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R Programming

  • Course Code: Programming - R
  • Course Dates: Contact us to schedule.
  • Course Category: Programming and Development Duration: 6 Days Audience: This course is geared for those who wants a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods

Course Snapshot 

  • Duration: 6 days 
  • Skill-level: Foundation-level programming skills for Intermediate skilled team members. This is not a basic class. 
  • Targeted Audience: This course is geared for those who wants a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods 
  • Hands-on Learning: This course is approximately 50% hands-on lab to 50% lecture ratio, combining engaging lecture, demos, group activities and discussions with machine-based student labs and exercises. Student machines are required. 
  • Delivery Format: This course is available for onsite private classroom presentation. 
  • Customizable: This course may be tailored to target your specific training skills objectives, tools of choice and learning goals. 

R teaches you how to use the R language by presenting examples relevant to scientific, technical, and business developers. Focusing on practical solutions, the course offers a crash course in statistics, including elegant methods for dealing with messy and incomplete data. You’ll also master R’s extensive graphical capabilities for exploring and presenting data visually. And this expanded includes new lessons on forecasting, data mining, and dynamic report writing. 

Working in a hands-on learning environment, led by our R expert instructor, students will learn about and explore: 

Focusing on practical solutions, offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods.  

You’ll also master R’s extensive graphical capabilities for exploring and presenting data visually.  

this expanded edition includes new lessons on time series analysis, cluster analysis, and classification methodologies, including decision trees, random forests, and support vector machines. 

Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below 

  • Complete R language tutorial 
  • Using R to manage, analyze, and visualize data 
  • Techniques for debugging programs and creating packages 
  • OOP in R 
  • Over 160 graphs 

Audience & Pre-Requisites 

This course is designed for readers who need to solve practical data analysis problems using the R language and tools. 

Pre-Requisites:  Students should have  

  • Basic to Intermediate IT Skills.  
  • Some background in mathematics and statistics is helpful 
  • no prior experience with R or computer programming is required. 

Course Agenda / Topics 

  1. Introduction to Rfree audio 
  1. Creating a dataset 
  1. Getting started with graphs 
  1. Basic data management 
  1. Advanced data management 
  1. Basic graphs 
  1. Basic statistics 
  1. Regression 
  1. Analysis of variance 
  1. Power analysis 
  1. Intermediate graphsfree audio 
  1. Resampling statistics and bootstrapping 
  1. Generalized linear models 
  1. Principal components and factor analysis 
  1. Time series 
  1. Cluster analysis 
  1. Classification 
  1. Advanced methods for missing data 
  1. Advanced graphics with ggplot2 
  1. Advanced programming 
  1. Creating a package 
  1. Creating dynamic reports 
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