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Google Advanced Data Analytics Professional Certificate

4.8(14,000)·260K enrolled
Intermediate 197 hours English Professional CertificateFREE

About this course

Google Advanced Data Analytics picks up where the core Google Data Analytics certificate leaves off. The curriculum shifts from spreadsheets and SQL to Python for data wrangling, statistical testing, and machine learning — covering regression models, hypothesis testing, and a final project that uses real workplace datasets. Seven courses, roughly 197 hours, at an intermediate pace.

What distinguishes this from a generic Python data course is the through-line: every module is framed in the context of making data-driven business decisions, not just passing a technical exam. The capstone requires you to build a complete analysis pipeline — from data cleaning to a machine learning model — and present your findings as you would to a business stakeholder.

This is the right next step if you've completed the Google Data Analytics certificate or already have some SQL and spreadsheet experience. Learners without that foundation will find the statistical concepts come faster with the core certificate under their belt first.

What you'll learn

Use Python (pandas, NumPy, scikit-learn) for data manipulation and analysis
Apply hypothesis testing and statistical inference to real datasets
Build and evaluate regression models for business prediction tasks
Implement basic classification models using scikit-learn
Communicate analytical findings clearly to non-technical stakeholders
Complete a portfolio capstone project using real workplace data

This course includes

197h
On-demand video
Yes
Certificate
Yes
Mobile access
English
Language
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Instructor

GC
Google Career Certificates
Coursera instructor
260K+ learners7 courses4.8 instructor rating

Taught by Google's Career Certificates team with contributions from Google data scientists and analysts who work on real business problems internally.

Requirements

  • Completion of Google Data Analytics Certificate or equivalent SQL/spreadsheet experience
  • No prior Python required — the program starts from scratch
  • A computer with internet access

Who this course is for

  • Completers of the Google Data Analytics Professional Certificate
  • Analysts with SQL and spreadsheet experience looking to move into Python
  • Data professionals wanting to formalise their ML knowledge with a credential
  • Career changers targeting mid-level data analyst or data scientist roles

About this provider

CO
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Frequently asked questions

Yes, noticeably. The core certificate is spreadsheets, SQL, and intro R. Advanced adds Python, statistical inference, and machine learning — all concepts that require more sustained effort. Plan for 10–15 hours per week rather than the 10 the core certificate suggests.
Yes — regression (linear and logistic), decision trees, random forests, and basic model evaluation using scikit-learn. It's an introduction to applied ML, not a deep dive into algorithms. For more depth, the DeepLearning.AI Machine Learning Specialization is the natural follow-on.
Technically yes, but Google recommends the core certificate first. If you already work with SQL and spreadsheets professionally, you can likely skip ahead. If Python is also new to you, starting with the core certificate gives you better grounding.
Google cites median salaries of $74,000 for data analysts in the US. The Advanced certificate positions you for mid-level roles where Python and ML experience are required — typically a step above the junior positions the core certificate targets.
Both are 6-course professional certificates on Coursera targeting data roles. IBM Data Science is broader — it covers Python, SQL, data viz, machine learning, and more courses. Google Advanced Data Analytics is more focused on statistical analysis and applied ML in a business context. Google's brand name carries more weight with non-technical hiring managers.
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