CMPU 395 - Advanced Special Topics

Semester Offered: Fall and Spring
1 unit(s)

In-depth treatment of specialized topics in Computer Science.

Topic for 2026/27a: Distributed Systems. A distributed system is one made of networked components that appear to the user as a single cohesive entity. Compared to centralized systems, the ability to share resources in a distributed setting enables improved performance, reliability, and scalability. This course explores the fundamental challenges in distributed systems, including fault tolerance, replication, and consistency. It examines solutions and the design principles behind them through in-depth case studies. Programming assignments provide hands-on experience with distributed system operation and creation. Rui Meireles.

Topic for 2026/27b: Social Computing: Network Analysis & Influence. This course explores how social networks shape information flows, collective behavior, and other social phenomena, such as influence. Using quantitative and computational methods, students analyze real-world social data to study networks across diverse contexts, from online platforms to local communities. Topics include detecting clusters, analyzing influence, and exploring network structure. The course also examines ethical considerations in algorithmic governance. Applications include social media analytics, recommender systems, and the study of social structures in both virtual and physical spaces. Students work individually or in groups on a significant final project using a dataset of their choosing. Jacob Erickson.

Prerequisite(s): a: CMPU 224, CMPU 203.

b: Either CMPU 250 or MATH 244 , or permission of the instructor.

Two 75-minute periods.

Course Format: CLS