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

26,562 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


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.


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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326 - 350 of 5,824 Reviews for Introduction to Data Science in Python

By eshaan k

Feb 2, 2017

I certainly learnt a lot through this course. The hands on oriented approach of this course works wonders for those who intend to dig deeper and improve their Python programming. The lectures are crisp and clear, but the main learning happens while doing the weekly assignments. Each assignment forces us to go search for content beyond what has been taught in the lectures and in this process we find new things. Also, the lecturer informed us about some good reference books for individual learning. I look forward to taking part two of this course.

The mentors in the discussions forum are quite active and helpful. The forum was of big help to me for clearing the assignments. The only flaw I found was that the autograder does not clearly define our mistakes and that's where the mentors come in and explain in the discussion forum. This part could be better automated.

Finally, I believe that a prior introduction to Python programming is an essential prerequisite to this course.

By Tanya

Aug 21, 2020

There are a few negative reviews which have been given to the course due to the fact that it involves going through discussion forums and having to google a lot. Stories of how people gave up halfway. The videos being distracting and useless. I almost didn't take the course because of them.

I realise now, googling is actually the essence of coding. The videos of the course are not enough to pass the course or even understand the assignment. But that is how it is going to be in reality as well. No one expects you to remember syntaxes. You only need to be able to think up the logic, google your needs and hey presto - you'll have done the question in no time. It is going to require hardwork and patience, but the confidence you end up with is mind blowing. I am going to continue on to the next course in the specialisation. Wish you all the very best in your endeavours!

By Arpit G

Jul 2, 2020

This course gives the beginner an insight of data cleaning and using pandas from scratch. The assignments are well formatted and well prepared for the beginners to provide the basic details of using pandas and cleaning data. It also gives us a sight of the real world data that is how the data could be messed up and how by learning this course one can deal with the messed up data. Well this course was more an individual learning rather relying on video lectures but yes, while doing assignments one is fully prepared for cleaning data. So I would recommend everyone who wants to start with data science to go through this course and do assignments. As assignements taught me better than any of the videos or other materials could do. I would like to thanks Professor Christopher Brooks for making such a wonderful course on data science using Python !!

By Jeff C

Feb 28, 2017

The course was a very efficient intro to using Python to get data from various simple sources and the different structures that can be used to hold and manipulate the data. The course starts with the intuitive methods to solve problems and then introduces more complex and process friendly alternatives to demonstrate how creativity and knowledge of Python can be used to generate elegant and efficient code. The auto-grading of assignments can be a little maddening as the correct answer needs to be formatted precisely as is expected or else it will be counted as incorrect. The good thing here is that it forces you to fully understand the data types and data, the bad is it can be frustrating not knowing if the answer is wrong or just the format of the answer. Admittedly, I feel this effort forced me to become a better Python programmer.

By Arek B

Jul 24, 2022

Quick, but very rich course, with several optional elements, that I strongly advice to take/read in parallel (I used the good, old free library to find & borrow all necesary books). Sympatethic & friendly lead teacher, with excellent language & speaking skills. Supportive forum moderators and a lot of information to be found there. Some minor glitches (as in all Coursera courses), the exams are not so easy to take and the programming assignments reauire focus & diligence - but hey, we are supposed to learn and learn everything, in order to be ready to dig in all kinds of data, so... nobody said it will be cookies and candy ;-) And, after all, the assignments seem easy now, once you got the knowledge, haha ;-) Looking forward to continuing the excellent courses from UMSI ( School of Information). Cheers & thanks!

By Yusuf E

Mar 3, 2018

The assignments in this course are extremely challenging and almost unsolvable if not for the forum/stackoverflow help. Among the nine certificates I got on Coursera, this has to be the most difficult to obtain. It even surpasses getting and cleaning data or r programming in the Johns Hopkins Data Science specialization. Also, some more time on lambdas would really be appreciated given how important they seem to be in Pandas.

Having said that it was a real pleasure going through the assignments, repeatedly debugging them and getting to the answer finally. I have no complaints with the structure of the course or the contents. Given how easy the Python for Everybody specialization was this course was really refreshing. I hope for more of the same for the rest of the specialization.

By Haris N

Apr 27, 2020

I really enjoyed this course. The material was a bit sparse but the assignments were very well done, even though I've seen lots of people complaining about them. It is true that this course isn't beginner level and someone with zero programming skills will struggle, but since the specialization homepage mentions that the courses are 'Intermediate' I don't think that should come as a surprise.

The assignments were challenging but not challenging enough to be frustrating. One habit the course has inculcated in me is to refer to the documentation and build my own solutions rather than blindly referring to stack overflow.

All in all, a good course for someone already proficient in Python looking to develop expertise in Pandas. Not recommended for a complete novice though.

By Rajendra K

May 9, 2017

An excellent course, which requires more self learning than what is taught. I extended the course and completed the final assignment in a week. The assignments involving data cleaning actually helps a budding data scientist. Documentation, Stack Overflow for assignments is a must which can boost your understanding not just for this course but for a lot more. My personal satisfaction about this course is mainly stackoverflow part which helped me to understand the lectures weeks ahead. But application of the concepts on assignments is a difficult one which can only be mastered after practice. Thanks to all mentors, especially "Sophie Greene" whom I followed a lot. Her debugs, algos and code checks have actually helped me to understand both python and Pandas better.

By 刘宇轩

Dec 12, 2017

The aim of this course is to help us get familiar with pandas. If one has already been quite familiar with functions in pandas, this course could be too simple. However, as someone who is just new to pandas, I have to spend quite some time getting familiar with those functions so that I can finish the assignments.

This course really helps I think. As I moved along the course, I really find myself more familiar with the design logic of pandas and gradually work more fluently in assignments.

Besides, the mentor in the forum is so helpful and has provided lots of hints to help us move forward. I'm really grateful to it but still suggest that new students should really work hard on our own before skimming the forum, because some hints somehow cross the line.


Feb 4, 2017

This course taught ma Pandas and Hypothesis test, which are very useful in my study and future work. For example, I learned how to sort values, merge tables, and reset indexes. And most parts is like SQL.

Lectures will give some basic knowledge of the contents for each week. And this course also provide enough related documents, including codes and slides in classes. And it also has subtitle, which helps me a lot for my understanding.

When I was doing assignment, I still need to search more information from internet and learn by myself. I think this is a great way to help me know how to solve problems by myself. I think it is also a little bit challenging for a beginner, so I suggest beginner to learn some basic knowledge before taking this course.

By Gabrielle S

Sep 18, 2017

I'm very happy with the course overall, especially the challenges that the graded assignments offer. The lecture covers just enough detail to give you a broad understanding of the topic, but allows room for self-discovery, as in having to read the docs to accomplish your assignments. I'm happy with the quality of instruction and level of knowledge that the lectures have as well. The main instructor was very articulate and demonstrated a deep knowledge and a lot of experience with Python pandas, as well as statistics. The discussion forums have been extremely helpful throughout completing assignments, and got me moving from where I was stuck. I've certainly leveled up my python and pandas (especially pandas) skills from taking this course.

By Liam G

Jun 24, 2019

This was a superb introduction to Data Science in Python. Before I started this course I had completed a few introductory Python courses, but never felt confident enough to perform standard analyses in Pandas. This course has changed that and I am now confidently using it in my day job as a Data Analyst, helping me to automate some workflows, analyse data much easier and so on!

What is really great about this course is that it sets you up on Jupyter Notebooks to follow alongside each week's lectures, and then gives you an assignment to complete each week in a notebook. It really helped me get to grips with using notebooks, and debugging code and so on!

As a Data Analyst, and budding Data Scientist, I cannot recommend this course enough!

By Rahul S

Jan 26, 2018

A well rounded course that gives a good introduction into the scope and use of python in data science. Lectures were kept concise and to the point. The assignments were really useful as they used real world data and gave a good understanding of using python from the data cleaning stage to arriving at meaningful results.

One negative I may point out is that the time that is shown for assignments doesn't really reflect the time it takes in reality as people need to do quite a bit of self study for a lot of the questions. If you could increase the time showed, it would really help working professionals like me to plan their time for it accordingly.

A really good course with good course materials and helpful teaching staff!

By Purinut K

May 31, 2020

Even though, the title of the course is "Introduction" but to pass the assignment is quite complex and require a lot of understanding. You have to deal with struggling in Data in real life, such as unclean, remove header, unnecessary information in text etc. which is the most difficult part of processing the data.

I think this is a excellent course to learn how to deal with the data but will recommend it for the people who has quite strong background in programming. The first chapter is simple but do not overconfident. The second chapter can be very difficult to process data and get to know how to deal with dataframe. Once you uses to how to use "Jupyter Notebook", it will much easier though the rest of the course.

By Antonin P

May 15, 2018

Course is great. I have learned a lot, but I am affraid that the assignments are not for everyone. It is sometimes hard to find a way how to make an automatic grader to pass your programming assignment. I had to use a forum a lot, not to find a solution, but to find a trick how to convert my result to the correct format and so... In first assignment, it was poorly described how to submit it, for instance that the function can´t use variables from previous functions. However, thank you a lot for the course, I have learned Pandas and general Python even though I didn´t use them before. But I regret a bit of the time searching throughtout a forum when my results was right, but the grader didn´t let me pass through.

By Milan V

Sep 2, 2019

An excellent course. Given the restrictions inherent to this kind of format of teaching (e.g. very short 'lecture' videos), I do not think that the course could have been organised any better. In other words, one gets the feeling that one has extracted the maximum of knowledge possible, within the limitations of the Coursera platform. This is probably in part due to the 'hands-on' approach to the programming assignments, which I though to be very well thought-of. I would also like to praise the course staff for being very active on the Discussion forums, and trying to answer as many student questions as physically possible. In the future I will definitely continue with other courses in this Specialisation.

By Loïc B

Aug 27, 2019

A very good introduction to essential Python tools for manipulating data. I recommend taking this if you either know some Python but are new to data science, or if you have at least a basic grasp of how to manipulate data with other software. Users without prior knowledge in Python or data wrangling will find this course too hard.

Prof. Brooks is very clear, and the Jupyter notebook environment helps tremendously. I liked a lot the format of assignments as well, though meeting the requirements of the autograder can be tough sometimes... Another point on assignment: the version of pandas used for the course and the current updated version now differ a bit, so that some syntaxes may differ on a few functions.

By Benny P

Sep 19, 2017

As others said, this course is fast paced, has only brief information in the videos, and has challenging programming tasks that requires students to get the required information elsewhere that was not given in the intros. Whether you like it or not depends on whether you are able to learn by yourself (with guidance on what to look for) or do you want to be fully nursed. For me, I LOVE IT! The material has enough information that I need, and I don't mind searching for references myself. The programming tasks are also challenging as it requires you to be really careful in reading the specs, and that is good. If you're not able to enjoy this course, maybe you need to take other introductory courses first.

By Paulo E N

Aug 10, 2020

I really appreciated this course. The assignments are excellent, but they took me more time than the announced.

The ability to submit your assignments and have them automatically corrected, even if you are note paying for the certificate, is great.

I just think that maybe it is a "too hard" introduction. You must already know python, and, I'd say, should have already studied a little of pandas. The explanation of pandas is really quick, but full of valuable real world tips.

For the assignments you'll need a lot of pandas knowledge that isn't the videos, so prepare for a lot of searching in StackOverflow and in the docs. I believe it is purposeful, so the assignments mimics a real world problem.

By Karen Y

Dec 1, 2016

This is a popular course series that many have expressed interest in taking. Rigorous and challenging course that offers excellent, high quality teaching of python pandas. The University of Michigan does not disappoint and neither does the delightful instructor Christopher Brooks. I highly recommend this course to anyone serious about python and data manipulation. Time and money worth spent. Interesting assignments and datasets are found each week. You will learn a great deal. Concise videos with sharp insights from an expert on pandas are seen throughout. Once you finish the first course of the series, it leaves you excited for the second course in the series. Rock on "pandorable" pandistas!

By Deleted A

Jan 21, 2017

This was overall an excellent course, I very much appreciate everyone who has made this happen. However, the very last question of the very last assignment I found to be substantially more difficult than everything else, by a very large degree. Because of that one question I ended up moving my session twice and nearly dropped the course. is what finally got me over the hump. The instructions were not very clear to me but the price ratio calculation was the key to success. My guess is that missed it somewhere. Anyway, thanks! I will be moving on to the next course.

By Sabyasachi M

May 3, 2020

This is a very good course about the basics of data science and how python can be used to facilitate data cleaning and handling. I am a beginner with very limited knowledge of python (I had read some basics). The course takes you step by step through the use of python libraries and commands mostly used in data science. I would like to point out here that the assignments post course completion were a bit challenging for me as I am a beginner, which is good. This is because I had to research and learn a lot of stuff to complete the assignments apart from the course material. Looking forward to more such courses and assignments. Kudos to the teaching staff and Coursera team :)

By Tanmaya S

Jul 29, 2020

Excellent course that throws you to deep-end

Good explanation of basic concepts and learning through challenging problems. This course really pushes you to utilise open resources and refer to forums and standard text which, in my opinion, helps learner utilize full potential of MOOC's. Excellent course for understanding applications of python, but be ready to scavenge forums and refer to the documentation for hours to solve assignment problems.

It would have been really awesome if some more exhaustive guide regarding fundamentals was also provided which could improve understanding of functions applied in assignments even more

By Vijay P R

Nov 27, 2016

The programming assignments are challenging ( atleast for beginners),with each question taking about 3 hours to complete .Many topics in Pandas are covered , making us reading the docs and finding solutions,that further helps in learning . Excellent course , good support from other learners taking the course and very very informative . No other platform can give us a course ( and knowledge ) of this standard . Planning to take more courses from courseera . However a small feedback : The description for some questions are slightly confusing . Please make such questions more descriptive with examples .

By Aditya S

Jun 27, 2018

This is one of the best courses on coursera by offering, the instructor Christopher Brooks has a great ability to deliver a lot of information/knowledge in a concise manner! He is a great teacher. I really learned a lot from this course, and reading the course blogs like : science isn't broken, following the data skeptic podcast, joining in on discussions. The discussion forum has great methods by Sophie Green , the teaching assistant, with great stackoverflow links added. This course has a steep learning curve, but as much as it was tough, by and large it was worth every minute investing in it!