Understanding vectors in R

Reading Data, Combining Data

Subsetting data

Sorting data and some basic data generation functions

Machine Learning Overview

ML Common Use Cases

Understanding Supervised and Unsupervised Learning

Techniques, Clustering

Similarity Metrics

Distance Measure Types: Euclidean, Cosine Measures, Creating predictive models

Understanding K-Means Clustering

Understanding TF-IDF and Cosine Similarity and their application to Vector Space Model

Implementing Association rule mining in R

Understanding Process flow of Supervised Learning Techniques

Decision Tree Classifier

How to build Decision trees

Random Forest Classifier

What is Random Forests

Features of Random Forest

Out of Box Error Estimate and Variable Importance

Naive Bayes Classifier

Hadoop Architecture

Common Hadoop commands

MapReduce and Data loading techniques (Directly in R and in Hadoop using SQOOP, FLUME, and other Data Loading Techniques)

Removing anomalies from the data

Integrating R with Hadoop using RHadoop and RMR package

Exploring RHIPE (R Hadoop Integrated Programming Environment)

Writing MapReduce Jobs in R and executing them on Hadoop

Implementing Machine Learning Algorithms on larger Data Sets with Apache Mahout

Implementation of different Mahout algorithms

Random Forest Classifier with parallel processing Library in R