{"id":29437424,"url":"https://github.com/jhermienpaul/google-data-analytics-program","last_synced_at":"2025-07-13T06:03:26.260Z","repository":{"id":302423799,"uuid":"1012384455","full_name":"jhermienpaul/google-data-analytics-program","owner":"jhermienpaul","description":"Hands-on learning materials from the 8-course Google Data Analytics Professional Certificate program, covering foundational data skills, tools, and real-world business problem-solving","archived":false,"fork":false,"pushed_at":"2025-07-09T10:08:02.000Z","size":82955,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-07-09T10:43:10.663Z","etag":null,"topics":["bigquery","dashboard","data-analysis","data-analytics","data-modeling","data-storytelling","data-visualization","data-wrangling","descriptive-analytics","diagnostic-analytics","etl-pipeline","r-programming","rstudio","sql","tableau"],"latest_commit_sha":null,"homepage":"https://www.coursera.org/professional-certificates/google-data-analytics","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jhermienpaul.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-07-02T08:52:22.000Z","updated_at":"2025-07-09T10:08:05.000Z","dependencies_parsed_at":"2025-07-02T10:42:21.641Z","dependency_job_id":null,"html_url":"https://github.com/jhermienpaul/google-data-analytics-program","commit_stats":null,"previous_names":["jhermienpaul/google-data-analytics-prof-cert"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/jhermienpaul/google-data-analytics-program","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jhermienpaul%2Fgoogle-data-analytics-program","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jhermienpaul%2Fgoogle-data-analytics-program/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jhermienpaul%2Fgoogle-data-analytics-program/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jhermienpaul%2Fgoogle-data-analytics-program/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jhermienpaul","download_url":"https://codeload.github.com/jhermienpaul/google-data-analytics-program/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jhermienpaul%2Fgoogle-data-analytics-program/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":265096820,"owners_count":23710794,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["bigquery","dashboard","data-analysis","data-analytics","data-modeling","data-storytelling","data-visualization","data-wrangling","descriptive-analytics","diagnostic-analytics","etl-pipeline","r-programming","rstudio","sql","tableau"],"created_at":"2025-07-13T06:02:21.781Z","updated_at":"2025-07-13T06:03:26.255Z","avatar_url":"https://github.com/jhermienpaul.png","language":null,"readme":"\u003ch1 align=\"center\"\u003eGoogle Data Analytics Professional Certificate\u003c/h1\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003ci\u003eGet on the fast track to a career in Data Analytics. In this certificate program, you’ll learn in-demand skills, and get AI training from Google experts. Learn at your own pace, no degree or experience required.\u003c/i\u003e\n  \u003cbr\u003e\u003cbr\u003e\n  \u003ca href=\"https://www.coursera.org/professional-certificates/google-data-analytics\" target=\"_blank\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/Coursera-Google%20Data%20Analytics%20Certificate-0056D2?style=for-the-badge\u0026logo=coursera\u0026logoColor=white\" alt=\"Coursera: Google Data Analytics Professional Certificate\"/\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n\n![Certificate](./Google%20Data%20Analytics%20Professional%20Certificate.png)\n\n[![Verify this certificate on Credly](https://img.shields.io/badge/Credly-View%20Credential-blue?logo=credly)](https://www.credly.com/users/jhermienpaul/badges)\n\n---\n\n### 📖 What you'll learn\n\n- Gain an immersive understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job\n- Learn key analytical skills (data cleaning, analysis, \u0026 visualization) and tools (spreadsheets, SQL, R programming, Tableau)\n- Understand how to clean and organize data for analysis, and complete analysis and calculations using spreadsheets, SQL and R programming\n- Learn how to visualize and present data findings in dashboards, presentations and commonly used visualization platforms\n\n#\n\n### 📈 Skills you'll gain\n\n[![Data Analytics](https://img.shields.io/badge/Data%20Analytics-0057b7?style=for-the-badge)](#)\n[![ETL](https://img.shields.io/badge/ETL-1e88e5?style=for-the-badge)](#)\n[![Data Wrangling](https://img.shields.io/badge/Data%20Wrangling-43a047?style=for-the-badge)](#)\n[![Data Modeling](https://img.shields.io/badge/Data%20Modeling-fbc02d?style=for-the-badge)](#)\n[![Data Analysis](https://img.shields.io/badge/Data%20Analysis-1976d2?style=for-the-badge)](#)\n[![Data Visualization](https://img.shields.io/badge/Data%20Visualization-3949ab?style=for-the-badge)](#)\n[![Data Storytelling](https://img.shields.io/badge/Data%20Storytelling-d81b60?style=for-the-badge)](#)\n[![Dashboard Development](https://img.shields.io/badge/Dashboard%20Development-00897b?style=for-the-badge)](#)\n[![SQL](https://img.shields.io/badge/SQL-4479A1?style=for-the-badge\u0026logo=mysql\u0026logoColor=white)](#)\n[![Tableau](https://img.shields.io/badge/Tableau-E97627?style=for-the-badge\u0026logo=tableau\u0026logoColor=white)](#)\n[![R](https://img.shields.io/badge/R-276DC3?style=for-the-badge\u0026logo=r\u0026logoColor=white)](#)\n[![Google BigQuery](https://img.shields.io/badge/BigQuery-4285F4?style=for-the-badge\u0026logo=google-bigquery\u0026logoColor=white)](#)\n[![RStudio](https://img.shields.io/badge/RStudio-75AADB?style=for-the-badge\u0026logo=rstudio\u0026logoColor=white)](#)\n\n#\n\n### 🏆 Endorsements and recognition\n\n- **ACE® College Credit Recommendation:** Up to 12 credits toward select universities in the US\n- **Google Career Certificates Employer Consortium:** Access to 150+ top employers (Google, Accenture, Deloitte, Verizon, and more)\n- **2.8M+ learners** and 75% of U.S. grads report a positive career outcome within 6 months\n\n#\n\n### 📚 Courses and lessons\n\n1. **Foundations: Data, Data, Everywhere**  \n   - Define and explain key concepts involved in data analytics including data, data analysis, and data ecosystems.\n   - Conduct an analytical thinking self assessment giving specific examples of the application of analytical thinking.\n   - Discuss the role of spreadsheets, query languages, and data visualization tools in data analytics.\n   - Describe the role of a data analyst with specific reference to jobs.\n\n2. **Ask Questions to Make Data-Driven Decisions**  \n   - Explain how the problem-solving road map applies to typical analysis scenarios.\n   - Discuss the use of data in the decision-making process.\n   - Demonstrate the use of spreadsheets to complete basic tasks of the data analyst including entering and organizing data.\n   - Describe the key ideas associated with structured thinking.\n\n3. **Prepare Data for Exploration**  \n   - Explain what factors to consider when making decisions about data collection.\n   - Discuss the difference between biased and unbiased data.\n   - Describe databases with references to their functions and components.\n   - Describe best practices for organizing data.\n\n4. **Process Data from Dirty to Clean**  \n   - Define different types of data integrity and identify risks to data integrity.\n   - Apply basic SQL functions to clean string variables in a database.\n   - Develop basic SQL queries for use on databases.\n   - Describe the process of verifying data cleaning results.\n\n5. **Analyze Data to Answer Questions**  \n   - Discuss the importance of organizing your data before analysis by using sorts and filters.\n   - Convert and format data.\n   - Apply the use of functions and syntax to create SQL queries to combine data from multiple database tables.\n   - Describe the use of functions to conduct basic calculations on data in spreadsheets.\n\n6. **Share Data Through the Art of Visualization**\n   - Describe the use of data visualizations to talk about data and the results of data analysis.\n   - Identify Tableau as a data visualization tool and understand its uses.\n   - Explain what data driven stories are including reference to their importance and their attributes.\n   - Explain principles and practices associated with effective presentations.\n\n7. **Data Analysis with R Programming**  \n   - Describe the R programming language and its programming environment.\n   - Explain the fundamental concepts associated with programming in R including functions, variables, data types, pipes, and vectors.\n   - Describe the options for generating visualizations in R.\n   - Demonstrate an understanding of the basic formatting in R Markdown to create structure and emphasize content.\n\n8. **Capstone Project**  \n   - Identify the key features and attributes of a completed case study.\n   - Apply the practices and procedures associated with the data analysis process to a given set of data.\n   - Discuss the use of case studies/portfolios when communicating with recruiters and potential employers.\n   - Gain a competitive edge by learning AI skills from Google experts.\n\n---\n\n### 🚀 How to use this repo\n\nThis repo is open source! Feel free to:\n- 👀 **Browse** the course readings, exercises, and case studies\n- 💻 **Fork/clone** for your own self-study or review\n- 🤝 **Collaborate** by submitting issues or improvements via pull requests\n- 🌟 **Get inspired** if you’re preparing to be a data professional or want to level up your data skills\n\u003e **Disclaimer:**\n\u003e All content is for educational purposes only and is shared to help aspiring data professionals. Please don’t submit this work as your own in graded assessments—let’s keep it ethical!\n\n---\n\n\u003cp align=\"center\"\u003e\n  \u003cb\u003e✨ I’m always open to networking, collaboration, or sharing insights ✨\u003c/b\u003e\u003cbr\u003e\n  \u003ci\u003eDon’t be shy — connect with me on LinkedIn! 👋\u003c/i\u003e\u003cbr\u003e\u003cbr\u003e\n  \u003ca href=\"https://www.linkedin.com/in/jhermienpaul/\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/LinkedIn-Let's%20Connect!-0077B5?style=for-the-badge\u0026logo=linkedin\u0026logoColor=white\" alt=\"LinkedIn Badge\"/\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjhermienpaul%2Fgoogle-data-analytics-program","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjhermienpaul%2Fgoogle-data-analytics-program","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjhermienpaul%2Fgoogle-data-analytics-program/lists"}