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學生對 密歇根大学 提供的 Introduction to Data Science in Python 的評價和反饋

24,120 個評分
5,405 條評論


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....



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


overall the good introductory course of python for data science but i feel it should have covered the basics in more details .specially for the ones who do not have any prior programming background .


126 - Introduction to Data Science in Python 的 150 個評論(共 5,326 個)

創建者 John R


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.

創建者 Stephen L


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.

創建者 Marika T


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.

創建者 Nattawat B


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.

創建者 James C


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.

創建者 Deleted A


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.

創建者 Low Y


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.

創建者 Shushant G


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...

創建者 Willber d S N


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.

創建者 Waseem A


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.

創建者 YASH R L


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.

創建者 vinod k


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

創建者 Pedro S


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

創建者 Shireen G


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

創建者 Ashish K P


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

創建者 Randy M


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

創建者 Haomin C


The materials and assignments are quite difficult for a beginner.

創建者 Akella H P


Great course. learned a lot from it

創建者 Lance E S


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.

創建者 Gina G


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.

創建者 Aarya P


The basic skill on how to get data from the csv files and excel files. Cleaning and manupulating and making dataframes are taught in the course. I am giving a comparitvely low score because there are multiple things i didnt like:

The professeor and the tutor in the video lectures are too boring. Straight forward they keep on taking and playing a video in which the codes are written at lightning fast speeds.

It becomes hard to keep up with learning as it goes super fast. They just keep on talking before a letting a person digest the syntax of code.

The assignments were super difficult for a beginner like me and the questions wording omgggg! The questions aren't framed well at all had to keep searching the discussion forums.

Not for the beginners course as it becomes too difficult to keep up with. Just keep searching forums in the clue of getting the syntax. Really i was not much impressed by the professor. They should definitely make it more interactive rather than super boring.

創建者 Sercan B


Assignments should be peer-reviewed. Spent most of my time trying to figure out why my code run successfully on Jupyter Notebook but not getting any grades on Coursera Grading system. Especially the Assignment 3 was a nightmare for me. Eventough I was getting the right outputs on Jupyter Notebook I had to spent several extra days to fit my code for the Coursera Grading System. Apart from that assignments are forcing learners to get more insight in python individually, which was great for me. If you're total beginner to Python there is very high chance that you may drop the course due to assignments.

創建者 Robert S


The course was frustrating in the occasional lack of specificity in the assignments, which led to problems with the grader. I assume that these resulted in the replacement by a new course, which unfortunately does not begin until after I had already completed this. The lectures by Prof. Brooks sometimes covered the material quickly without developing the points step by step. The lectures by the assistant were very difficult to follow. The assignments were challenging and I have a sense of accomplishment having completed them all.

創建者 Aman j


Concepts could have been taught with more explanation. I prefer learning from books. On trying this video course, it seems VERY tough & so time-consuming to learn. Elaborate explanations could have been provided.

Or at least if I could say, I already knew basic Python but learned Pandas for the first time. Advanced Pandas should be explained with more videos, more steps.

I needed to replay video parts countless times because of only higher level explanation in videos

創建者 Benjamin L


Almost every course everyone complain about assignments being hard..... but this one is EXCEPTIONALLY hard. Last question of assignment 4 is compulsory to pass the course and trust me it will bring to you trauma and pain like you have never imagined before.

Otherwise the lecturer is actually pretty good, and the other assignments are great for learning!!! I really think they overkilled it with assignment 4 though