GSND 6350 — Data-Driven Game Design
4 semester hoursGraduateLectureusually offered: springtypical days: ThBostonTraditional
Introduces the topic of game data science and the process of analysis with data science. Focuses on defining and understanding the player experience using game log data. Examines how gameplay data can be used to discover and communicate player behavioral patterns with the goal of supporting decision management, driving action, and/or improving game quality. Covers the fundamental tools, methods, and principles of game data science and data-driven player modeling including the knowledge-discovery process, data collection, feature extraction and selection, pattern recognition to aid in prediction and churn analysis, visualization, and reporting. Covers analytics across game forms, notably online games and delivery platforms. Presents analytical tools and visualization tools that analysts use within the game development pipeline.
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Spring 2024 | 1 | 24 | 48 | 50% | 24.0 |
| Spring 2025 | 1 | 31 | 48 | 65% | 17.0 |
| Spring 2026 | 1 | 26 | 32 | 81% | 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 0% · W 0% · Th 100% · F 0%
Common patterns: R (100% of sections) — in patterns, R means Thursday
Professors
Spring
- Shawn Connor (100% of students) · reviews
Percentages are each professor's average share of the season's enrolled students in recent terms.
Links
Official catalog (GSND course descriptions) · Student reviews on RateMyHusky · All GSND courses · Plan it at numap.app