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返回到 毕业项目:使用 Python 获取并处理数据,并用可视化方式展现数据

學生對 密歇根大学 提供的 毕业项目:使用 Python 获取并处理数据,并用可视化方式展现数据 的評價和反饋

4.6
4,604 個評分
636 個審閱

課程概述

In the capstone, students will build a series of applications to retrieve, process and visualize data using Python. The projects will involve all the elements of the specialization. In the first part of the capstone, students will do some visualizations to become familiar with the technologies in use and then will pursue their own project to visualize some other data that they have or can find. Chapters 15 and 16 from the book “Python for Everybody” will serve as the backbone for the capstone. This course covers Python 3....
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(132 個審閱)
Relevant project
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NS

Apr 10, 2016

Python for everyone is One of the Best Course on MOOC platform .\n\nDr. Chuck made it interesting and Knowledgeable. Way back 3 Months ,I can't even thing of the stuff that I leaned and implemented .

JC

May 26, 2017

I found this course a little bit easier that some of the previous courses, however, it allowed me to gain experience managing a larger projects that encompass several languages and multiple programs.

篩選依據:

1 - 毕业项目:使用 Python 获取并处理数据,并用可视化方式展现数据 的 25 個評論(共 614 個)

創建者 Morgan S

Apr 06, 2016

If this entire specialization were a bag of potato chips, the Capstone would be that bland chip that didn't get any salt.

The introduction to the Capstone promises that we'll "build applications" utilizing what we've learned so far with optional assignments for delving deeper. However, none of the required assignments involve even the most primitive of problem solving skills or code writing abilities. If you can download a file and take a screenshot then you've got what it takes to pass this class.

The optional assignments are far too focused around a new piece of video sharing technology that the instructor and associates have developed. Unfortunately, the technology adds almost nothing beneficial to the class and is probably to blame for the sheer lack of quality in the rest of the class.

In fact, the entire Capstone feels like it was so haphazardly put together that it can only be described as the most contrived beta-test I've ever been a part of. Such a disappointing ending to what was otherwise an enjoyable specialization.

創建者 Ayush B

Feb 14, 2019

peer grading for mentors very slow.

創建者 ali s

Aug 04, 2018

This should not be called a capstone. It is way too complicated to understand which is why the assignments have been kept to simplistic (this is reasonable). A bunch of small programs testing smooth amalgamation and application of the learnt concepts would have been more fruitful.

創建者 Hanyani A M

Nov 15, 2018

Didn't learn as much as the previous chapters. Markers are slow to mark, my subscription actually expired before they marked, not

創建者 Alex S

Jul 20, 2018

No code writing required to complete the course.

創建者 Jeffrey B

May 29, 2016

I thought this was poor. It was basically a re-hash of the previous module with slightly different tasks. Given that I had to wait three months for the capstone to be ready, I found it a bit rich that my deadline to finish it was a couple of weeks! Don't waste your money/time on this particular module.

創建者 PRANSHU P

Mar 19, 2019

I have completed the whole specialization successfully and Coursera and FFE and ofcourse, my guide, Dr. Chuck have been a constant source of motivation. I am really really thankful for this whole support of yours.

創建者 Amit K

Oct 24, 2018

This course helped me a lot in understanding the web and the data retrieval from it.

創建者 Zhisheng Y

May 06, 2019

For some reason, I lost my motivation so I don't think I'm going complete the capstone. But it is a good course, and the instructor is good too. It might take you some time if you try to comprehend every line of codes. I don't think I would recommend you to enroll this one if you just want to skate through and get the certificate like me. If you are passionate about data science, please enroll. Cheers.

Update: I think I may want to finish the capstone. Good luck to everyone.

Update: I completed.

創建者 Allen B V

May 31, 2019

one of the best python courses

創建者 Abrar W

Jun 03, 2019

Beautiful Course. Worth your time . Dr. Chuck is amazing

創建者 Diego N F

Jun 22, 2019

It's an excellent course!! Im glad to do it. Thaks to everyone who made it possible.

創建者 Christopher H

Mar 15, 2019

Great to see how Python can be used for data visualization; however, in my opinion, most of the code is way above the heads of students at this level.

創建者 Grace

Feb 07, 2019

Bad experience with grades not get in on time. Have to had back and forth btw the instructor and support.

創建者 Milap S

Dec 13, 2018

Not much to learn from project perspective. This course definitely needs improvement.

創建者 Spencer H

Jul 10, 2018

Honestly not a very good course. The first 3 courses in this specialization were great. We were really challenged to write our own logic and learned a lot of python. The last two courses, however, were disappointing. We essentially just ran pre-written code to "see how a complex app works." It would have been much more useful to have us write our own code.

創建者 Ponrajadurai S

Feb 11, 2019

My expectation was I will do the coding (get my hands dirty) based on the suggestion or ideas from the instructor. I didn't expect to run the code that was written by the instructor and share the screenshots. It would had been good, if the course involved in working on a project.

Week 3, week 5 and week 7 of this course should be made compulsory - my opinion

創建者 daniel m

Aug 22, 2018

I enjoyed the specialization a lot, overall! Absolutely fantastic teaching by Dr. Chuck, I learned so much. Unfortunately, the capstone didn't have the right structure for me. The required assignments didn't really teach anything new, it was just run this code and take screenshots. The " can anyone review my assignment" forum spam was just sad, and I think a better solution must be found for the course conclusion. The optional data visualization assignment is great, but I don't feel I had the tools necessary to complete it yet. I do plan to come back to it after I learn a bit more.

創建者 Anthony S

Aug 03, 2018

This Capstone was okay....I went through it, I think it wasn't as thorough as the other classes.

創建者 Dmitry E

May 09, 2019

It's not such interesting as previous courses. Mostly it contains some practical solutions which you have to execute (with some small changes).

Peer review assignment are very frustrating. Teacher assistant grades are very strange (i.e. bad screenshot, bad browser, etc. and you can't update them to improve your score).

I have to wait a week to have my assignments reviewed (not 1-2 days) - be sure to submit them more then week before month end or you will be charged for the next month due to subscription!

創建者 Marc A G

Oct 09, 2018

Should focus on data types and usage while allowing students do actual homework.

創建者 Stuart O Y M

Feb 18, 2019

Instructions for assignments not clear. TA not helpful with providing clarity on completing the assignments.

創建者 Brendan C

May 02, 2019

Very poor quality course, both from a content perspective as well as from an implementation perspective.

This final class in the specialization is not a programming course. You are instructed to run someone else's code and screenshot the various stages of running these scripts. You don't modify their code and it really takes a step back from the previous courses in this specialization as the instructions and the course staff's direction are significantly misaligned.

I was evaluating this course for use in my organization, but cannot suggest taking the capstone as it provides no value and is simply a waste of time.

My suggestion to improve the course would be to align the staff direction with the instruction given in the course. Additionally if you read through the forums you can see them get frustrated like they are volunteer staff working for free in a hostile environment.

創建者 PRUDHVI K

Jan 28, 2019

awesome course

創建者 Rafael E F O

Jan 17, 2019

It was awesome to do the projects of this capstone and to learn about data modeling, pagerank algorithm, web scrapping, email data parsing and data visualization.