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

4.5
stars
24,861 ratings
5,563 reviews

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

YY
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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401 - 425 of 5,507 Reviews for Introduction to Data Science in Python

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 Luis D H Q

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 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

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

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.

By Matt W

Mar 1, 2017

I overthought some of the homework (the forums will tell you to not do that) and wasted much time going a bit too far cleaning data, however my own hubris aside, it was a good course. I've been working in NNs for some time, but wanted to use more formal data science tools on top of that and add something to my CV. I wish these tools had been around when I was in grad school... le sigh.

By Aditya V

Jun 10, 2018

This course has been very helpful and has motivated me to pursue more in this field. Most of my concerns and doubts are addressed in the videos, the instructor's explanation is very clear and understandable. The only suggestion I have is, to lay a little more emphasis on the python terms pertaining to data analysis, so that the student will have a better understanding and memorizing.

By Abhilash V

Dec 24, 2016

A great practical course.This course will make you think and search a lot on stackoverflow,which is good because a lot can be learned by doing it ourselves.Then why this course because we need to know what to look for and this course gives us the basics and we will be able to do the assignments by ourselves .Its not really tough but will need some time to get all the answers correct.

By chenmeng

Jun 17, 2017

Well, this course is quite good. It's obvious that the staff put a lot of effort into the course. They answered students' questions and solved problems which helped a lot. I learned basic programming skills of Python and the usage of library of Pandas. The professor gave the outline of what you need to do and the most of the work is done by yourself. Very happy to take this course!

By Shihui W

Apr 5, 2020

It is too hard as a second course after 'Python Basics', I have to admit that I search a lot of tutorial to pass the assignment. I suggest more steps by steps examples should be given in the videos and/or readings. That would be much easier to understand and digest. But, overall, I learnt a lot in this course. And I will spent more time to review the content in this course. THANKS.

By Mgle A

Feb 27, 2020

Great course! The lectures explain topics very well. The assignments were challenging - you might want to do a beginners Python course before enrolling into this course. I liked that assignments were focused on independent learning where you had to go online and look for the answers yourself. I believe this form of learning is the most efficient one. Great course, highly recommend!

By alex s

May 24, 2017

A very clear introduction to using Pandas for handling data. The integration of Jupyter Notebooks in both the assignments and the in-lecture pop-ups was very effective. I also appreciated the balance of covering most of the material in lectures, but leaving you to track down some things for the assignments. I can only hope the next courses in this progression are this well done.

By Drew L

Jan 19, 2017

I'm an experienced data analytics professional re-skilling after being laid off. I really enjoyed this course. Professor Brooks' lectures were engaging and clear. I found the assignments to be great practice, although they were challenging for my level of programming experience.

I strongly recommend having some skill with python, particularly pandas, prior to taking this course.

By Rutamvar M

Aug 27, 2020

Great course to begin with. If you find this course to your liking you can enroll for the whole specialization. The instructor is fundamentally clear and easy to understand. Some of the codes may not make sense as of now, but I am pretty sure it will make more sense later on. I felt a little more content could be added to the videos and this would be even more easier to grasp.

By Patrick L

Apr 17, 2020

The whole course is quite demanding for me who do not need to use programming at work at all. However, it's challenging and I really feel that I have learnt something. Even the teaching staff are very helpful and the replies in the forum are very useful in completing the assignment.

The final project is a bit difficult but I hope that I could apply it in real life situation.

By Baochun L

Jul 3, 2017

After studying the course of Andrew on Machine Learning, I want to study a course , which focus on python. I once chose the Machine Learning Specification , but the course use the non open source python packages. And I tried this course. I used about 4 days to finish the 4 weeks, and get myself familiar with pandas though I have no experience on python and pandas programming.

By Shawn M

Aug 25, 2018

Great overview of Pandas and ETL using Pandas and Python.

Assignments and final project were challenging and realistic in terms of how you might use Pandas and Python in real world situations.

The auto-grading of projects can be annoying with error messages that aren't clear or accurate. If you aren't clear why an answer isn't accepted, then don't hesitate to search the forum.