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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

CB

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The assessments, quizzes, and course coverage are quite good. The main points are covered, although it does not cover everything. Additionally, it provides opportunities to learn and conduct research.

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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4676 - 4700 of 5,941 Reviews for Introduction to Data Science in Python

By Sangram K S

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Jul 13, 2020

It was good. The session can be more interactive and interesting.

By Gian C T G

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Jun 25, 2020

Need more excersices examples, some homeworks are quite difficult

By Subha M

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May 31, 2020

The course was good. But few points were not that up to the mark.

By Anil K C

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May 6, 2020

Good assignments to get you to learn the Pandas library in python

By Sadia a S

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Mar 21, 2020

It is a helpful course for working with python for data analysis.

By Roy Y

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Jul 17, 2019

A great introduction. But assignment grading a little bit tricky.

By hadeer a

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Jul 15, 2018

The course was helpful, but the assignments weren't clear at all.

By Ahmed E

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Jan 27, 2018

It is a challenging course specially for beginners and assignment

By Dhruba s R C

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Aug 17, 2017

A very detailed course. A must do for Data Science enthusiasts...

By N181133 P L S

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Jul 18, 2022

Really this course is amazing and lots of stuff given.Thank you

By Partha S

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Jan 23, 2021

Its not an easy course and requires a lot of focus and attention

By MINGYANG Z

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Jul 15, 2020

The instruction of the homework is sometimes hard to understand.

By Julian L

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Jun 16, 2020

It would be much better if all the videos had Spanish subtitles.

By sourav g

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May 21, 2020

If you could also provide written material, that would be great.

By Bharath k M

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Dec 8, 2019

Good Experience and learning. Overall gained a good confidence!!

By Andrew T

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May 25, 2017

There were some gaps that were tough to bridge, but I got there.

By Fan Z

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Sep 19, 2020

The course is good in general but the grading system is a pain.

By Daniel

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Jul 1, 2020

Falto poner o darle incapie más a fondo a la libreria de pandas

By natalia r

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Apr 20, 2020

bastante bueno aunque mucho tema fue buscado independientemente

By Shunjiang X

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Jul 8, 2018

Very vigorous course. A little hard but will learn quite a bit.

By Filip J

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Sep 1, 2020

It was great but I lack suggested solutions after assignments.

By Igor Q

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Jul 6, 2020

great course. I would add more classes about the distributions

By Ananay S

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May 19, 2020

Great explained and top level content to learn the skills from

By Shashank S

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Sep 6, 2019

Assignment 2 was way too tough, as per the concepts covered :(

By Mark P

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Jun 14, 2019

challenging but reading forums and stack overflow really helps