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Learner Reviews & Feedback for SQL for Data Science Capstone Project by University of California, Davis

41 ratings
8 reviews

About the Course

Data science is a dynamic and growing career field that demands knowledge and skills-based in SQL to be successful. This course is designed to provide you with a solid foundation in applying SQL skills to analyze data and solve real business problems. Whether you have successfully completed the other courses in the Learn SQL Basics for Data Science Specialization or are taking just this course, this project is your chance to apply the knowledge and skills you have acquired to practice important SQL querying and solve problems with data. You will participate in your own personal or professional journey to create a portfolio-worthy piece from start to finish. You will choose a dataset and develop a project proposal. You will explore your data and perform some initial statistics you have learned through this specialization. You will uncover analytics for qualitative data and consider new metrics that make sense from the patterns that surface in your analysis. You will put all of your work together in the form of a presentation where you will tell the story of your findings. Along the way, you will receive feedback through the peer-review process. This community of fellow learners will provide additional input to help you refine your approach to data analysis with SQL and present your findings to clients and management....
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1 - 8 of 8 Reviews for SQL for Data Science Capstone Project

By Mei H

May 11, 2020

I really don't understand why this course is added to this specialization. It is not really linked to the previous courses, and the way to get the grades are all based on peer-reviewed assignment. There is no peers to review my work after submitting the first assignment and there are four such assignment to go.

By Noah M

May 10, 2020

It was Ok. It's largely down to you to get the project done to the highest standard you can muster... if you're stuck just use stackoverflow. But through that I learned a hell of a lot, just stick to your ambition with answering your question and plug away at trying to get the answer even if it means googling lots to work lots of stuff out yourself. If you do, you may have a project worthy of being shared with your network or even blogged about.

Some feedback: given this was part of a SQL specialization, it would've been interesting to ensure candidates created a database that they would query themselves, rather than just draw the ER diagram. But to be fair on Course 4, that wasn't taught in the courses before, just seems to me to be an opportunity missed?

Another feedback: it may have been more helpful for the examples to be based in Spark / Pyspark for them to have the feel they build on Course 3 of this Specialization. Again, a missed opportunity if people just reverted to Pandas and not use the Capstone to apply Course 3 teachings.

But as always and perhaps rightly it's up to the learner to construct their project in a way that's meaningful to their learning goals.

Thanks for the course

By Usman N

Jun 23, 2020

the course is just an assignment, without much guidance and student is supposed to capitalize on whatever they have learned in previous courses. the requirement to use Python is frustrating, it would have been better if the course would have remained focus on SQL. limited people are enrolled in course, it takes weeks for peer review.

By Giulio A

May 27, 2020

thank you for this course. It has been very interesting to do it :)

By David M G

May 6, 2020

Some support is missing, and they should also enable sending pdfs on all deliveries (every week)

By Mohit g

Nov 12, 2020

It was good well structured course.

By Bao C

Sep 14, 2020

I think the aim for the course encourage exploration using the learned skill. Which is fine, actually a great idea. But the execution is sloppy. I think the course need to be balanced between exploration and steering as well. It should be designed so that some insights was hidden in the data and with no particular instruction, the students should find out these insights. So they have meaningful goal that they reached as well as a handful of exploration experience from the lack of instruction.

Instead? We have 3 sets of data, which are too narrow even compare to the example given in the lecture. Also the lecture and the assignments are barely comparable, which is more confusing. The peer review is cute and all but not too useful in this kind of capstone project where learners are generally inexperience.

Overall, not too much value was added from the course unless you want to experience the frustration of working with data, which you can get elsewhere. Not recommended

By Dev G

Sep 1, 2020

Not enough guidance on how to do the assignments- lots of use of python when there is no background of it in previous courses. The videos skimmed through it as well.