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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

YH

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This is the practical course.There is some concepts and assignments like: pandas, data-frame, merge and time. The asg 3 and asg4 are difficult but I think that it's very useful and improve my ability.

PB

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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

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4601 - 4625 of 5,940 Reviews for Introduction to Data Science in Python

By Alonso G L

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Feb 19, 2020

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

By Anindita N

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Sep 22, 2018

good but Statistical analysis part should be more explanatory with examples

By Matthew W

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Oct 8, 2017

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

By Thibaut L

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Jul 11, 2017

interesting but could provide some mathematical background for further info

By Rajib K

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Feb 12, 2021

I would prefer to have a generic assignments, this is too much US centric.

By Tarush B

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Jun 14, 2020

The focus was on self study and that was really a good learning experience

By Karan M

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Jun 23, 2019

Excellent course with lots to learn, but also loads of self learning to do

By Jesús P A

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Feb 23, 2017

Perfect to get hands on with python programming for data science purposes.

By Niraj K

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Dec 22, 2016

Great course, Gives good outline to navigate through the essential content

By John T J

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Oct 12, 2022

Good overall. The assignments have some problems with ambiguous wording.

By yasmina D

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Jul 17, 2020

i wish we could have some practise assignements like in the other courses

By Anuj K

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Jan 21, 2020

Coding environment should be improved. Assignments should be more guiding

By Anurag M

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Jan 6, 2020

Assignments are really good but the pace of teaching can be improved upon

By Bernardo J

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Dec 15, 2017

The assignment materials in the 3rd and 4th week need a SERIOUS make-over

By Ng Y H

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Nov 19, 2017

The lecture python examples could be closer to the homework requirements.

By Kevin D

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Jul 26, 2017

Interesting course with pretty useful interactive programming assignments

By Jorge G

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Aug 30, 2021

It covers necessary topics for my job purposes, but it's not sufficient.

By Karan K

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Apr 30, 2020

It was great experience learning the basics of data science with python.

By Daniel M

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Nov 18, 2019

Very clear and straight to the point, yet a bit advanced for a beginner.

By dibyaranjan s

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Oct 10, 2019

assignments are a bit tough, some of them are advanced than the teaching

By dhara a

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Jul 20, 2019

it is really nice course which gives you complete basic of data analysis

By Deleted A

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Mar 6, 2019

could have explained Hypothesis testing in better way with good examples

By AKI

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Jan 29, 2018

great course!but some assignments lack of clear instruction or mistakes.

By Carolina F A

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Oct 27, 2017

The course is pretty good. However, the tasks are no easy to understand.

By Mikhail

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Apr 5, 2017

Sometimes need more words in tasks, so it can help understand it better.