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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
6,630 个评分
636 个审阅

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

TP

Oct 25, 2018

Practice lab assignments were excellent in reinforcing my learning, they were just the right kind of challenging. This course has been the best one in the Data Science Professional series by far.

JM

Feb 28, 2019

Clear, thorough, well-designed. Labs give useful practice, assignments and quizzes test the actual instructional content. This course is by far the best in the IBM Data Science specialization.

筛选依据:

551 - Databases and SQL for Data Science 的 575 个评论(共 625 个)

创建者 Ravindra D

Nov 18, 2019

Covered all basic concepts about Databases and SQL

创建者 Pulkit P

Nov 18, 2019

In this course basic was easily explained and it was great course. but wanted to learn more about sql lacked in this course

创建者 Roger S

Dec 29, 2018

Getting the right syntax for Python and SQL together was really tricky/difficult. I wish there were a reference book/website for additional study.

创建者 Stephen S

Jan 01, 2019

I wanted to like this course more, but wow was it dry. There were a lot of small nuisances with having so many logins to access course material that made things frustrating at times. Although, the point is to get you accustomed to an IBM centric workflow, that when you start to learn it, its not bad. I did enjoy the final project, and found it to be the redeeming quality of this course.

创建者 Samir S

Feb 15, 2019

More SQL needed.

创建者 Aakash A

Feb 15, 2019

Learnt a lot about connecting database from python and how jupyter notebooks are useful.

Please mention IBM DB2 only, if it covers only IBM DB2.

Thanks

创建者 Sisir K

Feb 07, 2019

The speaker in the videos goes too fast. The hands-on labs are very useful and were my primary sources of learning. The videos didn’t help much with the learning process.

创建者 Vaibhav V

Feb 22, 2019

The course teaching methodology is not user-friendly especially for someone new to sql.

创建者 Vincent Z

Feb 10, 2019

This is a shallow introduction to SQL. Python API is shown, but not used in the assignments. The videos are OK at best, and many times, the examples are not the best, in that they don't really show why one would use, say, a left join instead of full join operation in real life. The earlier weeks need more exercices. However, the final week is quite good. At least the exercices and final quiz makes you think a little.

创建者 Christopher B

Feb 12, 2019

This is a logical extension of the certification, but the interfaces are clunky

创建者 Ozge I

Feb 01, 2019

Some quizzes include questions about materials not yet introduced. The material could be much more interesting with more interesting and interactive examples. Hands-on Labs should include new materials rather than letting the students rewrite given queries in sql.

创建者 Andrew C

Apr 08, 2019

Overall the course is satisfactory although some areas still need work.

创建者 Aniruddh G

Apr 11, 2019

The environment is difficult to set up. For someone who knows SQL and has worked on other platforms the IBM Cloud and workspace are difficult to set up.

创建者 Parth R J

Feb 05, 2019

the course is good but the way they teach you is not as good as other IBM courses it was bit confusing for me where to write the code etc the instructions were not as clear as they should be

创建者 Emily

Oct 09, 2018

Easy to follow. But not explained why should it be in detail.

创建者 Kendall G

Oct 31, 2018

This course is not a complete overview of SQL by any means. You will only learn the most basic functions. The value here however is that the course guides you on how to write SQL queries in Python. To round out your SQL skills, you will need to take a more in depth beginner course.

创建者 Marcus V C D

Aug 06, 2018

The last exercise of the last week is not clear how to do it and the server does not run it. There is no assistance from the forum.

创建者 Rohit T G

May 11, 2019

Awesome course. Please also provide job.

创建者 Matthew A

May 12, 2019

This course was OK, but I'd still like to see more hands-on exercises and a final assignment that's more aligned to the prior coursework

创建者 Yike

Jun 26, 2019

Assignment marked by other classmates is not a correct method. classmates often do not read answer carefully and give a correct grade.

创建者 vicky t

Jul 24, 2019

very short course sql should be needed to be taught in detail but it was just basics of the basics

创建者 Abdullah A S S

Aug 03, 2019

dude make the course a bit more human

创建者 Youlin C

Aug 03, 2019

I can't open Db2 console on the IBM cloud, it only showed 502 Bad Gateway. It cost me more time on finding another way to finish the homework.

创建者 Charles O

Jun 05, 2019

The labs did not all connect to the IBM cloud correctly, otherwise the course was fine.

创建者 Niklas M

Jun 06, 2019

Good course, however, it uses a lot of IBM specific tools.