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Introduction to R

Part Of The On-Demand Courses

WHAT YOU'LL LEARN

  • How to write queries that involve multiple tables and summary queries
  • How to modify data and understand the logical programming aspects of T-SQL
This course includes:
  • Course Description
  • Outline
  • Instructor
  • System Requirements
  • What to Know Before Class

Course Description

During this R programming virtual training course, you will learn how to use R for data analysis. We’ll start with a discussion of the R language and how to install the R language interpreter and RStudio, the popular R integrated development environment. You’ll learn how R can be extended with modules, called packages, and discuss some of the popular packages in use. We’ll delve into the unique features of R that make it so suitable for data science. The core R data structures; vectors, matrices, arrays, and data frames, will be discussed with examples. Before moving into predictive modeling, we’ll do a quick overview of key concepts in statistics. From there we will walk through the training, testing, and evaluation of a predictive model. Since many people will be using data from relational databases, we will explain how to use the RODBC package to read in data using a SQL Server table as an example. The course wraps up by discussing related topics such as scaling R programs, creating R based web applications, and creating dynamic presentations with R Markdown.

 

Click here for a downloadable PDF

Outline

 

Module 01 | Getting Started with R
10m 23s total

 

Module 01A | Getting Started with R
10m 23s

 

Module 02 | An Introduction to RStudio
22m 53s total

 

Module 02A | An Introduction to RStudio
22m 53s

 

Module 03 | Extending R with Packages
33m 31s total

 

Module 03A | Extending R with Packages
33m 31s

 

Module 04 | Vector Fundamentals
42m 10s total

 

Module 04A | Understanding Vectors
20m 08s

 

Module 04B | Leveraging Vectors
22m 02s

 

Module 05 | Matrices Fundamentals
23m 36s total

 

Module 05A | Matrices Fundamentals
23m 36s

 

Module 06 | Array Fundamentals
20m 55s total

 

Module 06A | Array Fundamentals
20m 55s

 

Module 07 | List Fundamentals
33m 32s total

 

Module 07A | List Fundamentals
33m 32s

 

Module 08 | Using Data Frames
33m 01s total

 

Module 08A | Using Data Frames
33m 01s

 

Module 09 | Statistics
41m 28s total

 

Module 09A | What you need to know
41m 28s

 

Module 10 | Data Quality and Missing Data
22m 59s total

 

Module 10A | Data Quality and Missing Data
22m 59s

 

Module 11 | Evaluating Data Relationships
21m 25s total

 

Module 11A | Evaluating Data Relationships
21m 25s

 

Module 12 | Overview of Data Science
18m 06s total

 

Module 12A | Overview of Data Science
18m 06s

 

Module 13 | Creating a Predictive Model
33m 07s total

 

Module 13A | Creating a Predictive Model
33m 07s

 

Module 14 | Comparing Models
16m 49s total

 

Module 14A | Comparing Models
16m 49s

 

Module 15 | Choosing a Predictive Model
13m 54s total

 

Module 15A | Choosing a Predictive Model
13m 54s

 

Module 16 | More On File Formats
40m 58s total

 

Module 16A | More On File Formats
40m 58s

 

Module 17 | Reading Data from Relational Databases
28m 34s total

 

Module 17A | Reading Data from Relational Databases
28m 34s

 

Module 18 | More Topics on R
35m 06s total

 

Module 18A | More Topics on R
35m 06s

 

Module 19 | Wrapping Up
19m 52s total

 

Module 19A | Wrapping Up
19m 52s

Instructor

BRYAN CAFFERKY

BI Consultant and Trainer
Bryan Cafferky is a Microsoft Technical Solutions Professional focused on helping customers understand and implement Data Analysis, Machine Learning, and AI solutions in the health care industry. He is a Microsoft 2017 Data Platform MVP and a 2016 Cloud and Data Center Management MVP. Bryan is the author of Pro PowerShell for Database Developers by Apress, available on Amazon. He leads The RI Microsoft BI User Group, and The Greater Boston Area Data Science, Machine Learning, and AI Group. He has been working with the SQL Server stack since 1997 and implemented projects in the banking, insurance, e-commerce, utility, and health care industries. He holds a bachelor of science in computer information systems and a Master’s degree in Business Administration.

System Requirements

  • Windows 7, Windows 8, or Windows 10
  • 1 GHz or faster CPU
  • 1 GB of available RAM (recommended 2 GB)
  • 20 GB of free hard drive space
  • R Language and Console – https://cran.r-project.org/
  • RStudio – <ahref=”https://www.rstudio.com/products/rstudio/download/”>https://www.rstudio.com/products/rstudio/download/

What to Know Before Class

A basic understanding of data structures would be helpful but not required.

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