Developing Data Products Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
An engaging course that teaches how to turn raw analysis into interactive, usable data products. This course is designed for beginners with prior R knowledge and focuses on building real-world tools using Shiny, R Markdown, and interactive visualization libraries. With approximately 9 hours of total content, learners will progress through structured modules to create, document, and deploy functional data products, culminating in a final capstone project. Lifetime access ensures ongoing learning and portfolio development.
Module 1: Course Overview
Estimated time: 1 hour
- Introduction to data products and their role in data science
- Course objectives and learning outcomes
- Overview of tools and software: Shiny, R Markdown, Leaflet
- Setting up the R environment for development
Module 2: Interactive Visualizations with Shiny and Plotly
Estimated time: 2 hours
- Building user interfaces with Shiny
- Implementing server logic in Shiny applications
- Creating dynamic graphics using Plotly
- Integrating GoogleVis for interactive charts
Module 3: Enhancing Data Products with R Markdown and Leaflet
Estimated time: 2 hours
- Generating dynamic reports with R Markdown
- Embedding interactive visualizations in reports
- Building maps using Leaflet in R
Module 4: Building and Documenting R Packages
Estimated time: 2 hours
- Understanding the structure of R packages
- Creating a custom R package from scratch
- Documenting functions and writing help files
Module 5: Final Course Project
Estimated time: 2 hours
- Designing an original, interactive data product
- Integrating Shiny, R Markdown, or visualization tools
- Submitting for peer review and feedback
Module 6: Final Project
Estimated time: 2 hours
- Deliverable 1
- Deliverable 2
- Deliverable 3
Prerequisites
- Familiarity with the R programming language
- Basic understanding of data analysis concepts
- Experience with RStudio or similar IDE
What You'll Be Able to Do After
- Build and deploy interactive web-based data applications using Shiny
- Create dynamic, presentation-ready reports with R Markdown
- Design interactive visualizations and maps using Plotly, GoogleVis, and Leaflet
- Develop and document custom R packages for sharing tools
- Showcase data insights through engaging, user-friendly products