Commiting my initial planned OSDSM curriculum

transcripts/nick-byrne-transcript.md

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 <h1>Nick Byrne Transcript</h1>
 **Open Source Data Science Masters**
 
-This is here to facilitate an initial pull request
+Want to collaborate? Get in touch: 
+ * [twitter](http://www.twitter.com/byrnenick)); or 
+ * [email](mailto:[email protected])
 
-Want to collaborate? Get in touch: [twitter](http://www.twitter.com/byrnenick)) or [email](mailto:[email protected])
+**OpenSource Data Science Masters Curriculum**
+Below is a planned curriculum that I'm looking to follow. As with life, I'm not expecting it to be followed linearly necessarily. And I may swap courses in and out as interesting things arise. 
+I do plan to take at least one element from all of the recommended themes published in the OpenSource Data Science masters. And I'm favouring online courses as it's obviously easier to stay honest with regards to progress over reading a book and claiming that you know the subject matter.
+
+<h2>Recognised openSource curriculum</h2>
+<h3>Base Introduction</h3>
+Data Science Introductions
+ - [ ] Intro to Data Science by UW / Coursera, online course
+ - [ ] Data Science by Harvard, online course
+ - [ ] Data Science with Open Source Tools, book
+ - [ ] Introduction to Computer Science and Programming, by MIT OpenCourseWare
+*Intro to CS was listed in Python(Learning) section but felt it would be a good one to bring up front (despite having a good grasp of python)
+
+Mathematics
+ - [ ] Linear Programming (Math 407) University of Washington
+ - [ ] Statistics by Princeton & Coursera
+ - [ ] Differential Equations in Data Science, Python tutorial
+ - [ ] Problem-Solving Heuristics "How to Solve It" by Polya, Book
+
+<h3>Computing</h3>
+Algorithms
+ - [ ] Algorithms Design & Analysis, by Stanford and Coursera
+
+Distributed Computing Paradigms
+ - [ ] Intro to Hadoop and MapReduce by Cloudera and Udacity 
+*Note: I might swap the above course with an EdX course on Apache Spark and distributed computing*
+
+Databases
+ - [ ] Introduction to Databases, by Stanford
+
+Data Mining
+ - [ ] Mining Massive Data Sets, by Stanford and Coursera
+
+Machine Learning - Foundational & Theoretical
+ - [ ] Machine Learning, by Ng Stanford and Coursera (**in-progress**)
+ - [ ] The Elements of Statistical Learning, by Stanford 
+
+Machine Learning - Practical
+ - [ ] Programming Collective Intelligence
+ - [ ] Intro to scikit-learn, by SciPy2013
+
+Probabilistic Modeling
+ - [ ] Probabilistic Graphical Models, by Stanford and Coursera
+
+Deep Learning (Neural Networks)
+ - [ ] Neural Networks, by Univesity of Toronto and Coursera
+
+Natural Language Processing
+ - [ ] From Languages to Information, by Stanford
+ - [ ] NLP with Python (NLKT library)
+
+Analysis
+ - [ ] Big Data Analysis with Twitter, by UC Berkeley
+
+<h3>Data Design</h3>
+*To be confirmed*
+
+
+<h3>Relevant prior studies</h3>
+ - [X] Adelaide University, Mathematics 1011
+ - [X] Adelaide University, Statistics 1001
+ - [X] Adelaide University, Engineering Modelling and Analysis 1003
+ - [X] Adelaide University, Mathematics 1012
+ - [X] Adelaide University, Differential Equations and Statistical Methods 2010
+ - [X] Adelaide University, Engineering Modelling and Analysis 2010
+ - [X] Adelaide University, Engineering Modelling and Analysis 3009
+ - [X] Adelaide University, Environmental Modelling, Management and Design 4987
+
+
+**OpenSource Data Science Masters Capstone Project**
+I would like to do a capstone project focused on using big data to understand workplace dynamics, and more appropriate hiring decisions. E.g. can we use big data to better understand an employees cultural fit? 
+As I progress through the curriculum, I'll better define the capstone project.
+
+If you'd like to pair up for the capstone, [let me know](http://www.twitter.com/byrnenick))