README: [Google Data Analytics Professional Certificate] documentation

My Certificate Credential URL

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Welcome to my learning repository for the Google Data Analytics Professional Certificate.

This repository is created to document and track my progress as I journey through the courses.

Whether you're a fellow learner, a potential employer, or someone interested in data analytics, feel free to explore the content and contribute.

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Purpose

This repository serves several purposes:

• Record Learning Progress: Every section of each course is meticulously documented to track my learning journey. It helps me keep a clear record of what I've learned and achieved.

• Reference Material: All relevant content and resources, including notes, code snippets, and additional references, are compiled for easy access. This creates a valuable reference for future projects or for revisiting concepts.

• Self-Documentation: Keypoints and insights are captured based on my understanding. This self-documentation aids in reinforcing concepts, making it a valuable resource for personal review.

Quick Link

• Case study documentation
• Case study 1: Cyclistic bike-share analysis case study: How does a bike-share navigate speedy success?
  • Case Study 1: R NoteBook
  • Case Study 1: Kaggle Notebook
  • Case Study 1: Github Repository

Table of Contents

Professional Certificate - 8-course series

Foundations: Data, Data, Everywhere

Course 1 • 24 hours • 4.8(96,078 ratings)

Ask Questions to Make Data-Driven Decisions

Course 2 • 19 hours • 4.7(29,470 ratings)

Prepare Data for Exploration

Course 3•24 hours•4.8(18,061 ratings)

Process Data from Dirty to Clean

Course 4•24 hours•4.8(13,744 ratings)

Analyze Data to Answer Questions

Course 5•29 hours•4.6(9,900 ratings)

Share Data Through the Art of Visualization

Course 6•22 hours•4.6(7,983 ratings)

Data Analysis with R Programming

Course 7•36 hours•4.8(9,063 ratings)

Google Data Analytics Capstone: Complete a Case Study

Course 8•8 hours•4.8(13,180 ratings)

What you'll learn

• Gain an immersive understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job
• Learn key analytical skills (data cleaning, analysis, & visualization) and tools (spreadsheets, SQL, R programming, Tableau)
• Understand how to clean and organize data for analysis, and complete analysis and calculations using spreadsheets, SQL and R programming
• Learn how to visualize and present data findings in dashboards, presentations and commonly used visualization platforms

Skills you'll gain

• Data Analysis
• Creating case studies
• Data Visualization
• Data Cleansing
• Developing a portfolio
• Data Collection
• Spreadsheet
• Metadata
• SQL
• Data Ethics
• Data Aggregation
• Data Calculations
• R Markdown
• R Programming
• Rstudio
• Tableau Software
• Presentation
• Data Integrity
• Sample Size Determination
• Decision-Making
• Problem Solving
• Questioning

Contributions

Contributions are highly encouraged! If you've gone through the same courses or have additional insights/resources to share, feel free to submit a pull request. Whether it's fixing a typo, adding a useful resource, or clarifying a concept, your contributions are valuable.

To contribute:

1. Fork the repository.
2. Create a new branch: git checkout -b pr/update-xxx.
3. Make and commit your changes: git commit -m 'Add a new update xxx'.
4. Push to the branch: git push origin pr/update-xxx.
5. Open a pull request.

Acknowledgements

I'd like to express my gratitude to the creators of the [Google Data Analytics Professional Certificate] and the supportive community of learners. Special thanks to anyone who contributes to this repository.

Feel free to reach out if you have any questions or suggestions!

Happy learning! 🚀