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Learning to program in R

MartinOvie

MartinOvie

C++ Certificate
Joined
11/12/15
Messages
84
Points
128
Hi all,

I'm very much interested in learning to program in R for big data analytics but I need some help on how to proceed. A colleague mentioned Coursera, and after some searching, I found the following programs:
  1. Coursera - Free Online Courses From Top Universities - Caltech-JPL Summer School on big data analytics. This isn't a course per se; only the material is provided but it covers Markov chain Monte Carlo (MCMC), Statistical resampling and inference, databases, data visualization, clustering and classification, decision trees and random forests, and dimensionality reduction.
  2. Coursera - Free Online Courses From Top Universities - John Hopkins. This series of 8 courses (intro excluded) and a Data Science Capstone project is offered monthly. It includes R Programming, getting and cleaning data, exploratory data analysis, reproducible research, statistical inference, regression models, practical machine learning, developing data products, and the data science capstone project in which students will create a usable/public data product drawn from real-world problems.
  3. Coursera - Free Online Courses From Top Universities - UC San Diego. This is another series which is offered quite frequently. It is composed of 5 courses: intro to big data, Hadoop platform and application framework, intro to big data analytics, machine learning with big data, graph analytics for big data, and big data capstone project. Their industry partner is Splunk (Operational Intelligence, Log Management, Application Management, Enterprise Security and Compliance | Splunk).

At the moment, I am leaning more towards UC San Diego because it appears to cover more material (see course syllabi), but I am open to thoughts and opinions. Are there other programs I should look into, any books? I currently have
  • Time series analysis and its applications by R. Shumway and D. Stoffer
  • Introductory R by R. Knell
  • The art of R programming by N. Matloff.

Any thoughts, ideas or pointers will be much appreciated.
Thanks.
@APalley @Pavlos Sakoglou
 
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