The OpenSource Data Science Masters
The opensource 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 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?
The Motivation
We need more Data Scientists.
…by 2018 the United States will experience a shortage of 190,000 skilled data scientists, and 1.5 million managers and analysts capable of reaping actionable insights from the big data deluge.
– McKinsey Report Highlights the Impending Data Scientist Shortage 23 July 2013
There are little to no Data Scientists with 5 years experience, because the job simply did not exist.
– David Hardtke “How To Hire A Data Scientist” 13 Nov 2012
An Academic Shortfall
Classic academic conduits aren’t providing Data Scientists – this talent gap will be closed differently.
Academic credentials are important but not necessary for highquality data science. The core aptitudes – curiosity, intellectual agility, statistical fluency, research stamina, scientific rigor, skeptical nature – that distinguish the best data scientists are widely distributed throughout the population.
We’re likely to see more uncredentialed, inexperienced individuals try their hands at data science, bootstrapping their skills on the opensource ecosystem and using the diversity of modeling tools available. Just as datascience platforms and tools are proliferating through the magic of open source, big data’s datascientist pool will as well.
And there’s yet another trend that will alleviate any talent gap: the democratization of data science. While I agree wholeheartedly with Raden’s statement that “the crèmedelacrème of data scientists will fill roles in academia, technology vendors, Wall Street, research and government,” I think he’s understating the extent to which autodidacts – the selftaught, uncredentialed, datapassionate people – will come to play a significant role in many organizations’ data science initiatives.
– James Kobielus, Closing the Talent Gap 17 Jan 2013
Ready?
The Open Source Data Science Curriculum
Start here.
Intro to Data Science / UW Videos
 Topics: Python NLP on Twitter API, Distributed Computing Paradigm, MapReduce/Hadoop & Pig Script, SQL/NoSQL, Relational Algebra, Experiment design, Statistics, Graphs, Amazon EC2, Visualization.
Data Science / Harvard Videos & Course
 Topics: Data wrangling, data management, exploratory data analysis to generate hypotheses and intuition, prediction based on statistical methods such as regression and classification, communication of results through visualization, stories, and summaries.
Data Science with Open Source Tools Book $27
 Topics: Visualizing Data, Estimation, Models from Scaling Arguments, Arguments from Probability Models, What you Really Need to Know about Classical Statistics, Data Mining, Clustering, PCA, Map/Reduce, Predictive Analytics
 Example Code in: R, Python, Sage, C, Gnu Scientific Library
A Note About Direction
This is an introduction geared toward those with at least a minimum understanding of programming , and (perhaps obviously) an interest in the components of Data Science (like statistics and distributed computing). Out of personal preference and need for focus, I geared the original curriculum toward Python tools and resources . R resources can be found here.
Ethics in Machine Intelligence
Human impact is a firstclass concern when building machine intelligence technology. When we build products, we deduce patterns and then reinforce them in the world. Ethics in any Engineering concerns understanding the sociotechnological impact of the products and services we are bringing to bear in the human world – and whether they are reinforcing a future we all want to live in.
Math
Linear Algebra & Programming
 Linear Algebra Khan Academy / Videos
 Linear Algebra / Levandosky Stanford / Book
$10
 Linear Programming (Math 407) University of Washington / Course
 The Manga Guide to Linear Algebra Book
$19
 An Intuitive Guide to Linear Algebra Better Explained / Article
 A Programmer’s Intuition for Matrix Multiplication Better Explained / Article
 Vector Calculus: Understanding the Cross Product Better Explained / Article
 Vector Calculus: Understanding the Dot Product Better Explained / Article
Convex Optimization
 Convex Optimization / Boyd Stanford / Lectures / Book
Statistics
 Stats in a Nutshell Book
$29
 Think Stats: Probability and Statistics for Programmers Digital & Book
$25
 Think Bayes Digital & Book
$25
Differential Equations & Calculus
 Differential Equations in Data Science Python Tutorial
Problem Solving
 ProblemSolving Heuristics “How To Solve It” Polya / Book
$10
Computing
Get your environment up and running with the Data Science Toolbox
Algorithms
 Algorithms Design & Analysis I Stanford / Coursera
 Algorithm Design, Kleinberg & Tardos Book
$125
Distributed Computing Paradigms
 *See Intro to Data Science UW / Lectures on MapReduce
 Intro to Hadoop and MapReduce Cloudera / Udacity Course *includes select free excerpts of Hadoop: The Definitive Guide Book
$29
Databases
 Introduction to Databases Stanford / Online Course
 SQL School Mode Analytics / Tutorials
 SQL Tutorials SQLZOO / Tutorials
Data Mining
 Mining Massive Data Sets / Stanford Coursera & Digital & Book
$58
 Mining The Social Web Book
$30
 Introduction to Information Retrieval / Stanford Digital & Book
$56
Data Design
How does the real world get translated into data? How should one structure that data to make it understandable and usable? Extends beyond database design to usability of schemas and models.
OSDSM Specialization: Web Scraping & Crawling
Machine Learning
Foundational & Theoretical
 Machine Learning Ng Stanford / Coursera & Stanford CS 229
 A Course in Machine Learning UMD / Digital Book
 The Elements of Statistical Learning / Stanford Digital & Book
$80
& Study Group  Machine Learning Caltech / Edx
Practical
 Programming Collective Intelligence Book
$27
 Machine Learning for Hackers ipynb / digital book
 Intro to scikitlearn, SciPy2013 youtube tutorials
Probabilistic Modeling
 Probabilistic Programming and Bayesian Methods for Hackers Github / Tutorials
 Probabilistic Graphical Models Stanford / Coursera
Deep Learning (Neural Networks)
 Neural Networks Andrej Karpathy / Python Walkthrough
 Neural Networks U Toronto / Coursera
 Deep Learning for Natural Language Processing CS224d Stanford
Social Network & Graph Analysis
 Social and Economic Networks: Models and Analysis / Stanford / Coursera
 Social Network Analysis for Startups Book
$22
Natural Language Processing
 From Languages to Information / Stanford CS147 Materials
 NLP with Python (NLTK library) Digital, Book
$36
 How to Write a Spelling Correcter / Norvig (Tutorial)[http://norvig.com/spellcorrect.html]
Data Analysis
One of the “unteachable” skills of data science is an intuition for analysis. What constitutes valuable, achievable, and welldesigned analysis is extremely dependent on context and ends at hand.
 Big Data Analysis with Twitter UC Berkeley / Lectures
 Exploratory Data Analysis Tukey / Book
$81
in Python
 Data Analysis in Python Tutorial
 Python for Data Analysis Book
$24
 An Example Data Science Process ipynb
Data Communication and Design
Visualization
Data Visualization and Communication
 The Truthful Art: Data, Charts, and Maps for Communication Cairo / Book
$21
Theoretical Design of Information
 Envisioning Information Tufte / Book
$36
 The Visual Display of Quantitative Information Tufte / Book
$27
Applied Design of Information
 Information Dashboard Design: Displaying Data for AtaGlance Monitoring Stephen Few / Book
$29
Theoretical Courses / Design & Visualization
 Data Visualization University of Washington / Slides & Resources
 Berkeley’s Viz Class UC Berkeley / Course Docs
 Rice University’s Data Viz class Rice University / Slides
Practical Visualization Resources
 D3 Library / Scott Murray Blog / Tutorials
 Interactive Data Visualization for the Web / Scott Murray Online Book & Book
$26
OSDSM Specialization: Data Journalism
Python (Learning)
 Learn Python the Hard Way Digital & Book
$23
 Python Class / Google
 Think Python Digital & Book
$34
Python (Libraries)
Installing Basic Packages Python, virtualenv, NumPy, SciPy, matplotlib and IPython & Using Python Scientifically
Command Line Install Script for Scientific Python Packages
 numpy Tutorial / Stanford CS231N
 Pandas Cookbook (data structure library)
More Libraries can be found in the “awesome machine learning” repo & in related specializations
Data Structures & Analysis Packages
 Flexible and powerful data analysis / manipulation library with labeled data structures objects, statistical functions, etc pandas & Tutorials Python for Data Analysis / Book
Machine Learning Packages
 scikitlearn  Tools for Data Mining & Analysis
Networks Packages
 networkx  Network Modeling & Viz
Statistical Packages
 PyMC  Bayesian Inference & Markov Chain Monte Carlo sampling toolkit
 Statsmodels  Python module that allows users to explore data, estimate statistical models, and perform statistical tests
 PyMVPA  Multivariate Pattern Analysis in Python
Natural Language Processing & Understanding
 NLTK  Natural Language Toolkit
 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  Python wrapper for the Twitter API
Visualization Packages
 matplotlib  wellintegrated with analysis and data manipulation packages like numpy and pandas
 Seaborn  a highlevel statistical visualization package built on top of matplotlib
iPython Data Science Notebooks
 Data Science in IPython Notebooks (Linear Regression, Logistic Regression, Random Forests, KMeans Clustering)
 A Gallery of Interesting IPython Notebooks  Pandas for Data Analysis
Datasets are now here
R resources are now here
Data Science as a Profession
 Doing Data Science: Straight Talk from the Frontline O’Reilly / Book
$25
 The Data Science Handbook: Advice and Insights from 25 Amazing Data Scientists Book
$22
Capstone Project
 Capstone Analysis of Your Own Design; Quora’s Idea Compendium
 Healthcare Twitter Analysis Coursolve & UW Data Science
 Analyze your LinkedIn Network Generate & Download Adjacency Matrix
Resources
Read
 DataTau  The “Hacker News” of Data Science
 Wikipedia  The free encyclopedia

The Signal and The Noise  Nate Silver
$15
 Bestseller Pop Sci  Zipfian Academy’s List of Resources
 A Software Engineer’s Guide to Getting Started with Data Science
 Data Scientist Interviews / Metamarkets
 /r/MachineLearning
Watch & Listen
 The Life of a Data Scientist / Josh Wills
 The Talking Machines  Podcast about Machine Learning
 What Data Science Is / Hilary Mason
Learn
 Metacademy  Search for a concept you want to learn
 Coursera  Online university courses
 Wolfram Alpha  The smart number and info cruncher
 Khan Academy  High quality, free learning videos
Notation
NonOpenSource books, courses, and resources are noted with $
.
Contribute
Please Contribute – this is Open Source!
Follow me on Twitter @clarecorthell
Refer: https://github.com/datasciencemasters/go#theopensourcedatasciencemasters