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

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.

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

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

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

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

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

Thanks to all three instructors

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

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

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

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

Good experience, little guidance for the topic but big challenge

Challenging real life project that apply the academic knowledge

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

Project is good for practice what you've learnt

Good test of what we learned in the courses.

I really had fun working on this project.

Nice balance of focused and open-ended

tough capstone and took a lot of time

Good and interesting project.

Very fun final project!

Interesting assignment!

Excellent course.

Great project.

Very hard!

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.