GSND6350 (Data-Driven Game Design) course reviews and ratings at Northeastern (NEU). Compare professors with RateMyProfessor reviews.
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.
Data updated October 2026.