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Kursteilnehmer-Bewertung und -Feedback für Data Science Capstone von Johns Hopkins University

4.5
886 Bewertungen
235 Bewertungen

Über den Kurs

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-Bewertungen

NT

Mar 05, 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 29, 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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151 - 175 von 226 Bewertungen für Data Science Capstone

von Terry L J

Nov 28, 2018

I appreciate all the work they put into creating the course,. However, it can be frustrating to follow. It would be nice if they would structure it in a more organized fashion.

von Jeremi S

Dec 07, 2018

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

von Filipe R

Oct 07, 2018

Great project.

von Sivaraman M

Oct 23, 2018

The content of this course is very good and the assignments test the knowledge gained

The video lectures are some times boring, losing focus.

I think video lectures need some improvement

von Pieter v d V

Oct 24, 2018

It is a lot of independent work, with guiding questions but no real help otherwise. If that's not your thing, this course is not for. If it is, you'll great a very fun end project.

von Rudolf E

Jun 20, 2017

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

von Carlos D C G

Mar 27, 2017

Very interesting, but Capstone is much more difficult than the rest of the course.

Be sure to study carefully the first courses, and don't rush.

von Telvis C

Jul 16, 2016

I enjoyed the course. This course took me waaaay more time than I thought because I struggled with a few issues. First, I wish I'd started by taking the NLP online course before starting the Capstone (https://www.youtube.com/watch?v=-aMYz1tMfPg). There was an issue installing RWeka, RJava and it took me several days to work through the issues. I eventually moved to using quanteda (https://cran.r-project.org/web/packages/quanteda/vignettes/quickstart.html). I also waited far too long to develop a method to test my model using a subset of the training data, so I could test whether changes to my model improved and reduced performance. It turns out that my model trained on a 25% sample performed just as well as a model trained on 100%. I'm thankful for the Discussion Forum and final peer review process. Both helped me learn how I can improve my model and demo application. I really appreciate the instructors for creating this specialization. I've learned a lot.

von Romain F

Jul 03, 2017

A very tough and challenging project, but a great way to learn a lot about Natural Language Processing and algorithm coding in R, and in the end to have a cool Shiny app to add to your portfolio. The project weekly structure could be enhanced (maybe adding one more week could help) and the weekly instructions, while informative, could also be improved. Thankfully the forum has been very helpful. Informative and motivating videos but where were the SwiftKey people mentioned ? Finally, the quizzes 2 and 3 should be replaced by other exercises with more educational value. Overall an interesting learning opportunity !

von Jay B

Oct 04, 2016

This is not for beginners with no experience. The estimated weekly hours are absurdly low.

No one has seen any sign whatsoever of the industry partner, SwiftKey, despite claims they will be around to help. The field has advanced dramatically since the course was developed. Be prepared to do a lot of research and trial and error.

The specialization has been an excellent way to learn a fair amount on the topic, but it is just the beginning. The capstone will challenge you. It is rewarding when you complete it.

von Victoria A

Mar 29, 2017

With this course I learned to go through a data problem from the scratch and get a real data product, and document it. My only constructive comment is that, when reviewing the projects of classmates, there is a huge dispersion on the effort and quality of the products presented, from very basic and simple Apps to a very professional products, and the scoring of them all is quite the same, perhaps one or two points of difference, in eleven points maximum score.

von Murray S

Oct 09, 2016

Good test of what we learned in the courses.

von Zaman F

Aug 24, 2017

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

Thanks to all three instructors

von Kalyan S M

Nov 06, 2016

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

von Humberto R

Apr 09, 2018

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

von Ajay K P

Mar 30, 2018

I really had fun working on this project.

von Kevin M

Jan 15, 2018

Very hard!

von Tiberiu D O

Sep 22, 2017

Interesting assignment!

von Sabawoon S

Nov 25, 2017

Excellent course.

von 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.

von HIN-WENG W

Aug 27, 2017

Challenging real life project that apply the academic knowledge

von Artem V

Sep 14, 2017

Nice balance of focused and open-ended

von Angela J

Apr 17, 2018

Overall, I was semi-satisfied with the capstone project:

On the negative side, my foremost issue is that the project has very little to do with what we learned in the nine courses before. I get that you will always see new data formats as a data scientist, but having the whole course cover numeric data and then having the final project be on text data where you can't apply what you learned seems sub-optimal. Also, to me it seemed that the accuracy increased mostly with how much data you train your algorithms on, and not so much how you design your algorithm. My second issue is that the class only starts every two months, and the assignments are blocked before the session starts so you can't see them if you're trying to get a head start. What happened to everyone learning at their own pace? I have a lot to do and had to switch sessions at least once for most classes, and this class was really stressful for me because I didn't want to move my completion back by two months. Lastly, I really hate RPresenter and that the instructors force us to use it, but maybe that's just me.

On the positive side, I did learn a lot: The basics of text prediction, how to do parallel programming in R and how to set up an RStudio instance on AWS (the latter two are not very hard, I recommend them to anyone struggling with gigantic runtimes, as long as you're willing to invest like $40 or so for the computing power). I liked that the guidelines were very broad, so there was a lot of room for creativity. I also finally found out how to make an pretty(-ish) presentation in R, though I would always choose Powerpoint in real life.

I really enjoyed the series as a whole and learned a great deal.

von Robert C

Aug 03, 2018

I wish that either there were a choice of capstone projects, or that there were a more numerical component to the analysis than such a pure text based assignment.

von Josh M

Oct 12, 2016

Good scenario and a good learning opportunity. I don't think the quizzes related well to the problem we were trying to solve and introduced a red herring, however. Predicting the next best word is not the same as predicting the relative probability of 4 words where one is the "right answer" but not necessarily the best prediction of a text prediction algorithm.