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学生对 IBM 提供的 Databases and SQL for Data Science 的评价和反馈

4.7
11,619 个评分
1,280 条评论

课程概述

Much of the world's data resides in databases. SQL (or Structured Query Language) is a powerful language which is used for communicating with and extracting data from databases. A working knowledge of databases and SQL is a must if you want to become a data scientist. The purpose of this course is to introduce relational database concepts and help you learn and apply foundational knowledge of the SQL language. It is also intended to get you started with performing SQL access in a data science environment. The emphasis in this course is on hands-on and practical learning . As such, you will work with real databases, real data science tools, and real-world datasets. You will create a database instance in the cloud. Through a series of hands-on labs you will practice building and running SQL queries. You will also learn how to access databases from Jupyter notebooks using SQL and Python. No prior knowledge of databases, SQL, Python, or programming is required. Anyone can audit this course at no-charge. If you choose to take this course and earn the Coursera course certificate, you can also earn an IBM digital badge upon successful completion of the course. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

热门审阅

BS

May 21, 2020

Amazing course for beginners! The entire course is well structured and has good hands-on assignments. SQL is extremely essential for Database management and fun learning so please do try this one out!

SA

Apr 23, 2020

The lessons were short and easy to follow, providing all the basics as well as a few more advanced topics, to get student quickly up-to-speed on databases and SQL and their application in D/S realm.

筛选依据:

426 - Databases and SQL for Data Science 的 450 个评论(共 1,262 个)

创建者 Hemant K S

Jul 22, 2019

Good learning. Focus on concepts and great hands on training.

创建者 Rahul K

Jun 16, 2019

The Explanation of the queries is the Best part of the Course

创建者 Pablo V V

Mar 03, 2019

I would like more exercises to practise my skills.

Thank you.

创建者 Richardson P T

May 01, 2020

This is a powerful database course that everyone would take.

创建者 Mónica

Feb 16, 2020

Very complete and well oriented course. Thank you very much!

创建者 Toan T L

Oct 19, 2018

Great on basic of SQL and using Python to work with Database

创建者 Ramiro B

Mar 02, 2020

A "must have" knowledge for becoming a real Data Scientist.

创建者 Thanasegar S

Feb 19, 2020

Great beginners course. Need more examples for each topics.

创建者 hassan u s

Aug 18, 2019

What a course, and nice practices. Really enjoyed learning.

创建者 Maria S

Jun 17, 2019

It was very hard, but interesting course. Highly recommend!

创建者 Aditya M

May 08, 2019

Perfect for novice, and it all takes how much you practice.

创建者 Chae Y R

Mar 14, 2019

It was an excellent program for learning SQL for beginners!

创建者 Serena R T

Nov 08, 2019

Very informative and sufficient sample and practices given

创建者 Ayan C

Mar 04, 2019

Good course for understanding and starting to work on SQL.

创建者 Ronald B

Jan 31, 2019

Great video's, nice explanations and good final excersise.

创建者 Ben M

Jul 22, 2020

Great course to get familiar with SQL and Python combined

创建者 Hong W

Jun 03, 2020

Vey good course for understanding the basic query of SQL.

创建者 Volodymyr B

May 27, 2020

Thanks for this course. It was very useful and intresting

创建者 Alejandro A

Apr 23, 2020

Really interesting and difficult!! really learned a lot!!

创建者 ibrahim d

Jan 14, 2020

I had some issues with the Labs, otherwise a good course.

创建者 NAKKA P R

Jan 14, 2020

great course you can understsand the concepts very easily

创建者 Dan R

Jul 31, 2019

I found it challenging as I'm not that familiar with SQL.

创建者 Nikhil B

Sep 25, 2018

Great Content and Labs, learned a lot more than expected!

创建者 Christian O T

Jul 17, 2020

The best way to study online. I really love this course.

创建者 Joseph B

May 09, 2020

Great course and a fast intro to SQL based on real data.