Applied Computing in Health Data Science

Companion repository for PUBH 6854 / PUBH 4201, Fall 2026 (Matthew Bendall, GWU Milken Institute School of Public Health).

Application of computational paradigms in biomedical sciences and health informatics: computing environments, reproducible research, data management, and analysis workflows using R, Python, and generative AI.

Deadlines

All deadlines are at 11:59pm (ET) unless otherwise noted.

Assignment	Due Date
Quiz 1	Fri, Sep 4
Lab 1 — Reproducible Computing Setup	Wed, Sep 9
Lab 2 — Analysis Notebook	Wed, Sep 16
Quiz 2	Fri, Sep 25
Lab 3 — Parsing Messy Health or Genomic Data	Fri, Oct 2
Final Project Proposal	Wed, Oct 7
Quiz 3	Fri, Oct 9
Lab 4 — Database-Driven Feature Table	Fri, Oct 30
Quiz 4	Fri, Oct 30
Lab 5 — Scalable Analysis Workflow	Wed, Nov 11
Quiz 5	Fri, Nov 20
Final Project Presentations	Mon–Wed, Dec 7–9
Final Project (final deliverable)	Mon, Dec 14

Schedule change (Nov): Mon Nov 2 class was cancelled (campus power outage). The Week 11 lecture moved to Wed Nov 4, the Week 12 lecture is Mon Nov 9, and the Week 11 and Week 12 practicals are combined into one session on Wed Nov 11. No assignment due dates changed. See SCHEDULE.md.

Office Hours

I will typically hold office hours 2:30 - 3:30 on Monday or Wednesday (location TBD).

Schedule (subject to change):

Day	Time	Last chance before
Wed Sep 2nd	2:30 - 3:30
Wed Sep 9th	2:30 - 3:30	Lab 1 due 9/9
Mon Sep 14th	2:30 - 3:30	Lab 2 due Wed 9/16
Wed Sep 23rd	2:30 - 3:30
Mon Sep 28th	2:30 - 3:30	Lab 3 due Fri 10/2
Wed Oct 7th	2:30 - 3:30	Final project proposal due 10/7
Mon Oct 12th	2:30 - 3:30
Wed Oct 21st	2:30 - 3:30
Mon Oct 26th	2:30 - 3:30	Lab 4 due Fri 10/30
Wed Nov 4th	2:30 - 3:30
Mon Nov 9th	2:30 - 3:30	Lab 5 due Wed 11/11
Wed Nov 18th	2:30 - 3:30
Wed Dec 2nd	2:30 - 3:30
Mon Dec 7th	2:30 - 3:30

Additional office hours are by appointment.

Repository structure

• lectures/ — one folder per week (week01…week15), slides and in-class materials
• labs/ — the 5 graded lab assignments; see labs/README.md for the full list, due dates, and submission instructions shared by all labs
• project/ — final project requirements, proposal template, rubrics, example project ideas
• environment/ — environment/dependency files (conda, renv, Docker) for the course
• setup/ — one-time computer setup instructions, by OS (SETUP.md is the entry point)
• data/ — raw/ (input datasets used in labs/lectures) and processed/
• resources/ — supplemental readings and slide assets

Course structure

15-week semester in 3 modules:

1. Weeks 1–5 — Computing Environments, Reproducibility, and Data Wrangling
2. Weeks 6–10 — Programming, Databases, and Scientific Visualization
3. Weeks 11–15 — Generative AI, Prompt Engineering, and Advanced Workflows

See SCHEDULE.md for the full session-by-session schedule and GRADING_AND_POLICIES.md for grading breakdown, evaluation criteria, and class policies (collaboration, generative AI use, late work, etc.). See project/requirements.md for final project details and the syllabus for the authoritative, official version of policies and grading.

Setup

One-time computer setup (terminal, git, conda/mamba, uv, R/renv, Docker, an IDE) lives in setup/SETUP.md, split out by OS (Windows, macOS, Linux). The course's own reference environment files (used to build/test lecture demos and lab solutions) are in environment/.

License

Code is licensed under MIT. Lecture slides, notes, text, images, and video are licensed under CC BY-SA 4.0.