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Отзывы учащихся о курсе Introduction to Data Science in Python от партнера Мичиганский университет

4.5
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Оценки: 21,868
Рецензии: 4,906

О курсе

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....

Лучшие рецензии

PK

May 10, 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

SI

Mar 16, 2018

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 .

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101–125 из 4,833 отзывов о курсе Introduction to Data Science in Python

автор: WASEEM A

May 05, 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.

автор: vinod k

Apr 06, 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

автор: Ashish K P

Sep 17, 2020

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

автор: Randy M

Aug 12, 2018

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

автор: Lance E S

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.

автор: Gina G

Apr 07, 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.

автор: Aarya P

Sep 16, 2020

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.

автор: Sercan B

Jul 15, 2020

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.

автор: Robert S

Sep 13, 2020

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.

автор: Aman j

May 07, 2019

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

автор: Benjamin L

Jan 03, 2019

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

автор: Pascal B

Jul 27, 2019

Generally, very good selection of content. The explanations are insufficient for passing the assignments tho, which means that most of the course work is self-study from the web. The buggy auto-grader sometime made the submission of the assignments quite a pain as one has to find a way to change the code in a way that still produces the right answer but doesn't blow up the auto-grader.

автор: Minyi Y

Nov 20, 2016

The content and assignments are certainly useful and relevant. However, the lectures are too short and do not help much with doing the assignment. As a beginner, I relied heavily on google and the discussion forum to get through the assignment. And I am not sure if i can actually tackle similar problems again without referring back to the pre-mentioned resources.

автор: Julien

Sep 20, 2018

Interesting course covering the main introduction topics to Data Science, however there is a too large gap between the theoretical (videos, Jupiter notebook examples, ...) lessons provided and the knowledge required to perform the assignment. The time to do individual research to perform the assignment is tremendous. This is not an easy course at all.

автор: Jennifer W

Sep 17, 2020

I didn't feel that the lecture material corresponded to the exercises. I spent all my time just looking at Stack Overflow. The exercises are also not clearly written, such that you spend time trying to adhere to solving for the solution as opposed to learning Python fundamentals.

автор: Sabbir A

Aug 08, 2020

I learned things, yes. But I was here to try and learn what is already there in the books; I thought it would make me understand easily and in interesting ways. I was disappointed. There is no point in taking the course if it sends me back to the books. :(

автор: Claude P

Nov 20, 2016

More concise coding tutorials and less "search on your own on the internet" needed. It is great to get to know the online community and the course needs more coding example directly relat to exams.

автор: Tom M

Dec 29, 2018

A lot of self directed learning, bordering on excessive. Sometimes it takes some investigation to figure out why the autograder did not pass you. Overall, I felt I learned a lot, much on my own.

автор: Pamela T

Feb 02, 2019

This is a great overview for python, but the materials/videos/slides are very elementary compared to the sophistication of the homework. Required many more hours than the estimates.

автор: Saadman S

Sep 16, 2020

Statistical stuffs are really tough, it's hard to understand without any background also the assignment materials should be discussed more, they should be included in the course.

автор: Colleen K

Sep 22, 2018

I learned a lot by doing assignments, but the course materials are not helpful. Stackflow and Python documents guide me much more than the course itself.

автор: Khairul A

Aug 10, 2020

Too fast explanation

автор: Erico L

Mar 02, 2019

I don't think I've learned much along the course. I had to pick a few concepts here and there, but I don't think that the way in which those are explained would stick.

Also, the course seems rushed: I'm not sure what the end game of these courses is, but I think it's an incredible wasted opportunity when it comes to MOOCs, as there could be more lengthy videos and more and better ungraded exercises (something that in this particular course do not exist) and much, much better explained assignments (I guess adding there the info from the forums by the teaching stuff would not hurt).

For being a course of intermediate level, the videos and explanations are too short; there are even places where things are left totally unexplained.

Even if it's supposed (and even encouraged) that the students seek information on their own, the lack of context in some places makes it rather difficult. this is specialy more so with the questions that are interwined in the videos, as normally in order to answer them corretly you have to go out and find the related info (something that totally disrupts watching the videos).

finally, the assignments are a wreckage; some of the questions are incredible difficult to understand, if not out right impossible. The fact that there's a lot of information added to the forums by the etaching stuff, up to the point that the more complicated questions are easily answered with that same infromation, proves this.

I do think there are examples of courses in Coursera: I recently completed "Mathematics for Machine Learning: Linear Algebra" and even thought I don't think it's not without its issues, I find it a much more challenging, entertaining and fun course, that covers in a good way its subject.

I have to commend the people from the teaching stuff that are in the forums, thought, as it's the only course in which I found people from the teaching area activelly participating, and helping the students.

автор: Zayd A

May 28, 2019

I had done "Python for Everybody" from Charles Severance which I had found excellent, with the instructor being passionate and the pace being just about right. I had assumed it would be similar for "Introduction to Data Science in Python", but that wasn't case. The delivery of the course is at a very very fast pace, you don't even have time to stop and absorb the functions and methods that you are supposed to learn. The instructor and the research assistant will list the functions and methods one after the other without pausing. The assignment is then extremely hard with no resemblance to the material in the course (I couldn't do it even after having reviewed the videos). After holding on for the first 2 weeks (it's a very useful topic after all), I gave up and decided to learn from the "learning the Pandas library book", which is a very good summary of the main Pandas functions and methods (and which was recommended by Dr Christopher Brooks), and I was able to follow it very easily.

автор: Sibo C

Sep 01, 2019

Overall: I felt this course was useful but pretty time-consuming. The course had relatively limited taught material and relied a lot on searching & self-studying. If you have a fair amount of time it is a good choice.

Pros: You learn through doing assignments which are well supported by mentors/community. Also, you get used to studying through googling problems and learning from websites such as Stackoverflow.

Cons: Whilst this learning method definitely had its merits, it could be quite time-consuming for someone seeking to gain introductory-level skills quickly. You could find yourself in situations where you spend hours searching for something quite elementary and could easily have been taught to you, which could be frustrating. I personally think this course could be improved by adding a bit more small quizzes for beginners to play around with the basics, before requiring them to self-learn through searches.