#Data Science Boot Camp 2014 Fall
This boot camp demo and lecture details all the things you need to know to get up and running on your path to becoming a total badass.
#Helpful general resources and links:
https://www.kaggle.com/ --data science competitions
http://www.topcoder.com/ --more competitions in data science
http://www.metacademy.org/ --a reference for learning data science
https://www.coursera.org/course/datascitoolbox --a course on the tools of being a data scientist
#Data science specific references and links: http://www.kdnuggets.com/2014/01/tutorial-data-science-python.html --Data science in detail
http://www.infochimps.com/ --how to cheat
http://misoproject.com/dataset/examples.html --how to visualize
https://snap.stanford.edu/data/
https://snap.stanford.edu/data/#socnets --another great dataset
http://www.pewinternet.org/datasets/pages/2/ --potentially interesting datasets
http://web.stanford.edu/class/cs124/lec/naivebayes.pdf
https://github.com/datumbox/NaiveBayesClassifier/tree/master/src/com/datumbox/opensource/dataobjects --how to implement
http://guidetodatamining.com/chapter-6/ --intro to data mining
http://www.cs.nyu.edu/~mohri/mlu/mlu_lecture_1.pdf --courant intro to data science
http://stackoverflow.com/questions/101268/hidden-features-of-python --the extra stuff in python that gets mentioned less but is still useful