My name is John Horn and I am passionate about using data to better the world. My professional interests include Machine Learning, Data Mining, Automation, Spatial Modeling, Interactive Data Visualization, and Statistical Models.

Below are classes I have completed as well as books that have been very influential. In Bold are the resources I would highly recommend.


’15 Johns Hopkins Data Science Coursera, Exploratory Data Analysis
’14 Johns Hopkins Data Science Coursera, Getting and Cleaning Data

’14 Johns Hopkins Data Science Coursera, R Programming
’14 Johns Hopkins Data Science Coursera, The Data Scientist’s Toolbox
’14 Intro to Hadoop and MapReduce, Cloudera / Udacity
’12 UCI, Geoscience Modeling and Data Analysis ESS 212
’11 Stanford, Fundamentals of Modeling EESS 211

’11 Stanford, Advanced Statistical Methods for Earth System Analysis EESS 260
’11 Stanford, Introduction to Probability and Statistics for Engineers CME 106


Introductory Time Series with R, Cowpertwait and Metcalfe, 978-0-387-88697-8
Applied Predictive Modeling, Kuhn and Johnson, ISBN-13: 978-1461468486

Python for Data Analysis, Wes Mckinney, 978-1782161417
Programming Collective Intelligence: Building Smart Web 2.0 Applications 
The Art of R Programming, Matloff, ISBN-13: 858-2592222227
The Linux Command Line, Shotts, ISBN-13: 978-1593273897
Learning Python, Lutz, ISBN-13: 978-1449355739
Building Machine Learning Systems with Python, Willi Richert, 1782161406