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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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5176 - 5200 of 5,915 Reviews for Introduction to Data Science in Python

By Alexandre G

Sep 23, 2019

The lectures do not contain enough material to prepare you for the programming assignments. Programming assignments are challenging but the problems are not clearly stated, most of your work will consist in finding answers in Stackoverflow instead of looking for the answers in lectures or programming assignment instructions.

By Iana L

Nov 8, 2021

While the information provided is not bad and I liked the style of teaching, with the Jupyter Notebook, the assignments are unnecessarily ambiguous, to the point that you have to go through the forums simply to understand the meaning of the question and what to return. And the autograder mechanism was also quite misleading.

By 象道

Oct 27, 2019

the instructor guides students to pandas, not bad. the assignments are not difficult, but are poorly designed---it's hard to get the goals of functions, and one may not get them done without searching internet. just don't know what a function is supposed to return, and there's no enough explanation on the assignments.

By Aakanksha D

Jun 16, 2017

The Assignments are very good. But the video lectures are terrible. they offer no or very little Explanation what so ever of the notebook being displayed on the screen. The TA just reads the notebook instead of diving into what the functions are doing. The subtitles overlap with what people are writing in the journal.

By Tyler N

Jan 30, 2017

This course was over all okay. My primary complaints are that I felt that the class moved too quickly and relied too heavily on students to teach themselves through the Pandas documentation. The Pandas documentation is really only so-so and it would have been nice to have more guidance through the course materials.

By Deenadayalan P

Aug 25, 2020

the weekly assignments are so challenging.But the instructions are not clear enough.for each question,one has to adventure through the discussion forum to find what the question expects.Thank you for the discussion forum because there are enough good people to explain and ask questions in each and every dimension.

By Pablo B

Oct 7, 2019

Though I very much appreciate Dr. Brooks' traits when video lecturing: relaxed, informative, and often lucid-- I worry that students with little to no computer science background will struggle greatly with assignments. That is to say, there is a disparage between the videos and the expectations of the assignments.

By Ali R K

Nov 17, 2016

Contents are great and very relative. Exam is fair and reasonable. However students have to deal with an autograder for the scores and the autograder is not up to par for this course. The amount of time that you spend on learning during the course is only a fraction of time you spend to get through the autograder.

By Jonathan O

Aug 31, 2018

The assignments have bugs that become more and more present after browsing the discussion board so extensively. I think that it would be really helpful to eliminate any bugs in the grader, so that when you get a solution marked as correct, you can actually count on later problems building on a correct solution.

By Chris S

May 1, 2017

The course doesn't feel complete, the information and techniques used for assignments can be found completely online through documentation and instead this is merely an exercise for doing basic analysis through documentation rather than an explanation of python through data science (which is what I anticipated)

By Chima P

Jul 1, 2018

This course is a very nice course, though it wasn't close to being thorough, but it helped me to develop self learning skills and endurance in tackling problems. it also helped me to have a pattern of study for data science, providing me with assignments which tasked me and helped me in learning so much more

By 霹靂卡霹靂拉拉波波麗娜貝貝魯多

Sep 10, 2023

Easy to Understand, but there's some errors in the course. So go check Discussion when you get confused.har

Assignments is very very time consuming, especially when you're not an American, like me :(. The data cleaning process is somewhat tedious but I think it'll be similar to the messy data in real life.

By Raul M

Mar 6, 2018

The lectures are too simple. The assignments are difficult. You constantly need to google how-to to be able to complete the assignments because the code/functions are not covered by the lectures. But if you overcome that, the assignments challenge you in a way that you will learn good things about Python.

By Bernardo C F d O

Aug 29, 2020

I have learned many things in this course, but this is more related to the searches that I have done outside Coursera to find information and tools to solve the assignments. There is a great disparity between what is shown in the videos and what must be done in the tests, which also are poorly organized.

By Roman K

Feb 4, 2018

Interesting assignments but definitely not the best video lectures - very short and not enough explanation, can as well read a documentation on my own.

Overall is not a bad course, but either change the name from 'Introduction' to 'Intermediate'-ish or create a more comprehensive set of lectures.

Thanks!

By Sang Y

Aug 15, 2019

The auto-grader system does not provide any useful information for understanding why my answer is wrong. Many questions are not clear enough to understand what they mean, we need to adopt trial-and-error approach to find the correct answer. Finally I aborted on the second course of this specialization.

By Apoorva R A

Aug 10, 2017

The assignments contain questions which are beyond the scope of what is taught. Assignmwnt 3 was very useful specially from Data analysis point of view. Assignment 4 was lil difficult. In my opinion, more lectures on how to code specially for tough problems like those in assignments should be added.

By Amanda K

Jun 11, 2017

I think there could have been more thorough video instruction / preparation for some of the harder assignments. It would have been more helpful if the auto grader could give more detail as to what was wrong with the output rather than trying to find someone who had the same problem on the forum.

By Ana T M D

May 27, 2018

The knowledge you get in the lectures do not match the level of the assigments. You use way more time googling and trying to solve technical problems than actually learning Python. I wish the lectures included more examples, specially things you can later use in the assigments. And more theory.

By Juan A G

Aug 5, 2019

The course has a high level which is fine. The bad part is that most the knowledge you require to complete the assignments is not available in the content of the videos and you have to spend quite some time on internet. It took me way more time than the hours they say to complete the course.

By Matias R

Sep 28, 2018

The course is well explained. The grading mechanism is insufficient... in some exercises I arrived at the same result but somehow the answer would be graded as incorrect; and I could never find the formatting differences.

Also, I come from the R world, and I find Pandas extremely unintuitive.

By Hussein A

Sep 1, 2020

hard and you will pull your hair, but I guess that is their point. It would take them forever to teach you each functionality in Pandas, but the real way to learn is to go and explore. It is the most difficult way though. Expect to spend hours on this, but the reward at the end is worth it.

By Chris R

Apr 7, 2023

The grading software is horrendous, but the quizzes are fantastic. This course requires a ton of research if you do not know python very well.

In the end I did learn a lot. But also I wasted so much time because of all the bugs in the autograder.

This course has the potential to be great.

By Vishal T

Jul 1, 2020

Assignments are challenging and assignments must be related with the content not out of content of the videos.But in assignment they aren't related with those content of video but out of content of the teaching videos . So, it will be better if you improve the assignments. Thank you !!

By Himanshu K (

May 31, 2019

The course material was not enough. The assignment questions were good but in order to solve those questions I had to find a lot of things from stack-overflow and the python documentation . This was mentioned there but I still think the material was less according to the assignments.