Table of Contents
This course is designed as the advanced level course of Statistical Computing (under graduate level). You will learn various topics like statistical parallel computing, techniques for big data analysis, text basic mining tools, statistical vitalization tools, developing your own packages.
- Basic knowledge of statistical programming
- Basic knowledge of R
Part I: Efficient statistical programming
- Loops and vectorization
- Parallel Concepts
- Optimization | Matrix Derivatives
- R Graphics
Part II: Statistical programming for big data
- Big Data with Linear Models
- Big Data with bigmemory
- Logistic Regression with GPU
- Big Data Visualization Tools | R code
Part III: Special topics
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