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Отзывы учащихся о курсе Prepare Data for Exploration от партнера Google

Оценки: 9,311

О курсе

This is the third course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. As you continue to build on your understanding of the topics from the first two courses, you’ll also be introduced to new topics that will help you gain practical data analytics skills. You’ll learn how to use tools like spreadsheets and SQL to extract and make use of the right data for your objectives and how to organize and protect your data. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources. Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary. By the end of this course, you will: - Find out how analysts decide which data to collect for analysis. - Learn about structured and unstructured data, data types, and data formats. - Discover how to identify different types of bias in data to help ensure data credibility. - Explore how analysts use spreadsheets and SQL with databases and data sets. - Examine open data and the relationship between and importance of data ethics and data privacy. - Gain an understanding of how to access databases and extract, filter, and sort the data they contain. - Learn the best practices for organizing data and keeping it secure....

Лучшие рецензии


4 июля 2021 г.

Thank you for the course! It's a nice introduction to SQL and Google Big Query as well as the concepts of data privacy and security. The course also offers some great tips for professional networking.


10 авг. 2022 г.

The lessons were easy to follow through and the explanantions were easy to understand. The hands-on practices also helped improve hands-on skills with the data analysis tools introduced in this course

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626–650 из 1,478 отзывов о курсе Prepare Data for Exploration

автор: Flora H

14 нояб. 2021 г.


автор: Rajkumar d

11 окт. 2021 г.

T​hanks.This course given me a lot of knowledge.

автор: Phương T N

5 сент. 2021 г.

A helpful course for beginers in data analytics.

автор: CHANDER K

12 июня 2021 г.

awesome to learn here Thanks google and coursera

автор: Aditya S Y

17 июня 2022 г.

Very short, sweet, simple and effective course.

автор: Sandeep T

25 мая 2022 г.

I will learn a lot of new things in the course.

автор: Valente M

23 мар. 2022 г.

Fantastic Course...Is changing me on data path!

автор: Amajuoritse J E

19 нояб. 2021 г.

This course was very innovative and educational

автор: Randall U

3 авг. 2021 г.

T​hanks to the instructor. Enjoyed the course.

автор: Mircea N S

6 июля 2021 г.

Excellent materials and instructors. Thank you.

автор: chenxiaowu

4 июля 2022 г.

Nice course to explain the foundation of data.

автор: Catalina S

16 июня 2022 г.

Love the instructor Tom, it was a great course

автор: Edrei R S

24 мая 2022 г.

Great and fun course. Good introduction to SQL

автор: KM R

9 мая 2022 г.

obverse isn good in coursera course

thank you!

автор: Mohamed M R M

10 мар. 2022 г.

Amazing, excited to complete this certificate.

автор: sepideh D H

2 дек. 2021 г.

​It was useful the infrastructure information.

автор: Tsie M

1 дек. 2021 г.

g​ained insight into how to prepare my data :)

автор: Lisbeth D

19 авг. 2021 г.

Very good course, I learnt a lot! Recommended!

автор: Nuhu A

10 июня 2021 г.

The teaching is hands on which is great for me

автор: Deepak V

20 мая 2021 г.

I really loved the instructor's communication.

автор: Cassandra M

15 мая 2021 г.

Easy to understand, useful and skill-building.

автор: Terrique B H

25 мар. 2021 г.

Easy to follow and teaches useful information.

автор: Yash A

21 июля 2022 г.

Great course for the data dreamers out there!

автор: Jürgen F

6 апр. 2022 г.

high quality content and attention to detail!

автор: Erwin N

16 февр. 2022 г.

Nice course to get new job in data analytics.