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.
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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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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Coding practice resources:
