Join 2.9 million developers at
Join 2.9 million developers at
LEARNING OBJECTIVES
- Generate a website using R and RStudio.
- Personalize the website with fonts, logos and colors.
- Configure features such as contact forms, page layouts, and social media links.
- Write original content such as blog posts, tutorials, research articles, and project portfolios.
- Deploy the website to the internet using Netlify and GitHub.
- Integrate Google Analytics into the website to capture user activity and use R to analyze it.
Learning Roadmap
1.
Getting Started
Getting Started
Learn how to use R to create and deploy your personal website effectively.
2.
Creating and Deploying the Website
Creating and Deploying the Website
Get started with building, styling, and deploying a personal website using blogdown, GitHub, and Netlify.
3.
Personalizing the Website
Personalizing the Website
6 Lessons
6 Lessons
Examine customizing and configuring your website, authoring content, and integrating analytics tools.
4.
Wrapping Up
Wrapping Up
3 Lessons
3 Lessons
Find out about creating personal websites using R, Hugo themes, and deployment methods.
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
Complete more lessons to unlock your certificate
Developed by MAANG Engineers
ABOUT THIS COURSE
R is one of the major programming languages for working with big data. This course will walk you through building a personal website using R.
To create a website, you don’t need any prior web development experience. This course will introduce you to various freely available tools, including GitHub, Hugo, Netlify, and Google Analytics. This course teaches you how to use R to create a comprehensive website utilizing these tools. You’ll be able to modify a theme and personalize it according to your needs.
By the end of this course, you’ll be able to build a personal website, blog, or portfolio using R.
ABOUT THE AUTHOR
Danny Morris
I am a Principal Data Scientist in the health services industry. In the last 6 years, I have developed various statistical, machine learning, time series, and data mining solutions. My programming experience includes R, Python, SQL, and AWS.
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