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学生对 约翰霍普金斯大学 提供的 数据课程毕业项目 的评价和反馈

4.5
1,189 个评分
316 条评论

课程概述

The capstone project class will allow students to create a usable/public data product that can be used to show your skills to potential employers. Projects will be drawn from real-world problems and will be conducted with industry, government, and academic partners....

热门审阅

NT
Mar 4, 2018

Capstone did provide a true test of Data Analytics skills. Its like a being left alone in a jungle to survive for a month. Either you succumb to nature or come out alive with a smile and confidence.

SS
Mar 28, 2017

Wow i finally managed to finish the specialization!! definitely learned a lot and also found out difficulties in building predictors by trying to balancing speed, accuracy and memory constraints!!!

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251 - 数据课程毕业项目 的 275 个评论(共 306 个)

创建者 Alex s

Apr 12, 2020

The project is really interesting by itself, but there is a lack of preparation and instructions to build it, basically you are on your own.

创建者 Robert W S

Mar 19, 2017

Although this project is very open-ended with little guidance, it definitely requires the "full-stack" of data science to complete.

创建者 Humberto R

Apr 9, 2018

Very instructive, since it presents you with a real world problem, that you need to solve by yourself, in all of its complexity.

创建者 Jeremi S

Dec 7, 2018

Challenging. The course could possibly offer a 'here's how it could be done' ideal example after final submission and pass.

创建者 xuanru s

Jun 20, 2017

Very challenge work. new topic. The only issue is if there is any videos that could guide us would be better.

创建者 Zaman F

Aug 24, 2017

Most of the courses were very well tought and contained useful material.

Thanks to all three instructors

创建者 Kalyan S M

Nov 6, 2016

Really great course to apply all the techniques learned earlier in the specialization.

创建者 Marcus S

Sep 20, 2016

A good & fun idea to implement. Would have prefered implementing my own idea though.

创建者 Rudolf E

Jun 20, 2017

Great course, great content, didn't like the final capstone project though.

创建者 Emi H

Jun 22, 2017

Good project. Got me to think outside the box and really challenge myself.

创建者 Oswaldo P

Jul 5, 2021

Good experience, little guidance for the topic but big challenge

创建者 HIN-WENG W

Aug 26, 2017

Challenging real life project that apply the academic knowledge

创建者 Greig R

Mar 16, 2018

A tricky end to the specialisation - but quite a lot of fun.

创建者 Chonlatit P

Jun 26, 2019

Project is good for practice what you've learnt

创建者 Murray S

Oct 9, 2016

Good test of what we learned in the courses.

创建者 Ajay K P

Mar 29, 2018

I really had fun working on this project.

创建者 Artem V

Sep 14, 2017

Nice balance of focused and open-ended

创建者 Gary B

Sep 14, 2017

tough capstone and took a lot of time

创建者 Yew C C

Jul 20, 2016

Good and interesting project.

创建者 siqiao c

Sep 22, 2020

Very fun final project!

创建者 Tiberiu D O

Sep 21, 2017

Interesting assignment!

创建者 Sabawoon S

Nov 25, 2017

Excellent course.

创建者 Filipe R

Oct 7, 2018

Great project.

创建者 Kevin M

Jan 15, 2018

Very hard!

创建者 David M

Jul 21, 2016

This was essentially a self-study project with some social peers. The topic, approach, and standards were different from all of the other units in the Data Science specialization. I found the other units more enjoyable.

Learning the essentials of NLP quickly is necessary to begin the project. I ordered a textbook, for example, and I was fortunate that it arrived quickly. If NLP is a prerequisite for this capstone project - whether in the form of a prior class or textbook knowledge - this should be indicated clearly on the course description page.

Nevertheless, the main learning that I achieved with this course was in the area of software engineering - specifically, how to take advantage of vectorization in R to achieve reasonable computing performance. While this is a valuable skill, it doesn't seem the proper focus of a capstone course in a sequence focused primarily on other topics.

As noted elsewhere in these comments, there was a complete absence of any traditional teaching support. Learning outcomes suffered as result. The missing resources included instructors, mentors, partners, and learning materials.

The course site notes an expected time requirement of a few hours per week. My commitment was 20 hours per week, under some pressure. Numerous students take this "course" multiple time, in order to arrange for reasonable software development time.

Producing working software was fun, as it always is. The course learner community was supportive, which is fortunately typical for Coursera.

All in all, this project was *not* an effective capstone for the Data Science specialization. The project was interesting in its way, but it felt 'parachuted in' to this learning sequence.