Google Data Analytics De course Syllabus

Full curriculum breakdown — modules, lessons, estimated time, and outcomes.

Overview: The Google Data Analytics Professional Certificate is a comprehensive 9-course program designed to equip beginners with in-demand data analytics skills. Spanning approximately 6 months with a recommended 10 hours per week, the program covers the full data analysis lifecycle—from data collection and cleaning to visualization and decision-making. Learners engage with real-world tools like SQL, Python, Tableau, and R, applying skills through hands-on projects. The curriculum emphasizes practical, job-ready competencies and includes AI-augmented analytics training. While the course is free to audit, a paid subscription is required to earn the certificate. All content is self-paced and delivered on Coursera.

Module 1: Ask Questions to Make Data-Driven Decisions

Estimated time: 15 hours

  • Define data analytics and its role in business
  • Understand the data analysis process
  • Learn how to ask effective analytical questions
  • Explore real-world data analyst roles and responsibilities

Module 2: Prepare Data for Exploration

Estimated time: 20 hours

  • Discover data cleaning techniques
  • Work with spreadsheets and SQL for data organization
  • Identify and handle data integrity issues
  • Transform and document data for analysis

Module 3: Process Data from Dirty to Clean

Estimated time: 25 hours

  • Use SQL to clean and filter data
  • Apply functions in spreadsheets to standardize data
  • Detect and correct errors in datasets
  • Document cleaning processes for reproducibility

Module 4: Analyze and Share Data with Visualizations

Estimated time: 20 hours

  • Perform data analysis using SQL and Python
  • Create visualizations in Tableau
  • Interpret trends and patterns in data
  • Communicate insights effectively to stakeholders

Module 5: Data Analysis with R Programming

Estimated time: 20 hours

  • Introduction to R and RStudio
  • Use R for data cleaning and transformation
  • Generate statistical summaries and visualizations
  • Apply R in exploratory data analysis

Module 6: Final Project

Estimated time: 30 hours

  • Select a real-world dataset for analysis
  • Apply the full data analysis process from question to insight
  • Create a portfolio-ready presentation using Tableau or R

Prerequisites

  • No prior experience required
  • Basic computer literacy
  • Access to a modern web browser and internet connection

What You'll Be Able to Do After

  • Collect, clean, and organize data using SQL and spreadsheets
  • Analyze data using Python and R programming
  • Create compelling data visualizations with Tableau
  • Communicate data insights effectively to non-technical audiences
  • Complete a portfolio project demonstrating job-ready skills
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