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clarecorthell authored Jan 31, 2017
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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.

### Contents
- [The Open-Source Data Science Masters](#the-open-source-data-science-masters)
- [Contents](#contents)
- [The Internet is Your Oyster](#the-internet-is-your-oyster)
- [The Motivation](#the-motivation)
- [An Academic Shortfall](#an-academic-shortfall)
- [Ready?](#ready)
- [The Open Source Data Science Curriculum](#the-open-source-data-science-curriculum)
- [A Note About Direction](#a-note-about-direction)
- [Math](#math)
- [Computing](#computing)
- [Data Analysis](#data-analysis)
- [Data Communication and Design](#data-communication-and-design)
- [Python (Learning)](#python-learning)
- [Python (Libraries)](#python-libraries)
- [Datasets are now here](#datasets-are-now-here)
- [R resources are now here](#r-resources-are-now-here)
- [Data Science as a Profession](#data-science-as-a-profession)
- [Capstone Project](#capstone-project)
- [Resources](#resources)
- [Read](#read)
- [Watch & Listen](#watch--listen)
- [Learn](#learn)
- [Notation](#notation)
- [Contribute](#contribute)

### The Internet is Your Oyster

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)

* **Statistics**
* Statistics I [Princeton / Coursera](http://bit.ly/course-princeton-stats)
* Statistics I [Princeton / Coursera](http://bit.ly/course-princeton-stats)
* Stats in a Nutshell [Book ```$29```](http://amzn.to/1iMnx2X)
* Think Stats: Probability and Statistics for Programmers [Digital](http://bit.ly/ebook-thinkstats) & [Book ```$25```](http://amzn.to/RcVnTf)
* 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)

* **Machine Learning Packages**
* [scikit-learn](http://bit.ly/py-scikit) - Tools for Data Mining & Analysis
* [scikit-learn](http://bit.ly/py-scikit) - Tools for Data Mining & Analysis

* **Networks Packages**
* [networkx](http://bit.ly/py-networkx) - Network Modeling & Viz
* [networkx](http://bit.ly/py-networkx) - Network Modeling & Viz

* **Statistical Packages**
* [PyMC](http://bit.ly/py-pymc) - Bayesian Inference & Markov Chain Monte Carlo sampling toolkit
* [Statsmodels](http://bit.ly/py-statsmodel) - Python module that allows users to explore data, estimate statistical models, and perform statistical tests
* [PyMVPA](http://bit.ly/py-mvpa) - Multivariate Pattern Analysis in Python
* [PyMVPA](http://bit.ly/py-mvpa) - Multivariate Pattern Analysis in Python

* **Natural Language Processing & Understanding**
* [NLTK](http://bit.ly/py-nltk) - Natural Language Toolkit
* [NLTK](http://bit.ly/py-nltk) - Natural Language Toolkit
* [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.

* **Data APIs**
* [twython](http://bit.ly/py-twython) - Python wrapper for the Twitter API
* [twython](http://bit.ly/py-twython) - Python wrapper for the Twitter API

* **Visualization Packages**
* [matplotlib](http://bit.ly/matplotlib-docs) - well-integrated with analysis and data manipulation packages like numpy and pandas
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### Resources

#### Read
* [DataTau](http://bit.ly/datatau) - The "Hacker News" of Data Science
* [DataTau](http://bit.ly/datatau) - The "Hacker News" of Data Science
* [Wikipedia](http://bit.ly/1kKg0gD) - The free encyclopedia
* [The Signal and The Noise - Nate Silver ```$15```](http://amzn.to/1hoxQoG) - Bestseller Pop Sci
* [Zipfian Academy's List of Resources](http://bit.ly/1qoF1We)
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#### Learn
* [Metacademy](http://bit.ly/metacademy) - Search for a concept you want to learn
* [Coursera](http://bit.ly/coursera-online-courses) - Online university courses
* [Coursera](http://bit.ly/coursera-online-courses) - Online university courses
* [Wolfram Alpha](http://bit.ly/wolframalpha-torus) - The smart number and info cruncher
* [Khan Academy](http://bit.ly/khan-academy-lifeinsurance) - High quality, free learning videos

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