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Learner Reviews & Feedback for Prepare Data for Exploration by Google

4.8
stars
22,032 ratings

About the Course

This is the third course in the Google Data Analytics Certificate. As you continue to build on your understanding of the topics from the first two courses, you’ll 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, learners will: - Find out how analysts decide what 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 within 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 best practices for organizing data and keeping it secure....

Top reviews

RA

Aug 10, 2022

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

AM

Nov 15, 2023

As a beginner, I really appreciated the ease and pace of the course. The videos were explanatory, the reads weren't over-whelming, and the hands-0n activities were very easy to follow and comprehend.

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By Sherry R

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Aug 7, 2023

There is a lot of great info and guidance here. Discussion of various types of data (some still a bit confusing to me), quantitative, qualitative, structured and unstructured, internal and external, etc. Discussion of data bias, data ethics, data protection, good vs bad data, open data etc. Discussion of importing data, spreadsheets and databases, sorting and filtering, creating datasets and tables, discussion of Boolean logic and SQL syntax, file naming conventions and staying organized. Creating a Kaggle account, a BigQuery account, a LinkedIn account; links to various helpful websites, dealing with Social Media; mentors/sponsors (for the future). All very very useful. Again, I very much like the format of these courses, where you have a few minutes of video, a few minutes of reading, some exercises and quizzes, so a lot of variety, you don't get bored. The "teachers" are enjoyable to listen to, and they have occasional "guest" appearances to throw in some personal perspectives. I end up sitting here at 10 PM thinking "OK, I'll watch just ONE MORE VIDEO..." and before you know it it's 6 AM...