DS 5500 — Data Science Capstone

4 semester hoursGraduateLectureusually offered: fall, springtypical days: T/FBostonOnlinePortland, MaineSilicon Valley, CALive CastOnlineTraditional

Offers students a capstone opportunity to practice data science skills learned in previous courses and to build a portfolio. Students practice visualization, data wrangling, and machine learning skills by applying them to semester-long term projects on real-world data. Students may either propose their own projects or choose from a selection of industry options. Emphasizes the overall data science process, including identification of the scientific problem, selection of appropriate machine learning methods, and visualization and communication of results. Lectures may include additional topics, including visualization, communication, and data science ethics.

Prerequisites

Offering history

TermSectionsEnrolledCapacityFullOpen seats/section
Fall 20232647289%4.0
Spring 202449018050%22.5
Fall 20243488358%11.7
Spring 202547719041%28.3
Fall 202546910963%10.0
Spring 202649318151%22.0

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 14% · T 64% · W 29% · Th 3% · F 53%

Common patterns: TF (38% of sections), T (25% of sections), WF (13% of sections), MW (12% of sections), W (5% of sections), R (3% of sections) — in patterns, R means Thursday

Professors

Fall

Spring

Percentages are each professor's average share of the season's enrolled students in recent terms.

Links

Official catalog (DS course descriptions) · Student reviews on RateMyHusky · All DS courses · Plan it at numap.app