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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

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

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.

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3751 - 3775 of 5,915 Reviews for Introduction to Data Science in Python

By Sabina D

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Dec 11, 2018

For someone knows basic python only some of the things are explained really fast. However, you can catch up during the assignments. A lot of time for the assignments spend on finding possible solution on the forums. From one point of view it is good - so you can find you own style. Form another, if you work full time and have busy schedule - it will take much longer to finish all the assignments.

By David H

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Sep 19, 2018

The course projects rely on material not yet presented and the automated grading system is very sensitive. I struggled with the assignments because when I had a problem it was difficult to pinpoint the source. Some of the blame is on myself for not using the discussion forums sooner, but this is not my first coursera specialization in data science / programming and I can honestly say I struggled.

By HARJEET

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Apr 17, 2017

course material good, mentors very very helpful and active , as mentioned in one of the posts the expected output of an answer in pictorial form can help students a lot , and the assignments were a little on the tough side , even being from a programming background i had to put a lot of effort to figure out silly mistakes and complete this first course but a nice experience , keep it up coursera.

By Iqbal F

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Nov 21, 2016

The course is good and provide great challenges to do a lot of things with Python and Pandas. However, I find that its resource material sometimes lacking complex examples. This may be intentional in order for the students to learn from external resources as well. However, this can also causes difficulties for people who are not already familiar with Pandas before they start following the course.

By Sebastien D

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Mar 28, 2021

The course was really good and forced me to intensively check on my weak points which I really much appreciated. The only "weak" point of the course is the automated graduation, but it's just a question about getting accustom to it to better organize ones strategy to pass the certificated. Well done, good job Coursera and University of Michigan. It was really fun, I like it and will continue !!!

By Zhe W

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Aug 28, 2020

The course is a good introduction or overview of the use of Pandas, it's pretty concise so you def need a lot of self-learning beyond the short videos to be proficient with Pandas or complete the assignments easily. I spent more time than expected on the assignments because I'm totally new to Pandas. But the materials are overall pretty good and useful, giving you a guidance of learning Pandas.

By Nate B

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Jul 5, 2020

This course was very helpful as it gives great experience working with real world data, rather than clean and prepared datasets. However, I can imagine this course would be challenging for someone without a lot of experience. I think the course could also have been a lot better if there was a way to see what about out assignments were wrong or see the actual answer when the question was wrong.

By Raivis J

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Jun 13, 2018

Week 4 lectures could have focused slightly more on hypothesis testing, perhaps delving a bit deeper into the thought process and methodology of coming up with hypotheses, designing an experiment to prove it, executing it, summarising and interpreting the results, etc. Since this is major part of programming assignment in week 4, this could have made the lectures more interesting and relevant.

By Aayush K

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Dec 8, 2019

The course content was great. But I felt the course duration was very small as I was able to finish the course in two days. Prof. Brooks explained each and every concept in a very easy, understandable and lucid manner. In my opinion, this is a very beginner friendly course but the assignments will definitely be a bit challenging for people are intermediate and advanced in python programming.

By R S

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Oct 20, 2019

The assignments were far difficult from what was taught in the course. Significant amount of searching the web had to be done for finding syntax. It will be helpful if a helping hand is given in the form of most probable syntax that can be used in the form of pdf along with assignments. The syntax in the assignment were far more sophisticated than those taught as part of the video. Thanks.

By Ying F

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Feb 20, 2017

Very good class - but it does require quite a bit of outside study - reading up on stackoverflow. But after this class, the student will be able to have a very hand set of tools/skills to tackle datascience projects. BTW, python with the interactive notebook is very popular in actual datascience projects in the commercial sphere, so this class can be leveraged directly in the real world

By Anand M

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Dec 7, 2016

This course was much harder than anticipated given it was also my first introduction to Python. Knowing Python coming into this course will make it a lot more manageable. Overall it's an excellent course which touches upon a LOT of items. Given more time on each item, this course could span 10 weeks easily. I now have an understanding of Python basics along with Pandas and a dash of numpy.

By Asees

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Jul 18, 2017

The course was great. It provided the learners to search for various concepts on their own which really added the knowledge gained through videos. I feel that best method to approach a solution should be provided after completing each assignment because there was time when I used long approach to get answer whereas it could have been done in a short way too. Overall, the course was nice.

By Julia H

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Jul 1, 2018

This course is definitely not for beginners. I have a lot of experience working with data in other programming languages and found the assignments very challenging. Lectures are very short and do not really teach you the material - you mostly learn from doing the assignments, which are well thought out and mimic the types of projects that would be done in a professional/academic setting.

By Sujay D

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Mar 1, 2020

In the end I got what I needed from the course but it was more through assignments than the video lectures which go through concepts very quickly. The assignments are good / challenging and require you to spend good amount of time on google and stack overflow but you end up learning a decent amount solving them. The auto grader can be frustrating at times but the discussion forums help

By Muhammad S

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Oct 9, 2019

Excellent Course for beginners to start learning pandas and get a pretty good hands on experience in it. The course's assignments are really competitive for me who knew little python (not pandas) before undertaking this course. There is a slight sudden change of concept in week 4 that requires a lot of self learning if (like me) you have little knowledge of data analytics or statistics.

By madan m

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Sep 16, 2018

This is an amazing course, I got to work on the real life problems which was complex indeed. Completing every assignment was not easy, passed them after several attempts. I would say one downside is that I had to spend a lot of time googling and on stack overflow. just to give a feel, an assignment tagged 4 hrs takes nearly 20 hrs to complete. Its a great course, be ready to sweat out !

By Jay S

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Apr 2, 2017

This is a good course if you have had some experience with the Pandas module in Python prior to taking the course. Pandas is a very powerful module but it has a fairly significant learning curve. There are all sorts of free Pandas tutorials available on the web. I highly recommend familiarizing yourself with the basics of Pandas prior to taking this course or you will probably struggle.

By Raman K

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Jun 5, 2020

The course is designed in a good manner. I would prefer slightly more material in the videos. The exercises are good, they definitely took more time than assigned. A few times question in the assignment is not very clear (that need a bit of work). I definitely learn many new techniques by listening to the videos, changing the class room notebook and last but not the least assignment.

By Deleted A

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Jun 13, 2017

Nice introduction to using Python, but lecture vignettes moved a bit too quickly. Assignments required far more than what was presented in lecture. If not for a particularly heroic mentor, assignments might not have been doable for some like me. On the whole, though, I am grateful for the course and that, at the time I took it, all materials and assignments were available to auditors.

By Shilpa S

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May 22, 2020

The course contents are well structured but the video lectures are not enough to master the assignments. More detailed explanations could have been included, since its really difficult for a person who is new to PANDAS. The assignments were challenging. Feed back for the assignments submitted were not found so useful. Although, the course contents provide enough space for learning.

By Kai P H

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Apr 22, 2019

For me, this was a difficult course in which I learned a lot. I did not find the materials (videos etc.) provided in the course so helpful, but the assignments you get for your own programming are very close to real world problems and will give you real experience. So you will need some other material to learn, I recommend the book "Python Data Science Handbook" by Jake VanderPlas.

By Kedar J

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Jun 27, 2018

Unlike other courses the lectures are packed with new concepts so much that you can't miss even a minute to understand it. The assignments are fairly challenging. The only part frustrating was working with the grader. Often it won't work and you are left wondering what went wrong without a great explanation. Overall great first course in the series. Looking forward to the next one.

By Aibek C

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Mar 2, 2019

It was a challenging course as a lot of things in the assignments you have to learn yourself. But it was the right way to do as during the work often times one will get stuck on something without any step-by-step directions on how to solve certain issues. The only thing I didn't like about the course is a bit unclear questions in the assignments which took some time to figure out.

By Hrituraj S

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Jul 19, 2017

Overall, I liked the course but there were some flaws (not too big ones but still worth mentioning) - The way things were explained seemed more like just giving information about something rather than explaining it well (of course at times!). Exercises were really very good as they promoted individual learning more than just depending on what was taught. Recommended for beginners/