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Learner Reviews & Feedback for Foundations of Data Science by Google

4.7
stars
3,788 ratings

About the Course

This is the first course in the Google Advanced Data Analytics Certificate, which will help develop the skills needed to apply for more advanced data professional roles, such as an entry-level data scientist or advanced-level data analyst. Data professionals analyze data to help businesses make better decisions. To do this, they use powerful techniques like data storytelling, statistics, and machine learning. In this course, you’ll begin your learning journey by exploring the role of data professionals in the workplace. You’ll also learn about the project workflow PACE (Plan, Analyze, Construct, Execute) and how it can help you organize data projects. Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you enhance your data analytics skills to prepare for your career. Learners who complete the eight courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate. By the end of this course, you will: -Describe the functions of data analytics and data science within an organization -Identify tools used by data professionals -Explore the value of data-based roles in organizations -Investigate career opportunities for a data professional -Explain a data project workflow -Develop effective communication skills...

Top reviews

NM

Feb 24, 2024

I have really got a fine refresher through this course. One of the basic idea of preparing PACE strategy document and understanding on RACI matrix was new for me. I recommend this course to every one.

LS

Oct 15, 2025

I believe a focus on the planning phase should come after getting familiar with the technical parts, as I feel like that is context you are missing to fully understand how to plan a data project.

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By KIDS L

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May 21, 2023

good.

By Snehil M

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Jan 18, 2026

Best

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Jan 5, 2026

Best

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Jan 1, 2026

nice

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Dec 22, 2025

cool

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Dec 6, 2025

done

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Nov 27, 2025

good

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Nov 27, 2025

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Nov 27, 2025

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Oct 29, 2025

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Jul 5, 2025

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May 14, 2025

good

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Apr 16, 2025

GOOD

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Feb 16, 2025

nice

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Feb 4, 2025

GOOD

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Jan 26, 2025

good

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Jan 23, 2025

Good

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Jan 7, 2025

good

By ANJANI M S

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Dec 31, 2024

Good

By warih w

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Dec 5, 2024

cool

By Nirav B

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Oct 29, 2024

Nice