What is data science and advanced data analytics?

<text variant="body1">Organizations of all types and sizes have business processes that generate massive volumes of data. Every moment, all sorts of information gets created by computers, the internet, phones, texts, streaming video, photographs, sensors, and much more. In the global digital landscape, data is increasingly imprecise, chaotic, and unstructured. As the speed and variety of data increases exponentially, organizations are struggling to keep pace. <text variant="body1">Data science and advanced data analytics are part of a field of study that uses raw data to create new ways of modeling and understanding the unknown. To gain insights, businesses rely on data professionals to acquire, organize, and interpret data, which helps inform internal projects and processes. Data scientists and advanced data analysts rely on a combination of critical skills, including statistics, scientific methods, data analysis, and artificial intelligence.

What do data professionals do?

<text variant="body1">A data professional is a term used to describe any individual who works with data and/or has data skills. At a minimum, a data professional is capable of exploring, cleaning, selecting, analyzing, and visualizing data. They may also be comfortable with writing code and have some familiarity with the techniques used by statisticians and machine learning engineers, including building models, developing algorithmic thinking, and building machine learning models. <text variant="body1">Data professionals are responsible for collecting, analyzing, and interpreting large amounts of data within a variety of different organizations. The role of a data professional is defined differently across companies. Generally speaking, data professionals possess technical and strategic capabilities that require more advanced analytical skills such as data manipulation, experimental design, predictive modeling, and machine learning. They perform a variety of tasks related to gathering, structuring, interpreting, monitoring, and reporting data in accessible formats, enabling stakeholders to understand and use data effectively. Ultimately, the work of data professionals helps organizations make informed, ethical decisions.

Why start a career in data science or advanced data analytics?

Large volumes of data — and the technology needed to manage and analyze it — are becoming increasingly accessible. Because of this, there has been a surge in career opportunities for people who can tell stories using data, such as senior data analysts and data scientists. These professionals collect, analyze, and interpret large amounts of data within a variety of different organizations. Their responsibilities require advanced analytical skills such as data manipulation, experimental design, predictive modeling, and machine learning.

Which jobs will this certificate help me prepare for?

The Google Advanced Data Analytics Certificate on Coursera is designed to prepare learners for roles as entry-level data scientists and advanced-level data analysts.

What tools and platforms are taught in the curriculum?

During this certificate program, you’ll gain knowledge of tools and platforms like Jupyter Notebook, Kaggle, Python, Stack Overflow, and Tableau.

Why enroll in the Google Advanced Data Analytics Certificate?

You’ll learn job-ready skills through interactive content — like activities, quizzes, and discussion prompts — in under six months, with less than 10 hours of flexible study a week. Along the way, you’ll work through a curriculum designed by Google employees who work in the field, with input from top employers and industry leaders. You’ll even have the opportunity to complete end-of-course projects and a final capstone project that you can share with potential employers to showcase your data analysis skills. After you’ve graduated from the program, you’ll have access to career resources and be connected directly with employers hiring for open entry-level roles in data science and advanced roles in data analytics.

Do I need to take the course in a certain order?

We highly recommend completing the seven courses in the order presented because the content in each course builds on information covered in earlier lessons.

When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I subscribe to this Certificate?

When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Foundations of Data Science

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Foundations of Data Science

This course is part of Google Advanced Data Analytics Professional Certificate

Instructor: Google Career Certificates

327,664 already enrolled

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5 modules

Gain insight into a topic and learn the fundamentals.

3,926 reviews

Advanced level

Designed for those already in the industry

Flexible schedule

2 weeks at 10 hours a week

Learn at your own pace

98%

Most learners liked this course

5 modules

Gain insight into a topic and learn the fundamentals.

3,926 reviews

Advanced level

Designed for those already in the industry

Flexible schedule

2 weeks at 10 hours a week

Learn at your own pace

98%

Most learners liked this course

What you'll learn

Understand common careers and industries that use advanced data analytics
Investigate the impact data analysis can have on decision-making
Explain how data professionals preserve data privacy and ethics
Develop a project plan considering roles and responsibilities of team members

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

21 assignments¹

AI Graded see disclaimer

Taught in English

See how employees at top companies are mastering in-demand skills

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Build your Data Analysis expertise

This course is part of the Google Advanced Data Analytics Professional Certificate

When you enroll in this course, you'll also be enrolled in this Professional Certificate.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate from Google

There are 5 modules in this 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

Module details

You’ll begin with an introduction to the Google Advanced Data Analytics Certificate. Then, you'll explore the history of data science and ways that data science helps solve problems today.

What's included

8 videos8 readings3 assignments1 plugin

8 videosTotal 23 minutes

Welcome to the Google Advanced Data Analytics Certificate5 minutes
Introduction to Course 13 minutes
Get started with your Google Advanced Data Analytics Certificate2 minutes
Welcome to module 13 minutes
Explore your data toolbox5 minutes
Wrap-up1 minute
Lois-An: Navigate your data career with curiosity2 minutes
Prepare for your first assessment 2 minutes

8 readingsTotal 42 minutes

Google Advanced Data Analytics Certificate overview8 minutes
Course 1 overview8 minutes
Helpful resources and tips8 minutes
Data discourse over the years4 minutes
Prepare to assess your readiness for the Google Advanced Data Analytics Certificate4 minutes
Understand your readiness score4 minutes
Connect with other learners4 minutes
Glossary terms from module 12 minutes

3 assignmentsTotal 80 minutes

Reflection: Your advanced data analytics journey10 minutes
Assess your readiness for the Advanced Analytics Data Certificate50 minutes
Module 1 challenge20 minutes

1 pluginTotal 5 minutes

Google Advanced Data Analytics Certificate participant entry survey5 minutes

Now that you’re more familiar with the history of data science, you’re ready to explore today’s data career space. You’ll learn more about how data professionals manage and analyze their data, as well as how data-driven insights can help organizations.

What's included

8 videos9 readings5 assignments2 plugins

8 videosTotal 27 minutes

Welcome to module 21 minute
Adrian: Create a data-driven business solution3 minutes
Data-driven careers drive modern business5 minutes
Leverage data analysis in nonprofits4 minutes
The top skills needed for a data career 5 minutes
Important ethical considerations for data professionals5 minutes
The data professional career space5 minutes
Wrap-up1 minute

9 readingsTotal 56 minutes

Profiles of data professionals 8 minutes
Where data makes a difference for the future4 minutes
Ideal qualities for data analytics professionals8 minutes
Volunteer data skills to make a positive impact 8 minutes
Critical data security and privacy principles8 minutes
The practices and principles of good data stewardship4 minutes
Build the perfect data team8 minutes
Activity Exemplar: Organize your data team4 minutes
Glossary terms from module 24 minutes

5 assignmentsTotal 96 minutes

Test your knowledge: Data-driven careers4 minutes
Test your knowledge: Data career skills6 minutes
Activity: Organize your data team30 minutes
Test your knowledge: Work in the field6 minutes
Module 2 challenge50 minutes

2 pluginsTotal 20 minutes

Explore: The data career neighborhood10 minutes
[Turkish learners ONLY] Explore: The data career neighborhood - Türkçe10 minutes

You’ll identify the skills data professionals use to analyze data. You'll also explore how data professionals collaborate with teammates.

What's included

4 videos4 readings3 assignments

4 videosTotal 8 minutes

Welcome to module 30 minutes
Cassie: A lifelong love of data3 minutes
The future of data careers3 minutes
Wrap-up1 minute

4 readingsTotal 16 minutes

Current and future tools4 minutes
How data professionals use AI4 minutes
The places you’ll go… 4 minutes
Glossary terms from module 34 minutes

3 assignmentsTotal 103 minutes

Activity: Write prompts for Gemini45 minutes
Test your knowledge: Trajectory of the field8 minutes
Module 3 challenge50 minutes

You’ll learn about the PACE (Plan, Analyze, Construct, Execute) project workflow and how to organize a data project. You’ll also learn how to communicate effectively with teammates and stakeholders.

What's included

7 videos9 readings6 assignments2 plugins

7 videosTotal 22 minutes

Welcome to module 41 minute
Hautahi: Importance of communication in a data science career3 minutes
Introduction to PACE7 minutes
Key elements of communication4 minutes
Communication drives PACE4 minutes
Connect PACE with upcoming course themes3 minutes
Wrap-up1 minute

9 readingsTotal 52 minutes

The PACE Stages8 minutes
Best communication practices for data professionals4 minutes
Activity Exemplar: Communicate with stakeholders in different roles4 minutes
Elements of successful communication4 minutes
The value of the PACE strategy document 8 minutes
Communicate objectives with a project proposal8 minutes
Connect PACE with executive summaries8 minutes
Activity Exemplar: Create a project proposal4 minutes
Glossary terms from module 44 minutes

6 assignmentsTotal 146 minutes

Test your knowledge: The data project workflow 6 minutes
Activity: Communicate with stakeholders in different roles30 minutes
Test your knowledge: Elements of communication6 minutes
Activity: Create a project proposal 50 minutes
Test your knowledge: Communicate like a data professional4 minutes
Module 4 challenge50 minutes

2 pluginsTotal 20 minutes

Categorize: PACE workflow tasks10 minutes
[Turkish learners ONLY] Categorize: PACE workflow tasks - Türkçe10 minutes

You’ll complete an end-of-course project, gaining an opportunity to apply your new data skills and knowledge from Course 1 to a workplace scenario, and practice solving a business problem.

What's included

5 videos12 readings4 assignments6 ungraded labs

5 videosTotal 13 minutes

The value of a portfolio4 minutes
Welcome to module 53 minutes
Introduction to your Course 1 end-of-course portfolio project2 minutes
End-of-course project wrap-up and tips for ongoing career success3 minutes
Course wrap-up1 minute

12 readingsTotal 80 minutes

Review pandas10 minutes
End-of-course portfolio project introduction4 minutes
Explore your Course 1 workplace scenarios8 minutes
Course 1 end-of-course portfolio project overview: Automatidata8 minutes
Activity Exemplar: Create your Course 1 Automatidata project8 minutes
Course 1 end-of-course portfolio project overview: TikTok8 minutes
Activity Exemplar: Create your Course 1 TikTok project8 minutes
Course 1 end-of-course portfolio project overview: Waze8 minutes
Activity Exemplar: Create your Course 1 Waze project8 minutes
Course 1 glossary2 minutes
Join the community4 minutes
Get started on the next course4 minutes

4 assignmentsTotal 135 minutes

Activity: Create your Course 1 Automatidata project 30 minutes
Activity: Create your Course 1 TikTok project 30 minutes
Activity: Create your Course 1 Waze project 30 minutes
Assess your Course 1 end-of-course project45 minutes

6 ungraded labsTotal 240 minutes

Activity: Course 1 Automatidata project lab60 minutes
Exemplar: Course 1 Automatidata project lab20 minutes
Activity: Course 1 TikTok project lab60 minutes
Exemplar: Course 1 TikTok project lab20 minutes
Activity: Course 1 Waze project lab60 minutes
Exemplar: Course 1 Waze project lab20 minutes

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Reviewed on May 8, 2024

This course is more than just training a few tools. Rather, it helps to have a proper view of the principles of managing and advancing a data-related project.

Reviewed on 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.

Reviewed on Aug 17, 2025

This Google FDS segment delivers solid tactics and sets expectations for the course student to enter a work environment with an established professional tone.

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