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

4.5
stars
26,898 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.

PK

May 9, 2020

The course had helped in understanding the concepts of NumPy and pandas. The assignments were so helpful to apply these concepts which provide an in-depth understanding of the Numpy as well as pandans

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426 - 450 of 5,915 Reviews for Introduction to Data Science in Python

By Ivan R

•

Jan 19, 2018

Immersive and challenging introduction to python/scipy libraries in just one month.

The thing I like the most:

Assignments make you think twice, they are challenging enough to make you investigate further on your own about a probable solution

What I disagree:

Time marked for each activity in course (specially programming assignmenent resolution) is non realistic, actually takes much more than 1..5 hrs to solve the assignment

By Ganesh J

•

Oct 25, 2018

Challenging course. Worth the time and effort I put in. Instructor and the material is excellent.

One suggested improvement could be the guidance for assignments could be tagged better. It takes a lot of searching before one can find the right material. Both Sophie Greene and Yusuf Ertas provide excellent support. But if the guidance or tips can be made easily disoverable, it would save a lot of time.

Highly recommend.

By Paloma M

•

Oct 24, 2017

Very nice introduction to the pandas library, with special focus on practical exercises. It might be a bit difficult if you have little experience with python, but it is not impossible. In my case, I needed more time than expected to finish my assigments because of my lack of experience with the language. Still, the forums are usually very active and the Teaching Staff is very helpful, so I'm glad I took this course.

By Alan J

•

Nov 18, 2016

Really awesome course. It is a kind of do it yourself course.The assignments are tough to crack. I think a little bit of programming experience is neccessary. The lectures themselves only give the basic knowledge. The assignments make you do research on the relevant topics. The autograder is pretty bad, it gives false negatives a lot of times, but that i believe is Coursera's drawback and they are working on it.

By Beatriz I

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Jun 16, 2018

This is a really good course if you are a beginner and want to learn Python. Assignments are not easy, but not impossible, and that is the best way to learn. After passing the course now I feel I need to stop and go over everything again to be able to make my code Pandorable, because right now I know it is not, it works, and I understand it, but I know it can be better. Thanks to the team for this great course!

By Varun S T

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Jul 7, 2020

A great course if you really want to build your knowledge and develop skills in respect to using pandas and numpy. The assignments are challenging to an extent and will make you dig deeper to find answers and ways to apply everything you learn during the week. A good example of a course where learning comes mostly from practicing what is taught rather than just watching videos and answering quiz questions.

By Georgi S

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Jun 23, 2019

Nice introduction to pandas. Lectures are short and give just a quick overview of the different sections while the main learning comes from the assignments which require more individual effort and self-learning. Material requires some basic prior knowledge of Python and/or experience in another programming language. Would definitely recommend this course to people interested in data analytics with Python.

By Sean Z

•

Dec 30, 2016

Excellent course for data analysis in python, although the assignments are quite challenging and time consuming for beginners. During the course, I wish I could access to the correct codes after passing minimum score so that I could compare what I did with what common practices would be. We all code in different ways to achieve the same outcome, but it would be nice to know the most efficient ways/styles.

By Nick P

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Jun 18, 2017

One of the best Python/intro to data science courses online. The assignments were sufficiently challenging and realistic, and I certainly learned new skills by completing them. I also appreciated the links to the articles and podcasts that gave me new perspective on my work. Also, a big thanks to Sophie and the other moderators on the discussion board, as the existing discussions were incredibly helpful.

By Soumyadeep P

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Jun 16, 2020

I did not expect that this would be so fruitful in my career.I was just exploring this portion of technology.Now I am kind of emerged in it.Thanks to University Of Michigan and the respected professors for giving me this opportunity and Coursera for giving such a platform.Sometimes it becomes hard to access the resources and knowledge like this ,but coursera made it very easy now to get access of these.

By Tanmay T M

•

May 31, 2019

Everything is taught from scratch, which makes this course very accessible- still requires effort, however will leave you with real problems,confidence and understanding of subjects covered.

It was very helpful and easy to learn.The quiz and programming assignments are well designed and very useful. Thank Prof. Christopher Brooks and Coursera and the ones who share their problems and ideas in the forum.

By Peter B

•

Jun 23, 2017

Very informative course. It's a little fast paced but you can always go back and watch the videos again. It teaches the basics of pandas with a focus on how to prepare your data before starting working on it

You certainly need to do your own research (Google, StackOverflow, pandas documentation) to complete the assignments.

The mentors on the forums are the best! Without their help I would have been lost.

By Cameron F

•

May 1, 2017

I appreciate this specialization's patience to begin teaching data science with such a thorough introduction to handling data in python. The lectures are concise, with 80-90% of my time time spent on the assignments. The creators of the course have a clear understanding that most of a data scientist's job is spent cleaning data, and it's incredibly important to get the practice offered by this course.

By Hari G S

•

Jul 30, 2019

One of the most satisfying and challenging online courses I've ever taken. It's a densely-packed, fast-paced course and the assignments can be a bit challenging. For the assignments, we are provided datasets that are similar to the ones that we are likely to encounter in the real world. This course also teaches us to refer the official documentation and where to look for when we encounter problems.

By Tucker S

•

May 9, 2019

This course was excellent! It is hard to believe this is an introductory course given the difficulty, but this course touched on all of the skills I was looking to improve as an amateur programmer / data scientist. I would highly recommend this to anyone who has a base knowledge in python / pandas, and I very much look forward to the other courses in the specialization. Thanks Christopher and team!!

By rough a

•

May 11, 2022

Great Great Great Great Course. Just too Good. After this course, I get to know why The University of Michigan is so famous. They give their hard work to build courses and curriculums just great courses. Thankful for their Aid. God Will Bless You Guys. Because you are just working for Humanity First then something else after that. Thank you very much for your Great work The University of Michigan.

By LDHQ

•

Jun 18, 2020

This course is perfect for understanding the basics of Data Science in real world scenarios applying python libraries such as pandas and numpy. The course assignments are interesting, but require a lot of investigation and self-learning. The instructor´s explanations are clear, and there are a lot of complementary activities. Python background is needed. Looking forward for the plotting curse. :D

By Jun Y

•

Apr 19, 2020

It seems to me self-learning is more important than watching the videos. Every time I used a lot of time in finishing the programming assignments.

Suggestions: give the standard answer of each assignment so that we can improve the coding skill. (yes its difficult in not showing to the ones who has not finished the assignment.But to those who wants to learn it is important. Thanks for the guiding)

By Harish S

•

Aug 12, 2020

One of the best courses i have taken up so far.I am really happy to complete the course gaining a vast knowledge in Data Science at the same time improving my python programming skills. I cannot express how good was the instructor(Christopher Brooks) and also i really thank University of Michigan for providing this course. I would really recommend this to my colleagues and friends . Thank You.

By ammara r

•

Jun 14, 2020

This was an extremely well designed course. Assignments were very challenging and I had so much fun doing them. Solving the assignments give a true sense of accomplishment. Special thanks to instructors and mentors who help students in understanding the assignments. This course could not have been completed without their help. Thanks to University of Michigan for offering this specialization.

By Andres M

•

Jul 15, 2022

Excellent course! It is demanding, as you need enough time to read the complementary material (book by Wes McKinney) and for the assignments. The videos of the instructor typing in the markdown cells as closed caption is not very didactic. Although what he says is absolutely relevant. The assignments are challenging and requires more time than what Coursera suggests (about 3h / assignment).

By Milan C

•

Jul 1, 2017

The course is very well structured from notes to assignments. Lecture content is to the point and lecture length is just right.

A lot of work has been put into the Assignments and Juniper notebooks. This element makes the course invaluable as you learn through practical experience. through well thought out and planned questions.

Thank you for making this quality of education available to all.

By Abdoulaye B

•

Nov 8, 2019

I have learned a lot from this course it is maybe the best course or one of the best so far. I come from a French-speaking country I learned English for six months before taking this course . However, what I like the most about this course is the way he is speaking.

I thoroughly recommend this course to everyone who wants to go for a career in Data Science because it is an excellent course.

By Nuno S

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May 21, 2019

Excellent course for students with some knowledge of Python, but not for the complete beginner. The assignments revolve around using pandas with real-world data and are the best way to solidify what was learned in the lectures. The exercises can be time-consuming and you'll end up perusing Stackoverflow and the pandas documentation often. It's nevertheless an investment that pays well off.

By Kevin L

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May 27, 2017

Excellent course, and very well taught. The projects are a bit difficult for beginners and will require independent learning as well as revising the lectures, but such is anything important in life.

The only thing I think the course can benefit from is a printed summary of lectures, since they can be quite dense with information! But I think the Jupyter Notebooks are a good inclusion as is.