• The R boot camp assumes you already have at least an intermediate understanding of R and statistics.  

• Coding –For the basic boot camp (the first 4 weeks), you need to have basic programming skills and have used R at a basic level, perhaps in an entry level MOOC or similar course.   Self-study is fine.   For the second 4-week module you need an intermediate knowledge of R, know at least one programming environment, know the different data types and be able to write moderately complex programs.  You don’t need to be an expert at the language. 

• Problem Solving – You should have some problem solving experience.  This could be via PDCA, Six Sigma, Lean, TOC, or any other problem solving methodology.  Learned via work experience is fine.

• Linear algebra – You should have taken a high school algebra course or first year college algebra course and remember it and can manipulate linear equations.

• Statistics -  For the first module you need an equivalent knowledge of a high school level stats course covering descriptive stats.  For module 2 you need at least a university level course that covers basic Anova, basic display methods, and hypothesis testing. The more the better.  Can be self-learned or learned on the job.

• Data Analysis – For the first four week session you should be comfortable around data and have some experience manipulating it, cleaning and organizing it.  For the second four week session you should have some knowledge of regression, data mining, cluster analysis, cleaned a data set, know how to impute missing values. Don't need to be an expert at these but we'll assume you know the terms and what they are used for.

• Business analysis -  You need some experience with economic and risk analysis and business decision making.