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

4.5
stars
26,924 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

Sep 28, 2021

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.

HC

May 3, 2018

It's very useful specially for new learner because it only dives into the part of python that data science need. I strongly recommend to anyone even if you don't have experience in programming before.

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676 - 700 of 5,919 Reviews for Introduction to Data Science in Python

By Devashish S

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Jan 8, 2017

Really good course. Provides ample time to figure out things. Does not penalize for slightly late submissions which is good for busy people. Teaches the fundamentals and asks tougher questions in assignments. Does not spoon feed the answers.

By Hrithik S

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Sep 11, 2017

This is a great course. A very contentful course.

The best thing about the course is that it's challenging assignments..!!

I had faced a bit of problem in the lectures, as I had to watch the video multiple number of times to understand it..

By Mohit N

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Aug 31, 2017

If you are thinking of doing something in the field of machine learning and Artificial intelligence . If data science is your passin. if you love playing with numbers . if your math teacher is boring , you need to take this specialisation.

By Ian V

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May 3, 2020

Great course, but took a lot longer than I expected to do the homework assignments thoroughly. Instead of 2-3 hours, I usually took 5+ hours. The final assignment took me a really long time because of some technical problems with Jupyter.

By Henry W

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Nov 10, 2017

Great introduction to doing data science in Python with Pandas. Combined with the later courses in the specialization (the next one is Applied Plotting, Charting, & Data Representation in Python), you will have a strong command of Pandas.

By Victor D

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Jan 27, 2024

Good course by all standards. The questions are quite hard, and you'd need to read the documentation to find answers to these. I love the program!!! If you just want the certificate without putting in the work, then this is not for you.

By Tejas B

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Aug 17, 2019

Very much challenging course. I just love the way you guys presented and delivered stuff.

Extremely helpful for the further endeavor. I can't wait to continue with the remaining modules.

Special thanks to Christopher Brooks

Appreciated !!

By Inge J

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Oct 31, 2018

Great course. Well presented videos and relevant assignments.

One small thing on the negative side. The course runs on an older pandas version, you should really upgrade this so we don't have to google "how it was done on pandas 0.19.1"

By Sina R

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Nov 25, 2016

This course covers basics of pandas dataframes. So useful for amateur/advanced programmers who want to start learning data science. The assignments are very good and help students learn how to pre-process and use data retrieved from web.

By Y. N

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Dec 27, 2022

A great course! Solid content. Assignments helps you explore and consolidate what you learn.

The autograder could be a bit of nuisance but check out the discussion forums and you should be able to resolve the technical problems yourself.

By Wouter v H

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Jan 25, 2018

The difficulty of the excersises made it a good and challenging learning experience. Sometimes it was not possible to continue the rest of the excersises in the assignment if a previous question was not correct, this should be possible.

By Julio C C

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May 21, 2017

In the beginning I thought that the course should have more Tips and Help to the student.After finishing it, I understand that having the ability to search for the solution without too helping is good to produce the data science skills.

By Elisabeth

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Aug 4, 2021

Great introductory course for data analysis using pandas in python. I have some previous self-taught exposure to python and to pandas, and this was very helpful to formalize my knowledge & approach to analysis in a more structured way.

By John B

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Dec 11, 2020

I learned much in this course, but it's weighted more towards learning Python and Pandas than data science concepts. It was also very time consuming even for someone with programming experience due to the Python/Pandas learning curve.

By Sai G B A

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May 12, 2020

The course is on some difficult level..But doing assignments is like challenging your self to how much extend you know the programming skills. But we need to spend good amount of time on forums and stack overflow to clarify our doubts.

By Getnet C

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May 17, 2018

It is well structured course you will find online about Data Science. All the aspects of a MOOC: like reading materials, videos tutorials, quizzes and assignments are included. Three words for this MOOC: Simple, Elegant and Structured.

By Rohini G

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Jun 21, 2020

I was able to solve the assignments from the discussion and not really from the lectures. I am thinking I should have spent more time reading the discussions (like a textbook) than listening to the lectures. The lectures are too basic

By Dhimant G

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Apr 3, 2020

Challenging assignments, prompt response for queries raised in the discussion forum, 5 star for Yusuf for pushing in the direction of the issue without giving out too much, short crisp videos, forces you to refer additional resources.

By Suewoon R

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Oct 3, 2017

At first I thought it wouldn't take long because it consists of only 4 weeks but I was wrong! It did't take me a month but definitely more than I expected. Thanks to Coursera and U. of Michigan, I had get to practice a lot. Thank you!

By Kadapa S K R

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Jul 26, 2017

This course of data cleaning is very good. But the tips provided are very high level. It is not easy for a beginner to reach the assignment expectations. I encourage to provide more depth in data manipulation techniques with examples.

By Erick S G P

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Aug 16, 2020

The professors are excellent though videos are taught at a very fast pace, mostly at the end of the course where more difficult concepts are shared. The excercises are really challenging but made me feel competent when I solved them.

By William R C

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Feb 19, 2022

This is a difficult course. It is worth the effort. You need to spend a lot of time on research and prractice for the assignments. However, the skills you get are worth the effort and can be applied in a lot of programming areas.

By Allyson D d L

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Sep 27, 2021

This course is really amazing. The assignments are comprehensive and challenging, I loved them. But for me only 3 hours were not enought to complete them. I think this course could be divided in 5 weeks and have one more assignment.

By Yan Y

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Jul 24, 2022

This course needs some basic knowledge for pandas and numpy. Learnt a lot for pandas and function (if, for loop etc) by doing the assignment and research online. The discussion forum provides great help to complete our assignments!

By Praveen V

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Jul 3, 2020

this course has been very challenging for me. it pushed me to learn different things by myself and the assignments were really amazing.

thanks to you Mr professor, it was an amazing experience since this was my first online course.