Data Analytics Using R Programming

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Tambaram East, Chennai

Course ID: 43206

Tambaram East, Chennai

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About Shan Murali

I have over 17 years of experience in Teaching, Training, Research and Consultancy work. Expertised in Statistical Data Analysis, Research Methodology, Research Guidance, Thesis Support and Paper Writing.
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About the Course

InnovGene Solutions provides course of Data Analytics Using R-Language for fresh graduates, employees looking for career change, IT professional to upgrade their skills in Data analytics. The course is fully customized based on the need of the candidate. A detailed introduction to statistics will be provided. 


COURSE SYLLABUS


Module 1: Intro To Data Analysis


Topics: Basic Programming, Analytics, Plotting, and Data Handling


Module 2: Introduction To R


Topics: What is R?, Need for R, R user Interfaces, Oracleâ??s Strategy for R, Working with Data in R


Module 3: Introduction To ORE


Topics: Starting R and Loading ORE, Prerequisites for using ORE, Basic Database Interaction with ORE


Module 4: Installing Packages


Topics: Finding and Installing Resources, Visualization with R


Module 5: Data Structures, Variables


Topics: Data Types, Sub Setting, Data Structures, Assignment, Variables, Indexing, Viewing Summaries and Data, Objects, Naming Conventions, Reading Data from Structured Text Files, Built-In Data, Reading Data using ODBC


Module 6: Data Handling


Topics: Importing or Exporting Data to Multiple Formats, Date and Date-Time Classes in R, Handling Data Frames, PLYR Package for Easy Data Manipulation, Formatting Dates for Modeling


Module 7: Control Flow


Topics: Truth Testing, Looping, Vectorized Calculations, Branching, Functions in Depth, Descriptive Statistics, Inferential Statistics, Group by Calculations,


Module 8: Functions


Topics: Writing user Defined Functions, Installing Packages, the â??Applyâ?? Family of Functions, Commonly used Built in Functions, Basic Visualization, Looping Functions


Module 9: Graphics


Topics: Base Graphics System in R, Exporting Graphics to Different Formats, Advanced R Graphics, Dot Plots, Bar Charts, Scatterplots, Histograms, and Whiskers, Learning the Grammar of Graphics, Quick Plot Function, Graphics for Exploratory Data Analysis, Building Graphics by Pieces, Standard Graphic Displays, Axes, Labels, Titles, Legends


Module 10: Statistical Analysis With R


Topics: Linear Models, Advanced Statistical Modeling with R, Survival Analysis, Density Estimation, Classification, Clustering, Generalized Linear Models


Module 11: Regression


Topics: Logistic, Gamma and Poisson Regression, Covariance Structures, Interpreting Random Effects in Models, Random Effects Introduction, Clustered Data, Prediction in Random Effects, Longitudinal Data, Covariance Structures, Marginal Versus Conditional Models


Module 12: Advanced Missing Data Techniques


Topics: Implications for Analysis, Multiple Imputation, AMELIA Package, Study of Different Types of Missing Data.

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