Google Data Analytics Korean course Syllabus

Overview: This comprehensive, self-paced program is designed for beginners and spans approximately six months with a recommended commitment of 10 hours per week. The Google Data Analytics Professional Certificate consists of nine courses delivered on Coursera, covering the full data analysis lifecycle—from data collection and cleaning to visualization and communication. Recently updated in January 2026, the curriculum includes foundational and advanced analytics skills, with an emphasis on practical tools like spreadsheets, SQL, Python, R, and Tableau. Learners will build job-ready competencies through hands-on projects and real-world scenarios, culminating in a portfolio-ready capstone project. No prior experience is required, making it ideal for career changers and aspiring data analysts.

Module 1: Ask Questions to Make Data-Driven Decisions

Estimated time: 8 hours

• Understanding the data analyst's role in business decision-making
• Formulating effective analytical questions
• Identifying key data sources and metrics
• Applying the data analysis process to real-world scenarios

Module 2: Prepare Data for Exploration

Estimated time: 12 hours

• Understanding data types and structures
• Exploring data cleaning techniques and best practices
• Identifying and handling missing or duplicate data
• Using spreadsheets for data organization and transformation

Module 3: Process Data from Dirty to Clean

Estimated time: 15 hours

• Validating and reporting data quality issues
• Standardizing and formatting data
• Using SQL for data cleaning and manipulation
• Documenting data cleaning processes

Module 4: Analyze Data to Answer Business Questions

Estimated time: 14 hours

• Performing data analysis using spreadsheets and SQL
• Applying statistical concepts to interpret data
• Using Python for exploratory data analysis
• Identifying patterns and trends in datasets

Module 5: Share Data Insights Through Visualization

Estimated time: 16 hours

• Designing effective data visualizations
• Creating dashboards in Tableau
• Using R for statistical visualization
• Communicating findings to stakeholders clearly and ethically

Module 6: Final Project

Estimated time: 25 hours

• Conduct a complete data analysis case study
• Create a portfolio-ready presentation and dashboard
• Apply AI-enhanced analytics tools to real-world data

Prerequisites

• No prior experience with data analytics required
• Basic computer literacy and internet navigation skills
• Willingness to learn programming and analytical tools

What You'll Be Able to Do After

• Clean and organize complex datasets for analysis
• Use SQL, Python, and spreadsheets to analyze real-world data
• Create interactive dashboards using Tableau and R
• Communicate data insights effectively to non-technical audiences
• Complete a professional portfolio project to showcase to employers