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Learner Reviews & Feedback for Data Science Capstone by Johns Hopkins University

4.5
stars
1,112 ratings
288 reviews

About the Course

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....

Top reviews

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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226 - 250 of 278 Reviews for Data Science Capstone

By 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.

By 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.

By 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.

By 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.

By 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.

By Zaman F

Aug 24, 2017

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

Thanks to all three instructors

By Kalyan S M

Nov 6, 2016

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

By Marcus S

Sep 20, 2016

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

By Rudolf E

Jun 20, 2017

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

By Emi H

Jun 22, 2017

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

By HIN-WENG W

Aug 26, 2017

Challenging real life project that apply the academic knowledge

By Greig R

Mar 16, 2018

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

By Chonlatit P

Jun 26, 2019

Project is good for practice what you've learnt

By Murray S

Oct 9, 2016

Good test of what we learned in the courses.

By Ajay K P

Mar 29, 2018

I really had fun working on this project.

By Artem V

Sep 14, 2017

Nice balance of focused and open-ended

By Gary B

Sep 14, 2017

tough capstone and took a lot of time

By Yew C C

Jul 20, 2016

Good and interesting project.

By siqiao c

Sep 22, 2020

Very fun final project!

By Tiberiu D O

Sep 21, 2017

Interesting assignment!

By Sabawoon S

Nov 25, 2017

Excellent course.

By Filipe R

Oct 7, 2018

Great project.

By Kevin M

Jan 15, 2018

Very hard!

By 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.

By Diego C G

Apr 13, 2016

Could be better. The teacher sometimes explain the concepts in a hard way, and not always shows how to do in practice.

But you will get curious and in case of doubts, you can find more simple explanations on the web, and the forum is very good.

The assignments are hard, you will need do research to accomplish then, but is the best way to learn.

I think the specialization is good to someone without much knowledge on the field (like me). But it's only the start!