ICS 491: Human-Centered Data Science
Undergraduate course, ICS Department, University of Hawaiʻi at Mānoa, 2023
There are several challenges that arise when working with human data, including privacy, fairness, ethics, and new modeling methods - to name just a few. Human-Centered Data Science is a course which covers the human-facing aspects of data science. This course discusses methods developed specifically for the analysis of biological, medical, social, text, and audiovisual data. As such, this course will cover the basics of biomedical informatics, health informatics, social network informatics, media analytics, and natural language processing. These topics require a thorough discussion of study design, research study analysis, privacy-preserving analysis, unbiased analysis, explainable analysis, qualitative analysis, and ethical tradeoffs between analysis decisions. No prior data science knowledge is required.
This is an unofficial and condensed copy of the course syllabus for public viewing. The official syllabus with all formal UHM policies and assignment submission details is available to course students on Laulima.
Coursework: Coursework consists of three Python notebook homework coding assignments, a final class project for a human-centered data science topic of your choosing (coding and writing) including several intermediate milestones throughout the semester, and in-class discussions and activities.
Grading: Grading will consist of a combination of a coding assignments, written work, presentations, and participation. Specifically, the breakdown is as follows:
- Class attendance and participation: 10% (excused absences are okay; just ask me beforehand)
- Class presentations: 10% (2 milestone presentations, 1 final project presentation, and 1 topic discussion leading; 2.5% each)
- Python coding notebooks: 30% (3 notebooks; 10% each)
- Final project milestones: 30% (6 milestones; 5% each)
- Final project report and code: 20%