Magolego sna 2015 — различия между версиями

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(Home Assignments)
(Usefull Links\Docs)
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== Usefull Links\Docs ==
 
== Usefull Links\Docs ==
# [https://www.dropbox.com/s/2vvm9xo0wcrcn21/r_markdown.pdf?dl=0| R Markdown Tutorual]
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# [https://www.dropbox.com/s/uxqokfto3ypx472/rmarkdown-cheatsheet.pdf?dl=0 R Markdown Cheat-Sheet]
# [https://www.dropbox.com/s/laqachove29t2xv/r_refcard.pdf?dl=0| R Cheat-Sheet]
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# [https://www.dropbox.com/s/lqogj4t3y4wks2n/R%20Tutorial.pdf?dl=0 R Short Introduction]
# [https://www.dropbox.com/s/q0mlggq160u4b80/short_r_intro.pdf?dl=0| R Short Introduction]
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# [http://swirlstats.com/ Learning R with SWIRL]
# [http://swirlstats.com/| Learning R with SWIRL]
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Версия 19:59, 27 мая 2015

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About the course

Course web-page: http://www.leonidzhukov.net/hse/2015/sna/

Instructors: Prof. Leonid Zhukov, Dr. Ilya Makarov
Teaching assistants: Andrey Shestakov, Dmitry Petrov, Julia Dodonova, Mikhail Dubov, Eugeniy Kolbey, Tanya Makhalova, Pavel Perevedencev, Daniil Gizdatullin, Eugeniy Tsymbalov

Please, send your questions and home assignments to hse.ntwks@gmail.com with prefix [MAGOLEGO SNA 2015] in message topic

Seminars

3 April 2015: Basic concepts and pre-requisites for the course. Introduction to R and igraph [R tutorial (.pdf)], [igraph tutorial (.Rmd), (.html)]
10 April 2015: Graph file-formats. Power law. Network descriptive statistics [Lab Script (.Rmd), (.html)], [Network data (.zip)]
17 April 2015: Graph models [Lab Script (.Rmd), (.html)]
24 April 2015: Centrality metrics [Lab Script (.Rmd), (.html)]
15 May 2015: Dense subgraphs and communities [Lab Script (.Rmd), (.html)]
22 May 2015: Graph Patterns, Assortativity Mixing [Lab Script (.Rmd), (.html)]


Please, put your email here

Home Assignments

1. Power law. Descriptive network analysis -- [due date - 24.04.2015 23:59] -- [(.Rmd), (.html)]
2. Graph models. Centrality metrics -- [due date - 15.05.2015 23:59] -- [(.Rmd), (.html)], NodeXL Tutorial
3. Network preprocessing. Community detection -- [due date - 05.06.2015 23:59] -- [(.Rmd), (.html)]



Results (Update 13.05.2015)

Usefull Links\Docs

  1. R Markdown Cheat-Sheet
  2. R Short Introduction
  3. Learning R with SWIRL