13 Appendix I: Resources

13.1 Chapter 1: Creating a Quarto Website and Deploying on GitHub Pages

Quarto Documentation: https://quarto.org/docs/websites/
GitHub Pages Guide: https://pages.github.com/
RStudio and Quarto Integration Video: YouTube Tutorial

13.2 Chapter 2: Interactive Data Visualization with ggplot2 and Plotly

ggplot2 Documentation: https://ggplot2.tidyverse.org/
Plotly R Library: https://plotly.com/r/
Data Visualization with R Video Tutorials: DataCamp

13.3 Chapter 3: Data Collection with APIs and Web Scraping

httr Package Documentation: https://cran.r-project.org/web/packages/httr/index.html
rvest Package for Web Scraping: https://rvest.tidyverse.org/
Web Scraping in R Video Guide: YouTube Tutorial

13.4 Chapter 4: Introduction to Shiny for Interactive Web Applications

Shiny Package Documentation: https://shiny.rstudio.com/
Deploying Shiny Apps on shinyapps.io: shinyapps.io User Guide
Building Shiny Apps Video Series: RStudio Education

13.5 Chapter 5: Advanced Shiny – Embedding Apps in Quarto

Embedding Shiny Apps in Quarto Documentation: Quarto Websites Guide
GitHub Pages Deployment for Quarto Sites: GitHub Pages Guide
Advanced Shiny Techniques Video Tutorial: YouTube Tutorial

13.6 Chapter 6: Data Management and Exploratory Data Analysis (EDA)

dplyr Package for Data Manipulation: https://dplyr.tidyverse.org/
tidyr Package for Data Tidying: https://tidyr.tidyverse.org/
EDA Techniques in R Video Course: Coursera Course

13.7 Chapter 7: Introduction to Machine Learning Models in R

caret Package for Machine Learning: https://topepo.github.io/caret/index.html
tidymodels Framework Overview: https://www.tidymodels.org/
Machine Learning with R Video Series: edX Course

13.8 Chapter 8: Introduction to Language Models and Text Analysis in R

tidytext Package for Text Mining: https://cran.r-project.org/web/packages/tidytext/index.html
Text Mining with R Book by Julia Silge and David Robinson: Online Book
Text Analysis in R Video Tutorial: YouTube Tutorial

13.9 Chapter 9: Leveraging GenAI for Data Science and Programming in R

GitHub Copilot Documentation: https://docs.github.com/en/copilot
OpenAI’s ChatGPT Documentation: https://beta.openai.com/docs/
AI Tools for Coding Efficiency Video Guide: YouTube Tutorial on GitHub Copilot and ChatGPT Integration

13.10 Additional Resources

13.10.1 Books

Wickham, H., & Grolemund, G. (2016). R for Data Science. O’Reilly Media.
Boehmke, B., & Greenwell, B. (2019). Hands-On Machine Learning with R. CRC Press.

13.10.2 Online Courses

Coursera’s Data Science Specialization by Johns Hopkins University
edX’s Professional Certificate in Data Science by Harvard University

13.10.3 Communities & Forums

Stack Overflow: For technical questions and coding help.
RStudio Community: A forum for discussing R-related topics.

This resources chapter compiles all the essential links, references, and videos from each chapter of the bootcamp, providing participants with a comprehensive guide to further their learning and exploration in data science. ```

13.10.4 Explanation

This chapter provides a structured list of resources categorized by each chapter topic, including documentation links, video tutorials, books, online courses, and community forums. This ensures participants have access to all necessary materials to continue their education beyond the bootcamp.

Sources [1] 7 Steps of Writing an Excellent Academic Book Chapter - Enago https://www.enago.com/academy/7-steps-of-writing-academic-book-chapter/ [2] Chapter by Chapter: An Online Program for Chapter Book Writers https://www.highlightsfoundation.org/workshop/chapter-by-chapter-an-online-program-for-chapter-book-writers/ [3] How to write your chapter outlines - Louisa Deasey Author https://louisadeasey.com/how-to-write-chapter-outlines/ [4] Writing Chapters: Really Useful Links by Lucy O’Callaghan - https://www.writing.ie/resources/writing-chapters-really-useful-links-by-lucy-ocallaghan/ [5] How to write a book chapter - Raul Pacheco-Vega, PhD https://www.raulpacheco.org/2018/07/how-to-write-a-book-chapter/ [6] Writing Resources - Lisa Poisso https://www.lisapoisso.com/editing/writing-resources-fiction/ [7] Let’s compile a comprehensive list of resources for writers - Reddit https://www.reddit.com/r/writing/comments/25jt4p/lets_compile_a_comprehensive_list_of_resources/ [8] Writing Resources I Recommend if You Want to Be a Writer https://jchenwriter.com/writing-resources/

# Appendix I: Resources ## Chapter 1: Creating a Quarto Website and Deploying on GitHub Pages - **Quarto Documentation:** <https://quarto.org/docs/websites/> - **GitHub Pages Guide:** <https://pages.github.com/> - **RStudio and Quarto Integration Video:** [YouTube Tutorial](https://www.youtube.com/watch?v=_bglTCjgcqY) ## Chapter 2: Interactive Data Visualization with ggplot2 and Plotly - **ggplot2 Documentation:** <https://ggplot2.tidyverse.org/> - **Plotly R Library:** <https://plotly.com/r/> - **Data Visualization with R Video Tutorials:** [DataCamp](https://www.datacamp.com/courses/data-visualization-with-ggplot2-part-1) ## Chapter 3: Data Collection with APIs and Web Scraping - **httr Package Documentation:** <https://cran.r-project.org/web/packages/httr/index.html> - **rvest Package for Web Scraping:** <https://rvest.tidyverse.org/> - **Web Scraping in R Video Guide:** [YouTube Tutorial](https://www.youtube.com/watch?v=YzP3oF0mG8U) ## Chapter 4: Introduction to Shiny for Interactive Web Applications - **Shiny Package Documentation:** <https://shiny.rstudio.com/> - **Deploying Shiny Apps on shinyapps.io:** [shinyapps.io User Guide](https://docs.rstudio.com/shinyapps.io/) - **Building Shiny Apps Video Series:** [RStudio Education](https://www.rstudio.com/resources/training/shiny-tutorials/) ## Chapter 5: Advanced Shiny – Embedding Apps in Quarto - **Embedding Shiny Apps in Quarto Documentation:** [Quarto Websites Guide](https://quarto.org/docs/websites/shiny.html) - **GitHub Pages Deployment for Quarto Sites:** [GitHub Pages Guide](https://docs.github.com/en/pages) - **Advanced Shiny Techniques Video Tutorial:** [YouTube Tutorial](https://www.youtube.com/watch?v=YN75YXaLFGM) ## Chapter 6: Data Management and Exploratory Data Analysis (EDA) - **dplyr Package for Data Manipulation:** <https://dplyr.tidyverse.org/> - **tidyr Package for Data Tidying:** <https://tidyr.tidyverse.org/> - **EDA Techniques in R Video Course:** [Coursera Course](https://www.coursera.org/learn/exploratory-data-analysis) ## Chapter 7: Introduction to Machine Learning Models in R - **caret Package for Machine Learning:** <https://topepo.github.io/caret/index.html> - **tidymodels Framework Overview:** <https://www.tidymodels.org/> - **Machine Learning with R Video Series:** [edX Course](https://www.edx.org/course/machine-learning-with-r-from-beginner-to-expert) ## Chapter 8: Introduction to Language Models and Text Analysis in R - **tidytext Package for Text Mining:** <https://cran.r-project.org/web/packages/tidytext/index.html> - **Text Mining with R Book by Julia Silge and David Robinson:** [Online Book](https://www.tidytextmining.com/) - **Text Analysis in R Video Tutorial:** [YouTube Tutorial](https://www.youtube.com/watch?v=YzP3oF0mG8U) ## Chapter 9: Leveraging GenAI for Data Science and Programming in R - **GitHub Copilot Documentation:** <https://docs.github.com/en/copilot> - **OpenAI's ChatGPT Documentation:** <https://beta.openai.com/docs/> - **AI Tools for Coding Efficiency Video Guide:** [YouTube Tutorial on GitHub Copilot and ChatGPT Integration](https://www.youtube.com/watch?v=YzP3oF0mG8U) ## Additional Resources ### Books 1. Wickham, H., & Grolemund, G. (2016). *R for Data Science*. O'Reilly Media. 2. Boehmke, B., & Greenwell, B. (2019). *Hands-On Machine Learning with R*. CRC Press. ### Online Courses 1. Coursera's Data Science Specialization by Johns Hopkins University 2. edX's Professional Certificate in Data Science by Harvard University ### Communities & Forums 1. Stack Overflow: For technical questions and coding help. 2. RStudio Community: A forum for discussing R-related topics. This resources chapter compiles all the essential links, references, and videos from each chapter of the bootcamp, providing participants with a comprehensive guide to further their learning and exploration in data science. \`\`\` ### Explanation This chapter provides a structured list of resources categorized by each chapter topic, including documentation links, video tutorials, books, online courses, and community forums. This ensures participants have access to all necessary materials to continue their education beyond the bootcamp. Sources \[1\] 7 Steps of Writing an Excellent Academic Book Chapter - Enago https://www.enago.com/academy/7-steps-of-writing-academic-book-chapter/ \[2\] Chapter by Chapter: An Online Program for Chapter Book Writers https://www.highlightsfoundation.org/workshop/chapter-by-chapter-an-online-program-for-chapter-book-writers/ \[3\] How to write your chapter outlines - Louisa Deasey Author https://louisadeasey.com/how-to-write-chapter-outlines/ \[4\] Writing Chapters: Really Useful Links by Lucy O'Callaghan - https://www.writing.ie/resources/writing-chapters-really-useful-links-by-lucy-ocallaghan/ \[5\] How to write a book chapter - Raul Pacheco-Vega, PhD https://www.raulpacheco.org/2018/07/how-to-write-a-book-chapter/ \[6\] Writing Resources - Lisa Poisso https://www.lisapoisso.com/editing/writing-resources-fiction/ \[7\] Let's compile a comprehensive list of resources for writers - Reddit https://www.reddit.com/r/writing/comments/25jt4p/lets_compile_a_comprehensive_list_of_resources/ \[8\] Writing Resources I Recommend if You Want to Be a Writer https://jchenwriter.com/writing-resources/