Google Data Analytics

Module 1: Bases: Data, Data Everywhere

• Define and explain key data analytics concepts
• Assess analytical thinking skills
• Discuss the role of spreadsheets, query languages, and data visualization tools
• Explore the responsibilities of a data analyst in specific job roles

Module 2: Asking Questions to Make Data-Driven Decisions

• Understand the relevance of data in decision-making
• Demonstrate basic data analysis tasks using spreadsheets
• Describe the importance of structured thinking
• Explain how each step in problem-solving contributes to common analysis scenarios

Module 3: Preparing Data for Exploration

• Explain factors to consider when making decisions about data collection
• Differentiate between biased and unbiased data
• Describe database basics and best practices for data organization
• Discuss the difference between partial and impartial data

Module 4: Data Cleaning

• Define data integrity and its impact
• Apply basic SQL functions to clean string variables in a database
• Develop basic SQL queries for data cleaning
• Describe the process involved in verifying data cleaning results

Module 5: Analyzing Data to Answer Questions

• Discuss the importance of organizing data before analysis
• Demonstrate an understanding of data conversion and formatting
• Use SQL queries to combine data from multiple database tables
• Describe the use of functions for basic data calculations in spreadsheets

Module 6: Sharing Data Through the Art of Visualization

• Describe the use of data visualizations to communicate data and analysis results
• Identify Tableau as a data visualization tool and understand its uses
• Explain the importance and attributes of data-based stories
• Discuss principles and practices associated with effective presentations

Module 7: Data Analysis with R Programming

• Describe the R programming language and its environment
• Understand basic R Markdown formatting for content structure
• Describe visualization generation options in R
• Explain fundamental concepts associated with programming in R

Module 8: Google Data Analytics Certificate Capstone Project: Completing a Case Study

• Differentiate between a synthesis project, a case study, and a portfolio
• Apply data analysis procedures to a specified dataset
• Discuss the use of case studies/portfolios in interactions with recruiters and potential employers