Structural Analysis & Visualization of Networks | Network Science Course

Comprehensive network science course covering network properties, models, centrality, community detection, and real-world applications. Hands-on labs using Python's NetworkX.

Introduction

This course provides an introduction to the field of network science, covering topics such as network properties, power laws, random graph models, small-world and scale-free networks, centrality measures, link analysis, community detection, and more. The course includes both theoretical lectures and hands-on labs using the NetworkX library in Python.

Highlights

• Comprehensive coverage of network science fundamentals
• Practical experience with network analysis and visualization using Python
• Exposure to cutting-edge research and real-world applications of network analysis

Recommendation

This course is recommended for students and professionals interested in data analysis, machine learning, and the study of complex systems. It provides a solid foundation in network science and equips learners with the skills to analyze and visualize network data in a variety of domains.