BIOE 7210 — A Data Science Toolkit for Human Neuroscience Research
4 semester hoursGraduateLectureusually offered: springtypical days: TBostonTraditional
Introduces fundamental programming, statistics, and machine learning methods that underlie modern human neuroscience research. Emphasizes understanding how linear models form the building blocks for a wide range of commonly used methods, as well as application of these methods through standard scientific computing libraries. With hands-on learning, students use R and Python to work through projects tailored to real-world neuroimaging applications (e.g., fMRI, EEG). Applies basic statistical and machine learning analysis procedures for human neuroscience research with R and Python to understand fundamental considerations underlying their application.
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Spring 2026 | 1 | 4 | 10 | 40% | 6.0 |
Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.
Meeting times
Share of recent sections by weekday: M 0% · T 100% · W 0% · Th 0% · F 0%
Common patterns: T (100% of sections) — in patterns, R means Thursday
Professors
Spring
- Stephanie Noble (100% of students) · reviews
Percentages are each professor's average share of the season's enrolled students in recent terms.
Links
Official catalog (BIOE course descriptions) · All BIOE courses · Plan it at numap.app