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Network Science Data and Models
Network Science Data & Models
Chapter 0: Introduction to the Course, Github, Computing Setup
Chapter 1: Python Refresher, Data Structures, Numpy
Chapter 2: Introduction to Networkx 1 — Graph Objects, Properties, Importing Data
Chapter 3: Introduction to Networkx 2 — Graph Properties & Algorithms
Chapter 4: Distributions of Network Properties & Centralities
Chapter 5: Scraping Web Data 1 - BeautifulSoup & HTML
Chapter 6: Constructing a Network from Scraped Data
Chapter 7: Big Data 1 — Algorithmic Complexity & Computing Paths
Chapter 8: Data Science 1 — Pandas, SQL, Regressions
Chapter 9: Data Science 2 — Querying SQL Tables for Network Construction
Chapter 10: Clustering & Community Detection 1 — Traditional
Chapter 11: Clustering & Community Detection 2 — Contemporary
Chapter 12: Visualization 1 — Python
Chapter 14: Machine Learning 1: Color-Coding Cambridge
Chapter 15: Machine Learning 2 — Building up to Graph Convolutional Networks
Chapter 16: Dynamics on Networks 1 — Diffusion and Random Walks
Chapter 17: Dynamics on Networks 2 — Compartmental Models
Chapter 18: Dynamics on Networks 3 — Agent-Based Models
Chapter 19: What To Do When Your Data Seems Too Big
Chapter 20: Network Sampling (Theory)
Chapter 21: Sampling Networks
Chapter 23: Dynamic of Networks: Temporal Networks
Chapter 24: Spatial Data, OSMNX, GeoPandas
Supplemental Material: Exploring colors and colormaps
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