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

4.5
stars
26,897 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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151 - 175 of 5,915 Reviews for Introduction to Data Science in Python

By Hảo T K

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Nov 5, 2020

This is the only course worth in the specialization

By Sumit K B

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Mar 5, 2019

Great course to bulild strong base on Pandas.

By Mohammad T N

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Sep 21, 2020

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By John R

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Aug 13, 2018

It took me a while, but I finally figured out the problem with this class. The lectures provide some good information, but only rarely do they go into WHY a particular action/method/approach is used or WHY it will be important later. I had to do my own deep dives into available documentation to figure out how most of the functionality covered in lectures really works. This is not necessarily a flaw in the class, but it does mean the suggested time commitment for each week of class is significantly underestimated.

The assignments, while interesting, have the same issue as the lectures. Most of the time is spent using of Google to look up Pandas and Numpy functions or methods, or if we really get stuck, to see if someone on StackOverflow already addressed any questions you might have.

Put simply, the only different between this class and learning from a book is the class sets deadlines for the students to meet in the form of graded assignments.

Of course, the setting of deadlines is an excellent way to stimulate learning, and this is why I will continue on with the Data Science specialization.

By Stephen L

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Jun 17, 2020

The course will teach you basics of the Pandas library, which is an essential skill. It also gets involved with some issues related to data cleaning, which is also essential, but felt a little like

There is very little peer-to-peer learning because there are no practice sets that peers can talk over, only assignments which Coursera's Honor Code naturally prohibits discussing. Hence, the learner never sees optimized code for solving real-world problems. I'm pretty sure I would have learned more if this course had provided more practice problems for learner discussions. For example, very inefficient iterations can be used to solved problems that should be solved in better ways with Pandas. I know that sometimes I was doing it right, but I think sometimes I wasn't and it would have been nice to see better code.

By Akshat

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Jan 30, 2022

+The assignments are quite challenging and test learning properly. (took me 12+hrs to finish assignments for week3/4)

+The videos were informative.

-A lot of very common functions, methods and constructs aren't given in the video and there is no supplementary reading material. You have to rely on other webistes/stackoverflow for a lot of your learning.

-A few parts in the videos felt rushed, many useful constructs skipped in some topics.

-Explanations of some fundamental concepts was missing.

OVERALL IMPRESSION : Take this course if you are willing to do a lot of self-learning outside of the course and already have some degree of proficency with python.

By Marika T

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Dec 31, 2020

This course was really helpful for me to gain some knowledge and strengthen the old one, especially I liked the recommended book. The lecturer touched the absolutely useful topics and made me to read and practice beside this course. But, I'll be honest, assignments were really hard for me, maybe because of lack of my experience in Python, but, anyway, I had to search on Google and sometimes find answers of questions, analysis it and than write them on my own.

My recommendation would be to make the course more comprehensive and thorough.

By Nattawat B

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Apr 2, 2019

This course is very tough. For those who have just learned how to code python will take up to 8 hours for each assignment. The auto-grader required an exactly solution for the answer and sometimes the answer is corrected but you it give you wrong and you have no idea why it is wring just because the type of return value are different!

Apart from those things, you will learned and accomplished alot from this course.

By James C

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Nov 24, 2020

More challenging material than the introductory courses. Requires reading in the text book, reviewing the exercises in parallel in Jupyter Labs, and reviewing the lectures. The assignments occasionally had ambiguity which cost some time in solution. In general moved my understanding of Pandas greatly forward. Will start using Pandas in work as opposed to Excel.

By Deleted A

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Nov 29, 2020

Assignment 4 is worded so badly and the code that was placed by the course author is so misleading (the return function the course author wrote in themselves returns two numbers only for the hidden test to come back and tell you need just one). That it is the reason I am knocking a star of its course.

By Low Y

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Sep 5, 2020

Very helpful for beginner in Python to build up a solid understanding and practical experience in pandas and NumPy library for querying, merging, grouping, and aggregating data frame.

However, the old version of python library in the auto-grader brings some difficulties for grading assignments.

By Shushant G

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Dec 28, 2020

The course is Excellent for new learners to start in the field of data science.

The Only reason I'm not giving this course a 5-star rating because it's a bit fast course. I mean from one week to another, things change a bit too much. Although best would be for me to give it a 4.5 star...

By Willber d S N

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Mar 21, 2019

Great Course!! You learn alot about Python for data analytics. It is very hard for someone that is beginning to programming. But there are a lot of recourses on internet that can help you. I recomend this course for all that need learning data manipulation with python.

By WASEEM A

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May 5, 2019

The course is good but it gets challenging in doing assignments since you have to a lot of learning at your own , video lectures cover a limited domain of weekly projects. over all this course will help you learn new stuff.

By Lukhi Y R

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Dec 4, 2020

Tag for this course should change Intermediate to Advanced level. Course is pretty good with challenging assignments but prerequisite, define in course are not match appropriate. Please, make changes above mention.

By vinod k

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Apr 6, 2019

Assignment questions were not clear. I made lot of assumptions and went through forums to get clear picture. It would be good if the question is explained in more descriptive manner

By Pedro S

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Oct 12, 2020

Assignments are pretty hard. I suggest raising the number of classes, because some topics are not explained.

By Shireen G

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Mar 7, 2021

Requires a lot of self-learning to finish the course. Assignments are exhausting but worth it.

By Ashish K P

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Sep 17, 2020

the language is quite difficult to understand and the the course neede more detailed lectures

By Randy M

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Aug 11, 2018

I have taken my Pandas skills to a new level as a result of this course.

By Haomin C

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Jan 9, 2021

The materials and assignments are quite difficult for a beginner.

By Akella H P

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Sep 28, 2020

Great course. learned a lot from it

By Mr. L E S

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Jul 18, 2018

Assignment 3, question 1: The autograder would mark this answer correct even when the data in the DataFrame was wrong. I discovered this after I answered the question, was told it was correct, but I produced wrong answers for subsequent questions that depended on the first one. Messages from fellow students in the forum helped me track down the problem.

Assn. 3, question 2: This was worded very awkwardly and the Venn diagram seemed to contradict the question rather than clarify it.

Assn. 4, question 1 ("get_list_of_university_towns"): The function template provided has a long comment block that seemed to be complete instructions for what the function should do. However, there are two other different versions of the instructions for this assignment in the Coursera course resources section and Google Drive. If the function template includes instructions in the comments, they should be complete. Otherwise, don't show them at all and let the student get the instructions from the other document. Also, the course's "Resources" section doesn't seem like the correct place for these instructions. They should be under the "Instructions" tab of the assignment submission page.

The instructor, teaching staff, mentors, etc. are almost completely unhelpful or extremely slow to answer questions. With regards to my forum postings for assn. 3, a staff member replied only recently, about two weeks after I asked the question. Since then, I've completed that assignment and the one following it!

The course videos are difficult to watch. Whenever Mr. Brooks shows how some code works in Jupyter Notebook, he uses a full-screen view of his browser. On my laptop with a 15-inch screen, his font is a little too small to read easily. I need to concentrate so much more on deciphering the screen that I can't easily keep up with what he is saying. Sometimes I wanted to view the course video on my phone or mobile device. At those times, it was impossible to read the screen being shown. I recommend these alternate ways of showing the code:

Use slides. Students usually don't need to see the instructor typing in real-time. Show a slide with the code and the result.

Use a large font. If showing real-time input and results is important for a specific question, use a large font or zoom in the display as much as possible.

There were some small mistakes made in the videos and assignments that make me think all the materials need some proofreading and updates.

Overall, I'm glad I took the course. I wish several things were better, though. I'm looking forward to the next course of the specialization (data visualization), which is the one I was most interested in taking. I took this course because I would need it for the final certificate and I wanted to be sure I didn't miss any information that would be helpful in the second course. I thought maybe the first course wouldn't be interesting to me, since I have many years of Python programming experience. However, I was pleased to find that the course covered a lot of pandas features and some of the mathematics and statistics techniques that I haven't used in many years, so those contributed to making the course challenging. I would prefer to have done without the additional challenges related to autograder technical shortcomings, though.

By Gina G

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Apr 6, 2020

I think all the assignments in this course are interesting and well designed. I learned more from doing the assignments than watching the videos. Yes, it took me a lot of time searching and reading stack overflow and other similar resources, but I did learn from them.

Most of my frustration was in fact coming from their outdated Autotrader - for those who plan to do the assignments on local Jupyter Notebook, you'll run into some confusion and frustration with their Autograder as their Pandas are not as updated as your Pandas. This means that even though your code can run perfectly correct on your local, it doesn't mean it would do the same with the Autograde after you uploaded for grading. I spent tons of time, not on debugging exactly, but on figuring out why my code won't just execute after submission. I guess my advice to avoid similar frustration would be just writing assignments in the Jupyter Notebook on Coursera.

As for the video lectures, I agree that they could and should be made better in terms of pedagogy. I'm sure the professor and the teaching assistance are absolutely knowledgable on the subject, but their teaching style is way too stiff. Basically they were just reading off a prepared script, which was not colloquial at all, and they rush through it. I don't think coding skills can be taught in the way of lectures as if delivering a TV speech. Honestly, lots of free youtube videos are better at online teaching than this course.

This is an intermediate level course in python, but entitling it as 'Introduction to Data Science in Python' kinda devalued how much of strength people have to spend on finishing it.

But all in all, I did learn a lot from completing this course, thanks to the well-designed assignments. I would recommend this course to those who wouldn't mind spending more time doing their own thinking and research.

By Zhe Z

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Feb 3, 2022

Pros:

1: The content of the course is really good. A lot of important staffs of Numpy and Pandas were given.

2: Even though the homeworks were a little bit difficult, I could practice what I learnt during the video through the homework. This helped me better memorize and grasp the knowledge.

3: The TAs in the forum were really nice and helpful. They tried their best to answer every question raised by the students. They even summarized the algrithoms to solve the homeworks and pointed out the bugs of the system. I definitely would like to give the TAs a star.

Cons:

1, There are a few bugs in the autograder system. I had to adjust my right codes to go around the bugs of the autograder. This is a little bit ridiculous. I wrote right code with correct answer but I could not pass the autograder bucause the autograder had bugs! Obviously, these bugs had been raised by other learners for quite a long time. However, it seems the Prof.'s team didn't listen to the voice of the customers. They should improve the autograder to give the learners better experience because we paid to learn.

2 Some of the problems of the homeworks were not very clear.

3. The teaching style of the Professor is not my taste. I felt like he was just reading the content of a text book. A lot of new things popped up during the course without any explanation. The structure of this course was not well organized.