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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: 13,735
Рецензии: 3,108

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

AU

Dec 10, 2017

Wow, this was amazing. Learned a lot (mostly thanks to stack overflow) but the course also opened my eyes to all the possibilities available out there and I feel like i'm only scratching the surface!

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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51–75 из 3,034 отзывов о курсе Introduction to Data Science in Python

автор: Sean C

Jul 29, 2019

This course is excellent if you're looking to learn how to use Pandas inside Jupyter Notebooks. Assignments are autograded and feedback can be received immediately. Course is a few years old and discussion forums contain answers to common questions

автор: Ofir R

Jul 25, 2019

Frankly, I did not watch the lessons at all, although they seem good.

The assignments were really great !

Challenging and very rewarding.

Really recommend the course !

автор: Krishna M S

May 12, 2019

Excellent course with assignments, But some elaborated videos on topics could help much better in solving the assignments in time.

автор: Sumit K B

Mar 05, 2019

Great course to bulild strong base on Pandas.

автор: John R

Aug 14, 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.

автор: Nattawat B

Apr 02, 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.

автор: Willber d S N

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.

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: Randy M

Aug 12, 2018

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

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: 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: 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: 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: Bart T C

Aug 19, 2018

This course provides very little instruction. I really like learning by trial and error, and I think that is how coding is typically learned. Learning python from stack_exchange, however, is how I was already learning it, and I was doing fine. The whole problem of learning from stack exchange is that you don't know if you are doing things in the best possible way, which can be important for big datasets. There was no discussion of the best practices for complete an assignment, after it was turned in, and, in general, may functions were required to pass the course that were never discussed in the course. The entire weeks lecture could also be watched in about 30 minutes, which seems low to me. Most courses I have taken have at least three hours a week of lecture. I have friends who have taken this same course, and had a similar assessment.

автор: Aaron B

Mar 20, 2019

Really appreciate this course. Got me started in Python, Pandas, and Jupyter. First week felt like magic. I am giving it a low score because the assignment questions were so ambiguous that it required constant resubmits an scouring the forums. The ratio of learning of course content to required Stack Overflow internet research was way off balance.

I learned a lot but was extremely frustrated and burned a lot of time it what I felt was all the wrong places.

Still grateful for this opportunity. I think the questions can be better explained and tightened up.

автор: Daniel A

Aug 20, 2018

This is not really a course. 2h of lectures in total. I have been in longer one-day university lectures. You have to attend other courses in order to be able to complete the assignments because 90% of what they ask is not in the lectures. This is a compilation of exercises, not a course.

On the other hand, the assignments and exercises are OK, that's why I gave it 2 stars.

автор: Carl M

Nov 14, 2019

Poorly worded questions (that are mentioned throughout the discussion board), older version of pandas and the course resources don't help you with course. Get ready to 'learn' by looking in StackOverflow or reading the volumes upon volumes of python/pandas documentation. In other words, expect to spend 15 hours a week per week (obviously it will vary)

автор: Marc B

Jan 11, 2019

The assignments are good practice, but the course teaches you nearly nothing. You have to do your own research to figure out how to do them.

There are some very useful Mentors on the forums to help the assignments, and if it were not for them, this course would be unbearably frustrating and useless.