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존스홉킨스대학교의 Data Science Capstone 학습자 리뷰 및 피드백

1,189개의 평가
316개의 리뷰

강좌 소개

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....

최상위 리뷰

2018년 3월 4일

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.

2017년 3월 28일

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!!!

필터링 기준:

Data Science Capstone의 306개 리뷰 중 251~275

교육 기관: Alex s

2020년 4월 12일

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.

교육 기관: Robert W S

2017년 3월 19일

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

교육 기관: Humberto R

2018년 4월 9일

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

교육 기관: Jeremi S

2018년 12월 7일

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

교육 기관: xuanru s

2017년 6월 20일

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

교육 기관: Zaman F

2017년 8월 24일

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

Thanks to all three instructors

교육 기관: Kalyan S M

2016년 11월 6일

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

교육 기관: Marcus S

2016년 9월 20일

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

교육 기관: Rudolf E

2017년 6월 20일

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

교육 기관: Emi H

2017년 6월 22일

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

교육 기관: Oswaldo P

2021년 7월 5일

Good experience, little guidance for the topic but big challenge

교육 기관: HIN-WENG W

2017년 8월 26일

Challenging real life project that apply the academic knowledge

교육 기관: Greig R

2018년 3월 16일

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

교육 기관: Chonlatit P

2019년 6월 26일

Project is good for practice what you've learnt

교육 기관: Murray S

2016년 10월 9일

Good test of what we learned in the courses.

교육 기관: Ajay K P

2018년 3월 29일

I really had fun working on this project.

교육 기관: Artem V

2017년 9월 14일

Nice balance of focused and open-ended

교육 기관: Gary B

2017년 9월 14일

tough capstone and took a lot of time

교육 기관: Yew C C

2016년 7월 20일

Good and interesting project.

교육 기관: siqiao c

2020년 9월 22일

Very fun final project!

교육 기관: Tiberiu D O

2017년 9월 21일

Interesting assignment!

교육 기관: Sabawoon S

2017년 11월 25일

Excellent course.

교육 기관: Filipe R

2018년 10월 7일

Great project.

교육 기관: Kevin M

2018년 1월 15일

Very hard!

교육 기관: David M

2016년 7월 21일

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.