Follow me on Twitter @clarecorthell
+ ++The Open-Source Data Science Masters
+ +The open-source curriculum for learning Data Science. Foundational in both theory and technologies, the OSDSM breaks down the core competencies necessary to make data useful.
+ ++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 high-quality 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 open-source ecosystem and using the diversity of modeling tools available. Just as data-science platforms and tools are proliferating through the magic of open source, big data’s data-scientist 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 crème-de-la-crème 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 self-taught, uncredentialed, data-passionate 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 / Coursera
+ +-
+
- +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 Video Archive & 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.
+ ++Math
+ +★ What are some good resources for learning about numerical analysis? / Quora
+ +-
+
-
+
Linear Algebra & Programming
+ +-
+
- Linear Algebra / Levandosky Stanford / Book
$10+
+ - Linear Programming (Math 407) University of Washington / Course + +
+ - Linear Algebra / Levandosky Stanford / Book
-
+
Statistics
+ + +
+ -
+
Differential Equations & Calculus
+ +-
+
- Differential Equations in Data Science Python Tutorial + +
+ -
+
Problem Solving
+ +-
+
- Problem-Solving Heuristics "How To Solve It" Polya / Book
$10+
+
+ - Problem-Solving Heuristics "How To Solve It" Polya / Book
+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
+ + +
+
OSDSM Specialization: Web Scraping & Crawling
+ +-
+
-
+
Machine Learning
+ +Foundational & Theoretical
+ +-
+
- Machine Learning Ng Stanford / Coursera + +
- 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 scikit-learn, SciPy2013 youtube tutorials + +
+ -
+
Probabilistic Modeling
+ +-
+
- Probabilistic Programming and Bayesian Methods for Hackers Github / Tutorials + +
- Probabalistic Graphical Models Stanford / Coursera + +
+ -
+
Deep Learning (Neural Networks)
+ +-
+
- Neural Networks Andrej Karpathy / Python Walkthrough + +
- Neural Networks U Toronto / Coursera + +
+ -
+
Social Network & Graph Analysis
+ +-
+
- Social and Economic Networks: Models and Analysis / Stanford / Coursera + +
- Social Network Analysis for Startups Book
$22+
+
+ -
+
Natural Language Processing
+ + +
+ -
+
Analysis
+ +-
+
- Python for Data Analysis Book
$24+
+ - Big Data Analysis with Twitter UC Berkeley / Lectures + +
- Exploratory Data Analysis Tukey / Book
$81+
+
+ - Python for Data Analysis Book
+Data Design
+ +-
+
-
+
Visualization
+ +Foundational Information Design Books
+ +-
+
- Envisioning Information Tufte / Book
$36+
+ - The Visual Display of Quantitative Information Tufte / Book
$27+
+
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+
+
+ - Envisioning Information Tufte / Book
OSDSM Specialization: Data Journalism
+ ++ +Python (Learning)
+ +-
+
- Learn Python the Hard Way Digital & Book
$23+
+ - Python Class / Google + +
- Think Python Digital & Book
$34+
+ - Introduction to Computer Science and Programming MIT OpenCourseWare / Lectures + +
+ +Python (Libraries)
+ +Installing Basic Packages Python, virtualenv, NumPy, SciPy, matplotlib and IPython & Using Python Scientifically
+ +Command Line Install Script for Scientific Python Packages
+ +-
+
- +Pandas Cookbook (data structure library) +
More Libraries can be found 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
+ +-
+
- +scikit-learn - 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
+ + +
+ -
+
Live Data Packages
+ +-
+
- +twython - Python wrapper for the Twitter API +
+ -
+
Visualization Packages
+ +-
+
- +matplotlib - well-integrated with analysis and data manipulation packages like numpy and pandas +
- +Orange - Open source data visualization and analysis for novice and experts. Data mining through visual programming or Python scripting. Components for machine learning. Add-ons for bioinformatics and text mining +
+
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+
-
+iPython Data Science Notebooks
+
+
-
+
- +Data Science in IPython Notebooks (Linear Regression, Logistic Regression, Random Forests, K-Means 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+
+
+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
+ +-
+
- +DataTau - The "Hacker News" of Data Science +
- +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 +
- +Wikipedia - The free encyclopedia +
- The Signal and The Noise - Nate Silver Pop-Sci Data Analysis
$15+
+ - Zipfian Academy's List of Resources +
- A Software Engineer's Guide to Getting Started with Data Science +
- Josh Wills - The Life of a Data Scientist / Video + +
- Data Scientist Interviews Metamarkets + +
- /r/MachineLearning Reddit + +
+ +
+Notation
+ +Non-Open-Source books, courses, and resources are noted with $.
+Contribute
+ +Please Contribute Your Ideas -- this is Open Source!
+ +Please showcase your own specialization & transcript by submitting a markdown file pull request in the /transcripts directory with your name! eg clare-corthell-2014.md
Follow me on Twitter @clarecorthell
+ +Email me at github@clarecorthell.com
+