Google (via Coursera)

Google Data Analytics Certificate

Google Data Analytics Professional Certificate

Google's beginner-friendly professional certificate that teaches the full data analysis process: asking questions, preparing and cleaning data, analyzing, and visualizing, using spreadsheets, SQL, Python, and Tableau. A popular career-switch gateway into entry-level data analyst roles.

About 6 months at 10 hours/week (~152 hours of content across 9 courses)

What's on the exam

Google Data Analytics Professional Certificate (Coursera, 9-course series with AI content)

Foundations of Data Analytics

9%

The data ecosystem and analytical thinking · Roles and responsibilities of a data analyst · Common analytics tools and the data life cycle · Spreadsheet basics · Data-driven decision making · Career paths in data analytics

Asking Questions to Make Data-Driven Decisions

10%

Structured thinking and problem types · SMART questions · Connecting data to business objectives · Stakeholder communication · Spreadsheet formulas and functions · Data-driven vs. data-inspired decisions

Preparing Data for Exploration

13%

Data types, formats, and structures · Bias, credibility, and data ethics · Databases and extracting data · Introduction to SQL queries · Data organization and metadata · Protecting and securing data

Processing Data from Dirty to Clean

11%

Data integrity and sampling · Cleaning data in spreadsheets · Cleaning data with SQL · Verifying and reporting cleaning results · Documenting the cleaning process · Data manipulation techniques

Analyzing Data to Answer Questions

17%

Organizing and formatting data · Aggregating and combining data with SQL · Spreadsheet formulas, functions, and pivot tables · Performing calculations across datasets · Working with multiple data sources · Drawing conclusions from analysis

Sharing Data Through Visualization

12%

Principles of effective data visualization · Creating visualizations in Tableau · Designing dashboards · Data storytelling and presentations · Accessibility and avoiding misleading charts · Building a portfolio of visualizations

Data Analysis Using Python

18%

Python fundamentals and syntax · Jupyter notebooks · Working with data using pandas · Cleaning and transforming data in Python · Visualizing data with Python libraries · Applying Python to analysis tasks

Capstone Case Study

7%

Framing a real-world business problem · Applying the full data analysis process end to end · Using AI assistance for cleaning, formulas, visualizations, and code · Building a case study deliverable · Communicating findings to stakeholders · Assembling a portfolio project · Presenting recommendations

Accelerate Your Job Search with AI

4%

Using AI tools in a job search · Tailoring resumes and applications · Preparing for interviews · Presenting a data analytics portfolio

Frequently asked questions

How much does the Google Data Analytics Certificate cost?

Fees vary. Coursera subscription (about $49/month in the US/Canada after a free trial); most learners finish for under ~$300 total. Financial aid available..

How long is the Google Data Analytics Certificate and how many questions does it have?

Per-course graded assessments and a portfolio capstone — About 6 months at 10 hours/week (~152 hours of content across 9 courses).

What do you need to pass the Google Data Analytics Certificate?

Pass each course's graded assessments and complete the capstone to earn the certificate.

Can you retake the Google Data Analytics Certificate?

Quizzes and assessments may be retaken per Coursera policy.

What is the best way to study for the Google Data Analytics Certificate?

Start from the official outline and your primary study materials: the exam is weighted by domain (Foundations of Data Analytics 9%, Asking Questions to Make Data-Driven Decisions 10%, Preparing Data for Exploration 13%, Processing Data from Dirty to Clean 11%, Analyzing Data to Answer Questions 17%, Sharing Data Through Visualization 12%, Data Analysis Using Python 18%, Capstone Case Study 7%, Accelerate Your Job Search with AI 4%). Once you've learned the material, spaced-repetition flashcards organized by those domains are an efficient way to retain it and refresh it before test day.

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