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Вернуться к Databases and SQL for Data Science with Python

Отзывы учащихся о курсе Databases and SQL for Data Science with Python от партнера IBM

4.7
звезд
Оценки: 13,554
Рецензии: 1,609

О курсе

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....

Лучшие рецензии

BS
20 мая 2020 г.

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!

PK
19 авг. 2020 г.

A very useful course with some very interesting datasets/Jupyter notebooks to work through/practice your skills. Offers a good balanced blend between theory and practical/practice. Very good course!

Фильтр по:

1126–1150 из 1,606 отзывов о курсе Databases and SQL for Data Science with Python

автор: Chathura S R

9 июля 2020 г.

good

автор: Nazim S

8 июля 2020 г.

best

автор: Jaladi N

27 июня 2020 г.

good

автор: Golla M

1 июня 2020 г.

good

автор: Vishnupriya.R

27 мая 2020 г.

NICE

автор: Shahnaz P

3 мая 2020 г.

good

автор: Naveen S P

26 апр. 2020 г.

BEST

автор: Supparkom J

25 апр. 2020 г.

nice

автор: Kindrat V R

22 мар. 2020 г.

Nice

автор: TANGIRALA S P S

6 мар. 2020 г.

Good

автор: Debakanta S

18 февр. 2020 г.

good

автор: Deleted A

10 янв. 2020 г.

good

автор: iyyanar

10 окт. 2019 г.

Good

автор: Prabhu M

2 сент. 2019 г.

good

автор: Nidhi G

15 мар. 2019 г.

Good

автор: Mahesh A

5 янв. 2019 г.

Nice

автор: ASHISH K J

11 нояб. 2018 г.

good

автор: Ahmad B

17 мар. 2020 г.

Thx

автор: Josh H

9 янв. 2020 г.

aaa

автор: André J A

22 июля 2021 г.

ok

автор: Kiran K

16 июня 2020 г.

NA

автор: Muhammad T A

11 сент. 2019 г.

<3

автор: Ali C B

17 нояб. 2020 г.

.

автор: koradedinesh@johndeere.com

23 янв. 2020 г.

G

автор: Mao T T

22 мар. 2020 г.

Of the courses in this professional data science certificate I have taken, this is probably the best designed one. The labs force you to think and apply what you learnt in the video and not simply make minor modification to example codes. By the end of the course, I have internalized some of the commands. Overall, the labs were rather effective at drilling the concepts into students.

Some of the labs in the second week were rather lazily written. Instead of asking students to practice what they saw in the videos, all labs should contain actual questions that ask students to apply what they have learnt to new examples and problems, forcing them to think about what they have learnt.

The grading system is also in need of improvement. Some graders do not seem to know what they are doing. Simply resubmitting the assignment can result in a drastically improved score simply because the first grader was marking down answers that were actually correct. Perhaps there could be multiple graders assigned to any single assignment and the average score taken, or something to that effect.