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Avis et commentaires pour d'étudiants pour SQL for Data Science Capstone Project par Université de Californie à Davis

3.8
étoiles
11 évaluations
4 avis

À propos du cours

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 - 4 sur 4 Avis pour SQL for Data Science Capstone Project

par Giulio A

May 27, 2020

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

par David M G

May 06, 2020

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

par 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

par 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.