

Oct 24, 2020

Hands on projects with a little feedback and a lot support from the community.

By kamisetty h

Jun 1, 2020

It is a good course but it would be better if they involve some more excersise

By Jiaqi

Dec 21, 2016

通过这个课程,学习了pandas和jupyter noterbook,都是非常好用的工具。作业很有挑战性,但是遇到问题都是自己解决,助教提供的帮助比较有限。

By Timo K

Apr 28, 2021

Very good course, but it took much longer for me than the estimated 31 hours

By 贺世哲

Feb 29, 2020

It's a nice course. But it's quite difficult for me to finish the assignment.

By Nihat I

Dec 7, 2019

It will be excellet if we can get more resources for learning. Thanks a lot .

By Lokesh V

Feb 25, 2019

since i'm a new bee to python i am expecting little bit slow of explanations

By CMC

Feb 9, 2019

Good introduction to pandas. The programming exercises were quite effective.

By Juan M M

Dec 28, 2017

Basic course to understand some important element in Data Science with Python

By Zargham k

Jan 21, 2021

course was good. But assignments are not designed well enough. so confusing.

By ANTHONIRAJ A

Jun 20, 2020

the course videos should be slower and concepts should be explained clearly.

By Haochen W

Jul 7, 2019

it is a fantastic coursera but the assignment is not relevant to the vedios.

By Anjali R

Jan 2, 2019

Thank you for educating and expertising us in new topics through this course

By Applied M

Apr 2, 2018

this coursed gives us a brief idea about data science using python libraries

By Churamani P

Jul 30, 2017

I think a little more explanation from the Professor would have been helpful

By Taewon M

Jan 25, 2017

It's great course, but the assignments are so hard to data science beginner.

By Sameeksha K

Aug 6, 2021

There are more functions that can be explained in pandas & especially REGEX

By Animesh K

Nov 18, 2020

Good course. Assignments are challenging. Overall good introductory course.

By Alonso G L

Feb 19, 2020

Great opportunity to learn pandas. Some previous experience is an advantage

By Anindita N

Sep 23, 2018

good but Statistical analysis part should be more explanatory with examples

By Matthew W

Oct 8, 2017

Contents are not hard but assignment need more practice and time to finish.