CSCI 4900
Data Science Capstone · 1 instructor on record · 1 section
Boston College's ratings are bunched at the top — the median instructor averages about 88 out of 100 on the raw scale, and 44% of them clear 90 — so a raw score cannot separate anybody. Every figure here is ranked against BC classes and that rank is re-expressed out of 100, which is what turns a raw 88 — the middle of the university — into a figure that says where somebody actually stands. On this scale 77 is the median, 84 the top quarter and 91 the top tenth. Workload is then an adjustment on top of that, worth nothing at all for an ordinary one. Boston College's workload question was not reported in these records, so easiness could not be worked out. That is missing data, not a heavy class — and it takes nothing off the score.
The class itself, averaged across everyone who taught it — who taught it is the board below.
How is this worked out?
That is what a student picking a section is actually choosing between: the board carries each instructor's own score for this class, and the score above is the class averaged across all of them.
Not reported in these records — which is missing data, not an easy class.
How is this worked out?
Boston College's “intellectually challenging” question was not reported in these records, so there is nothing to show. That is missing data, not an easy class.
Not reported in these records — which is missing data, not a light class.
How is this worked out?
Boston College's workload question was not reported in these records, so there is nothing to show. That is missing data, not a light class.
In this Capstone course for Data Science minors, students will apply their skills to real-world projects by working in teams on data science challenges provided by faculty members across the university. Projects may involve machine learning applications for STEM and social science research or data-driven insights for research in the humanities, education, nursing, or social work. Students will be assigned to teams according to their individual interests and major field of study, and they will meet regularly outside of class with their assigned faculty research mentor. The instructor and one or more graduate TAs will provide instruction and guidance during the weekly class meeting. The course will culminate in a final paper and a public presentation, either in a poster session or a series of talks, showcasing the students findings and analyses.
| Instructor | Curve | Easiness | Challenge |
|---|---|---|---|
| Emily Prud'hommeauxAssociate Professor · Computer Science Provisional | 8191 raw · 1 record | — | — |
There is no ranking to read here: Emily Prud'hommeaux is the only instructor with evaluation records for CSCI 4900, so the number is a record, not a position. It rests on 1 record, which is thin — read it as provisional.
Also taught by Emily Prud'hommeaux
5 other classesOther CSCI classes
All of themThe line
All 13 items · means across 1 recordNone of the evaluation questions were reported for these records.
Game log
1 section · newest first| Instructor | Term | Sec | Instr | Course | Work |
|---|---|---|---|---|---|
| Emily Prud'hommeaux | Fall 2025 | 01 | 91 | 84 | — |
How to read this board
Instructors are ranked on their record in this class only, never on their average across everything they teach. Scores are out of 100 — Boston College's 1–5 agreement scale, ×20, the way these numbers were printed for years. Workload is BC's own five-band figure, not a number of hours, and is shown as a rank. A dash means the question was not reported, and is never a zero.