[Transcript] Clare Corthell

The Open-Sourced Masters

I didn't want to wait to go back to grad school - so I designed my own. DIY loves the Internet!

My Background / linkedin

I'm a Stanford-educated Engineer (and Linguist), previously a Front-End Developer and UX Designer on early-stage products. I'm always hacking in hot pursuit of deeper insight to social questions!

Goals & Motivations of the Open Source M.S.

Data Science is an ideal place to marry my technical capacities, social research inquisitions, and my geekish-freakish love of statistics.

Next Steps?

I spent April to August 2013 on this curriculum - now I'm itching to work with other people!

• The right team is where
• I can invest in industry best practices,
• Work with intractably large data sets, and
• Hack on interesting social networking questions.

Are you my team? --> her (at) clarecorthell.com

The Data Science Curriculum / April-August 2013

• Introduction to Data Science UW / Coursera

Math

• Linear Algebra / Levandosky / Book

Computing

• Algorithms

• Algorithms Design & Analysis I / Stanford / Coursera

• Databases

• Introduction to Databases / Stanford / Coursera

  • Selected Topics:

• Data Mining

• Mining Massive Data Sets / Stanford / Book

• Selected Topics: Support Vector Machines,

• Mining Social Networks O'Reilly / Book

• Distributed Computing Paradigms

• MapReduce/Hadoop

• Machine Learning

• Stanford / Coursera

• Programming Collective Intelligence O'Reilly / Book

• Natural Language for ML / link

• Probabilistic Graphical Models

• Stanford / Coursera

• Selected Topics: Bayesian Network Fundamentals, Markov Networks, Inference, MAP Estimation, Decision Making, Structured Learning

• Probabilistic Programming and Bayesian Methods for Hackers / Github / Tutorials

Analysis

• Big Data Analysis with Twitter UC Berkeley / Lectures

• Social and Economic Networks: Models and Analysis / Stanford / Coursera

• Python (Language & Learning)

• Python for Data Analysis O'Reilly / Book

• New To Python: Learn Python the Hard Way, Google's Python Class

• Python (Libraries)

• Basic Packages Python, virtualenv, NumPy, SciPy, matplotlib and IPython

• Bayesian Inference | pymc

• Labeled data structures objects, statistical functions, etc pandas (See: Python for Data Analysis)

• Python wrapper for the Twitter API [twython]](https://github.com/ryanmcgrath/twython)

• Tools for Data Mining & Analysis scikit-learn

• Network Modeling & Viz networkx

Projects

• uw
• capstone

---

I "Forked" this into the Open Source Data Science Masters Curriculum.

Follow me on Twitter @clarecorthell