Google Data Analytics Professional Certificate Course Syllabus

This Google Data Analytics Professional Certificate course is designed for beginners and offers a comprehensive pathway into the field of data analytics. The program is structured into six modules that progressively build your skills—from foundational concepts to hands-on data analysis and visualization. With an estimated total commitment of 150–200 hours, learners can expect to spend between 3 to 6 months completing the certificate at a flexible pace. Each module combines video lectures, hands-on exercises, and knowledge checks, culminating in a capstone project that simulates a real-world analytics challenge. The curriculum emphasizes practical experience with industry-standard tools including spreadsheets, SQL, R, and Tableau, preparing learners to confidently enter the data workforce.

Module 1: Foundations of Data Analytics

Estimated time: 20 hours

• Introduction to data analytics and its role in business decision-making
• Understanding the data lifecycle: from collection to analysis
• Key skills for data analysts: problem-solving and critical thinking
• Overview of tools: spreadsheets, SQL, and data visualization software

Module 2: Data Cleaning and Preparation

Estimated time: 30 hours

• Understanding data structures and database fundamentals
• Identifying and correcting common data errors
• Using spreadsheets and SQL for data cleaning
• Best practices for data accuracy, consistency, and reliability

Module 3: Data Analysis with Spreadsheets, SQL, and R

Estimated time: 50 hours

• Performing calculations and using pivot tables in spreadsheets
• Writing SQL queries to retrieve and manipulate data
• Using R programming for statistical analysis and data transformation
• Generating data-driven business insights and recommendations

Module 4: Data Visualization and Storytelling

Estimated time: 40 hours

• Creating visual dashboards using Tableau and spreadsheets
• Applying ggplot2 in R for effective data visualization
• Translating complex data into clear, actionable insights
• Developing compelling narratives for stakeholders
• Design principles for engaging and informative visuals

Module 5: Exploratory Data Analysis and Business Applications

Estimated time: 30 hours

• Applying exploratory data analysis (EDA) techniques
• Uncovering trends, patterns, and anomalies in datasets
• Using real-world case studies to solve business problems
• Integrating analytical findings into business decision-making

Module 6: Final Project

Estimated time: 60 hours

• Clean and prepare a real-world dataset using spreadsheets and SQL
• Analyze data using R and perform statistical exploration
• Create interactive dashboards and visualizations in Tableau and R
• Present findings through a comprehensive report and storytelling presentation

Prerequisites

• No prior experience in data analytics required
• Basic computer literacy and comfort with web-based applications
• Access to a reliable internet connection for using online tools

What You'll Be Able to Do After

• Process and clean raw data using spreadsheets and SQL
• Perform data analysis using R programming and statistical methods
• Create compelling data visualizations with Tableau and ggplot2
• Communicate insights effectively through data storytelling
• Complete a portfolio-ready capstone project for job applications