by Integrity Training | Released February 2019 | ISBN: 300000006A0160

The Introduction to R is a primary course for aspiring data scientists who are currently working with Microsoft Excel, Matlab, Mathematica or SAS for numerical analysis of large sets of data. The course enables the candidates in using more powerful OpenSource environments especially the R programming language. R is a functional programming environment employed by many data analysts and data scientists, easily accessible to non-programmers and naturally extending a skill set that is common to data analysts and data scientists. It's the perfect tool for when the one has a statistical, numerical, or probabilities-based problem based on real data and they've pushed those tools past their limits. This fundamental course covers all the necessary topics required to kick start the candidates in working with R programming language. This introductory course provides a complete coverage of the fundamentals of R programming language, including its uses, benefits and applications. The students who enroll in this course will move one step closer to become accomplished data scientists. The course covers the umbrella of technologies that are on the leading edge of data science development focused on R and related tools. Show and hide more

1. Chapter 01 - Introduction to R
   • Topic A: About R - Part 1 00:01:43
   • About R - Part 2 00:13:24
   • About R - Part 3 00:00:58
   • Topic B: RStudio - Part 1 00:00:26
   • RStudio - Part 2 00:10:15
   • RStudio - Part 3 00:00:32
   • Topic C: Workspaces - Part 1 00:00:32
   • Workspaces - Part 2 00:11:43
   • Workspaces - Part 3 00:00:34
   • Topic D: Basic Types - Part 1 00:00:29
   • Basic Types - Part 2 00:13:22
   • Basic Types - Part 3 00:00:45
2. Chapter 02 - Variables
   • Topic A: Basic Types Demo - Part 1 00:00:24
   • Basic Types Demo - Part 2 00:17:24
   • Basic Types Demo - Part 3 00:00:46
   • Topic B: Dates Demo - Part 1 00:00:30
   • Dates Demo - Part 2 00:17:11
   • Dates Demo - Part 3 00:00:37
   • Topic C: Variables - Part 1 00:00:31
   • Variables - Part 2 00:09:55
   • Variables - Part 3 00:00:30
   • Topic D: Missing Values - Part 1 00:00:35
   • Missing Values - Part 2 00:11:24
   • Missing Values - Part 3 00:00:36
3. Chapter 03 - Data Structures and Operators
   • Topic A: Vectors - Part 1 00:00:32
   • Vectors - Part 2 00:20:01
   • Vectors - Part 3 00:00:43
   • Topic B: Matrices - Part 1 00:00:32
   • Matrices - Part 2A 00:16:22
   • Matrices - Part 2B 00:04:19
   • Matrices - Part 3 00:00:42
   • Topic C: Arrays - Part 1 00:00:32
   • Arrays - Part 2 00:08:15
   • Arrays - Part 3 00:00:27
   • Topic D: Lists and Factors - Part 1 00:00:32
   • Lists and Factors - Part 2 00:17:03
   • Lists and Factors - Part 3 00:00:46
   • Topic E: Arithmetic and Relational Operators - Part 1 00:00:30
   • Arithmetic and Relational Operators - Part 2 00:16:46
   • Arithmetic and Relational Operators - Part 3 00:00:44
   • Topic F: Logical and Assignment Operators - Part 1 00:00:26
   • Logical and Assignment Operators - Part 2 00:09:43
   • Logical and Assignment Operators - Part 3 00:00:54
4. Chapter 04 - Data Frames and Tables
   • Topic A: Data Frames - Part 1 00:00:39
   • Data Frames - Part 2 00:09:33
   • Data Frames - Part 3 00:00:37
   • Topic B: Working with Data Frames - Part 1 00:00:26
   • Working with Data Frames - Part 2A 00:14:28
   • Working with Data Frames - Part 2B 00:14:59
   • Working with Data Frames - Part 3 00:00:42
   • Topic C: Data Tables - Part 1 00:00:42
   • Data Tables - Part 2 00:13:53
   • Data Tables - Part 3 00:00:42
   • Topic D: Working with Data Tables - Part 1 00:00:32
   • Working with Data Tables - Part 2 00:17:53
   • Working with Data Tables - Part 3 00:00:49
   • Topic E: Shortcuts - Part 1 00:00:30
   • Shortcuts - Part 2A 00:14:53
   • Shortcuts - Part 2B 00:07:10
   • Shortcuts - Part 3 00:01:16
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