Qian Zhang
Was sagt dein Gewissen? — 'Du sollst der werden, der du bist.'
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Northeastern University launched the first Network Science PhD program in academic year 2014/15. As one of the core courses for the program, Network Science Data is designed to equip future network scientists with computational tools to analyze networks from real-world data, and uncover structural and temporal properties of networks, as well as dynamical phenomenon on top of networks. 

This course was first designed and instructed by Dr. Nicola Perra in 2014/15. Since 2015/16 academic year, Dr. Matteo Chinazzi and I have co-instructed this course. Starting from 2017/18 academic year, we have re-designed it as a two-semester course with more advanced computing techniques (PHYS7331) and cutting-edge network science research topics (PHYS7332).

Students in past years were from network science, physics, bioinformatics, industrial engineering, statistics, and business.
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PHYS7332 Network Science Data II
Topics
Network Science Fundamental, Models & Centrality Measures
Network Sampling and Reduction
Dynamical Processes on Networks
Community Detection
Temporal Networks
​Multilayer Networks
Syllabus Spring 2018
PHYS7331 Network Science Data
Topics
Basic Python
Python for scientific computing
Web crawling and API
​Data Structure
Object-oriented Programming
Algorithms
Hadoop & Cloud computing
Syllabus Fall 2017
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PHYS7331 Network Science Data 
(Before 2017/18 academic year)
Topics
Introduction to Python for scientific computing
Network Science Fundamental, Models & Centrality Measures
Network Sampling and Reduction
Dynamical Processes on Networks
Community Detection
Temporal Networks
​Syllabus Spring 2017

Coding practice resources:
  • Project Euler
  • Code Wars
  • Rosetta Code
  • Leet Code
  • Hacker Rank
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