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R Programming for Data Scientists | In-Depth R

Detailed R programming, data-focused skills covering foundation, vectors, dates, AI / MadLib, Data Visualization, Hadoop and More

GK# 9260

Course Overview

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R is a functional programming environment for business analysts and data scientists. It's a language that many non-programmers can easily work with, naturally extending a skill set that is common to high-end Excel users. It's the perfect tool for when the analyst has a statistical, numerical, or probabilities-based problem based on real data and they've pushed Excel past its limits.

Schedule

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What You'll Learn

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R Programming for Data Scientists & Analysts is a five-day, comprehensive hands-on course that presents common scenarios encountered in analysis and present practical solutions. In this course, special attention is paid to data science theory including AI grouping theory. A discussion of using R with AI libraries like Madlib are included.

Outline

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Virtual Classroom Live Outline

From Excel to R

  • Common problems with Excel
  • The R Environment
  • Hello, R

R Basics

  • Simple Math with R
  • Working with Vectors
  • Functions
  • Comments and Code Structure
  • Using Packages

Vectors

  • Vector Properties
  • Creating, Combining, and
  • Iteratorating
  • Passing and Returning Vectors in Functions
  • Logical Vectors

Reading and Writing

  • Text Manipulation
  • Factors

Dates

  • Working with Dates
  • Date Formats and formatting
  • Time Manipulation and Operations

Multiple Dimensions

  • Adding a second dimension
  • Indices and named rows and columns in a Matrix
  • Matrix calculation
  • n-Dimensional Arrays
  • Data Frames
  • Lists

R in Data Science

  • AI Grouping Theory
  • K-means
  • Linear Regression
  • Logistic Regression
  • Elastic Net

R with MadLib

  • Importing and Exporting static Data (CSV, Excel)
  • Using Libraries with CRAN
  • K-means with Madlib
  • Regression with Madlib
  • Other libraries

Data Visualization

  • Powerful Data Through Visualization: Communicating the Message
  • Techniques in Data Visualization
  • Data Visualization Tools
  • Examples

R with Hadoop

  • Overview of Hadoop
  • Overview of Distributed Databases
  • Overview of Pig
  • Overview of Mahout
  • Exploiting Hadoop clusters with R
  • Hadoop, Mahout, and R

Business Rule Systems

  • Rule Systems in the Enterprise
  • Enterprise Service Busses
  • Drools
  • Using R with Drools

Labs

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Virtual Classroom Live Labs

This “skills-centric” course is about 50% hands-on lab and 50% lecture, designed to train attendees in core R programming and data analytics skills, coupling the most current, effective techniques with the soundest industry practices. Throughout the course students will be led through a series of progressively advanced topics, where each topic consists of lecture, group discussion, comprehensive hands-on lab exercises, and lab review.

Prerequisites

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Students should have attended the course(s) below, or should have basic skills in these areas:

  • Introduction to SQL
  • Working with Excel

Who Should Attend

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This is an intermediate and beyond level course, geared for experienced Data Analyst and Data Scientists who need to learn the details beyond the essentials of how to program in R. Incoming students should have prior data analytics background, and should have experience working with Excel and should know the basics of SQL.

Course Delivery

This course is available in the following formats:

Virtual Classroom Live

Experience expert-led online training from the convenience of your home, office or anywhere with an internet connection.

Duration: 3 day

Request this course in a different delivery format.
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