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README.md

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The open-source curriculum for learning Data Science. Foundational in both theory and technologies, the OSDSM breaks down the core competencies necessary to making use of data.
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### Contents
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- [The Open-Source Data Science Masters](#the-open-source-data-science-masters)
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- [Contents](#contents)
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- [The Internet is Your Oyster](#the-internet-is-your-oyster)
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- [The Motivation](#the-motivation)
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- [An Academic Shortfall](#an-academic-shortfall)
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- [Ready?](#ready)
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- [The Open Source Data Science Curriculum](#the-open-source-data-science-curriculum)
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- [A Note About Direction](#a-note-about-direction)
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- [Math](#math)
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- [Computing](#computing)
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- [Data Analysis](#data-analysis)
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- [Data Communication and Design](#data-communication-and-design)
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- [Python (Learning)](#python-learning)
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- [Python (Libraries)](#python-libraries)
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- [Datasets are now here](#datasets-are-now-here)
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- [R resources are now here](#r-resources-are-now-here)
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- [Data Science as a Profession](#data-science-as-a-profession)
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- [Capstone Project](#capstone-project)
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- [Resources](#resources)
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- [Read](#read)
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- [Watch & Listen](#watch--listen)
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- [Learn](#learn)
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- [Notation](#notation)
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- [Contribute](#contribute)
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### The Internet is Your Oyster
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With Coursera, ebooks, Stack Overflow, and GitHub -- all free and open -- how can you afford not to take advantage of an open source education?
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* Convex Optimization / Boyd [Stanford / Lectures](http://stanford.edu/class/ee364a/index.html) / [Book](http://stanford.edu/~boyd/cvxbook/bv_cvxbook.pdf)
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* **Statistics**
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* Statistics I [Princeton / Coursera](http://bit.ly/course-princeton-stats)
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* Statistics I [Princeton / Coursera](http://bit.ly/course-princeton-stats)
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* Stats in a Nutshell [Book ```$29```](http://amzn.to/1iMnx2X)
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* Think Stats: Probability and Statistics for Programmers [Digital](http://bit.ly/ebook-thinkstats) & [Book ```$25```](http://amzn.to/RcVnTf)
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* Think Bayes [Digital](http://bit.ly/ebook-thinkbayes) & [Book ```$25```](http://amzn.to/1hmy4Cr)
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* Flexible and powerful data analysis / manipulation library with labeled data structures objects, statistical functions, etc [pandas](http://bit.ly/py-pandas) & Tutorials [Python for Data Analysis / Book](http://amzn.to/Q2pI5I)
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* **Machine Learning Packages**
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* [scikit-learn](http://bit.ly/py-scikit) - Tools for Data Mining & Analysis
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* [scikit-learn](http://bit.ly/py-scikit) - Tools for Data Mining & Analysis
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* **Networks Packages**
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* [networkx](http://bit.ly/py-networkx) - Network Modeling & Viz
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* [networkx](http://bit.ly/py-networkx) - Network Modeling & Viz
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* **Statistical Packages**
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* [PyMC](http://bit.ly/py-pymc) - Bayesian Inference & Markov Chain Monte Carlo sampling toolkit
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* [Statsmodels](http://bit.ly/py-statsmodel) - Python module that allows users to explore data, estimate statistical models, and perform statistical tests
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* [PyMVPA](http://bit.ly/py-mvpa) - Multivariate Pattern Analysis in Python
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* [PyMVPA](http://bit.ly/py-mvpa) - Multivariate Pattern Analysis in Python
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* **Natural Language Processing & Understanding**
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* [NLTK](http://bit.ly/py-nltk) - Natural Language Toolkit
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* [NLTK](http://bit.ly/py-nltk) - Natural Language Toolkit
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* [Gensim](http://bit.ly/py-gensim) - Python library for topic modeling, document indexing and similarity retrieval with large corpora. Target audience is the natural language processing (NLP) and information retrieval (IR) community.
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* **Data APIs**
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* [twython](http://bit.ly/py-twython) - Python wrapper for the Twitter API
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* [twython](http://bit.ly/py-twython) - Python wrapper for the Twitter API
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* **Visualization Packages**
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* [matplotlib](http://bit.ly/matplotlib-docs) - well-integrated with analysis and data manipulation packages like numpy and pandas
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### Resources
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#### Read
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* [DataTau](http://bit.ly/datatau) - The "Hacker News" of Data Science
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* [DataTau](http://bit.ly/datatau) - The "Hacker News" of Data Science
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* [Wikipedia](http://bit.ly/1kKg0gD) - The free encyclopedia
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* [The Signal and The Noise - Nate Silver ```$15```](http://amzn.to/1hoxQoG) - Bestseller Pop Sci
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* [Zipfian Academy's List of Resources](http://bit.ly/1qoF1We)
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#### Learn
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* [Metacademy](http://bit.ly/metacademy) - Search for a concept you want to learn
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* [Coursera](http://bit.ly/coursera-online-courses) - Online university courses
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* [Coursera](http://bit.ly/coursera-online-courses) - Online university courses
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* [Wolfram Alpha](http://bit.ly/wolframalpha-torus) - The smart number and info cruncher
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* [Khan Academy](http://bit.ly/khan-academy-lifeinsurance) - High quality, free learning videos
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