Chevron Left
Voltar para Databases and SQL for Data Science with Python

Comentários e feedback de alunos de Databases and SQL for Data Science with Python da instituição IBM

4.7
estrelas
13,557 classificações
1,609 avaliações

Sobre o curso

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....

Melhores avaliações

BS
20 de Mai de 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
22 de Abr de 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.

Filtrar por:

1126 — 1150 de 1,606 Avaliações para o Databases and SQL for Data Science with Python

por Chathura S R

9 de Jul de 2020

good

por Nazim S

8 de Jul de 2020

best

por Jaladi N

27 de Jun de 2020

good

por Golla M

1 de Jun de 2020

good

por Vishnupriya.R

27 de Mai de 2020

NICE

por Shahnaz P

3 de Mai de 2020

good

por Naveen S P

26 de Abr de 2020

BEST

por Supparkom J

25 de Abr de 2020

nice

por Kindrat V R

22 de Mar de 2020

Nice

por TANGIRALA S P S

6 de Mar de 2020

Good

por Debakanta S

18 de Fev de 2020

good

por Deleted A

10 de Jan de 2020

good

por iyyanar

10 de Out de 2019

Good

por Prabhu M

2 de Set de 2019

good

por Nidhi G

15 de Mar de 2019

Good

por Mahesh A

5 de Jan de 2019

Nice

por ASHISH K J

11 de Nov de 2018

good

por Ahmad B

17 de Mar de 2020

Thx

por Josh H

9 de Jan de 2020

aaa

por André J A

22 de Jul de 2021

ok

por Kiran K

16 de Jun de 2020

NA

por Muhammad T A

11 de Set de 2019

<3

por Ali C B

17 de Nov de 2020

.

por koradedinesh@johndeere.com

23 de Jan de 2020

G

por Mao T T

22 de Mar de 2020

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.