Name: Foundations of Data Science
Brand: Google
Availability: OnlineOnly
Rating: 4.7 (734 reviews)

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Learner Reviews & Feedback for Foundations of Data Science by Google

4.7

stars

3,908 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

Nov 7, 2023

I love the course very much, it provides everything needed to get started with a data science project and proper communication with both the data teams and stakeholders.

Oct 16, 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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