C S 575
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Introduction to Graph Data Science
Course Description
Use graph structures to explore labeled data and discover network relationships within the data. Understand network relationships, learn graph models of common network structures, identify network communities and influential members, and work with knowledge graphs.
When Taught
Winter
Fixed/Max
3
Fixed
3
Other Prerequisites
Linear Algebra
Title
Network Algorithms
Learning Outcome
Students will be able to implement and use Barabasi-Albert, Watts-Strogatz, Erdos-Renyi, and affiliation network-based algorithms. This fulfills the Intellectually Enlarging aim by requiring the rigorous mental discipline and technical depth necessary to model complex global systems.
Title
Graph Theory Foundations
Learning Outcome
Students will be able to implement and use graph theory concepts applicable to networks: adjacency matrix, adjacency matrix, adjacency lists, graph Laplacian, algebraic connectivity, spectral graph properties. This outcome is Intellectually Enlarging while combining abstract linear algebra and practical data science.
Title
Diffusion Dynamics
Learning Outcome
Simulate the spread of information or disease across a network by modeling simple and complex contagion processes. This aligns with the Spiritually Strengthening aim by challenging students to understand how influence travels through communities and to consider their role in promoting uplifting connections.
Title
Network Metrics
Learning Outcome
Students will apply graph metrics to understand diffusion dynamics: clustering, density, diameter, algebraic connectivity, degree distribution, distance, modularity, assortativity. This supports the Character Building aim by requiring the technical integrity and "sustained effort" needed to accurately assess the health and structure of a social or physical network.
Title
Agent-Based Modeling
Learning Outcome
Students will be able to implement agent-based models over networks. This fosters Lifelong Learning and Service by training students to use their knowledge to "go forth to serve" by predicting and solving real-world challenges in public health or social organization.
Title
Network Mitigation and Promotion
Learning Outcome
Students will be able to mitigate/promote network effects by identifying communities, removing edges, adding edges, choosing early adopters. This advances the Character Building aim as students must exercise "responsibility" and ethical judgment when making decisions that impact the connectivity and agency of a digital or local community.
