A Journey of Data Science — an interactive training app for people who are new to data: import → clean → visualize → understand, with AI as your assistant and you as the judge.
Developed for WHO data trainings (Global Health Learning Center and country-office sessions), but the content is general: anyone learning data science or starting to use AI assistants at work can use it for self-study.
Documentation: https://shanlong-who.github.io/cataScience/
Guides
| Guide | What you will learn |
|---|---|
| Getting started | Launch the app, follow the module map and use the example data |
| Data-quality workflow | Compare cleaning choices, inspect text and joins, and explain a chart |
| Training guide | Plan a three-hour data science session or a two-hour AI session |
The website contains documentation. Launch the Shiny app from R for the interactive lessons and exercises.
Installation
install.packages("cataScience")or
# install.packages("remotes")
remotes::install_github("shanlong-who/cataScience")Usage
The app opens in your browser. Everything runs locally — no internet connection is needed after installation.
Start with Import → Or use the example data, then follow Cleaning → Missing data, Cleaning → Outliers, Visualize and Quiz. Use Reset to original data to compare cleaning choices.
Use RStudio’s Stop button or Escape in the console to stop the app. Live demonstrations with an external AI assistant need internet access.
What is inside
| Module | Content |
|---|---|
| Import | Upload Excel/CSV files, or use the bundled example data |
| Cleaning | Missing data (MCAR/MAR/MNAR, imputation), outliers, text, merging |
| Visualize | 7 chart types with grouping, faceting, and flipping |
| Statistics | Describing data, normal distribution, t-test, regression |
| AI | Prompting levels, prompt gallery, AI-assisted analysis, “When AI gets it wrong” case study, AI safety |
| Quiz | 27 questions with per-session topic filters |
| Training | Instructor playbook, lab script, critique checklist |
For trainers
The Training → Training guide page inside the app contains a full playbook: a module menu with suggested timings, ready-made agendas (a 3-hour data-science session, a 2-hour AI session, and a full day), and a pre-course checklist for participants.
Participants who do not have R installed can use the portable Windows edition instead — contact the maintainer.
Development
The app source under inst/app/ mirrors the internal training project; edit content there and re-install to test with run_cata().
Contact
Shanlong Ding — dings@who.int