The Comprehensive Programming in R Course

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Torrent File Content (114 files)

The Comprehensive Programming in R Course
07 Details About Dataframe Data Structures
004 A Salary Survey Extended Example.mp4 -

132.92 MB

01 Introduction and Overview of R
002 Introduction and Getting Started.mp4 -

85.35 MB

003 Getting Started and First R Session.mp4 -

75.25 MB

004 First R Session part 2.mp4 -

65.52 MB

005 First R Session part 3.mp4 -

67.85 MB

006 Matrices, Lists and Dataframes.mp4 -

74.84 MB

007 Introduction to Functions.mp4 -

74.66 MB

008 Functions and Default Arguments.mp4 -

73.42 MB

009 More Examples of Functions part 1.mp4 -

71.84 MB

010 More Functions Examples part 2.mp4 -

73.99 MB

011 More Functions Examples part 3.mp4 -

46.54 MB

012 More Functions Examples part 4.mp4 -

59.76 MB

013 More Functions Examples part 5.mp4 -

47.08 MB

014 More Functions Examples part 6.mp4 -

31.48 MB

02 What are Vector Data Structures in R
001 Homemade t-test Exercise Solution.mp4 -

74.76 MB

002 Section 2 Exercise and Package Demonstrations.mp4 -

95.38 MB

003 Begin Discussion of Vectors.mp4 -

94.51 MB

004 More Examples of Vectors.mp4 -

82.6 MB

005 Common Vector Operations and More.mp4 -

103.12 MB

006 Findruns Example and Vectors Exercises.mp4 -

104.85 MB

03 More Discussion of Vector Data Structures
001 Vector-Based Programming Exercise Solution part 1.mp4 -

68.15 MB

002 Vector Exercise Solution part 2 and Begin General Vector Discussion.mp4 -

98.1 MB

003 Continue General Vector Discussion.mp4 -

112.04 MB

004 More General Vector Examples.mp4 -

75.28 MB

005 More on Vectors and Vector Equality.mp4 -

109.77 MB

006 Extended Vector Example and Exercise.mp4 -

99.26 MB

04 Finish Vectors and Begin Matrices
001 Finish Vector Discussion.mp4 -

101.17 MB

002 Vector-Maker Exercise Solutions.mp4 -

105.66 MB

003 Begin Discussion of Matrices and Arrays.mp4 -

86.21 MB

004 Filtering Matrices and More Examples.mp4 -

109.16 MB

005 Still More Matrices Examples.mp4 -

124.5 MB

05 Finish Matrices and Begin Lists Discussion
001 Min-Merge Vector Exercise Solutions.mp4 -

89.45 MB

002 Game of Craps Exercise Solution.mp4 -

54.61 MB

003 Naming Matrix Rows and Columns.mp4 -

95.41 MB

004 Lists General List Operations.mp4 -

70.79 MB

005 Processing Text with Lists.mp4 -

101.81 MB

006 Applying Functions to Lists.mp4 -

123.22 MB

007 Vector and Matrix Exercise.mp4 -

41.28 MB

06 Continue Lists Discussion
001 Review Programming Exercises.mp4 -

101.85 MB

002 Finish Programming Exercise Review and Begin Discussing Lists.mp4 -

94.57 MB

003 List Data Structures General Discussion part 2.mp4 -

113.86 MB

004 List Data Structures General Discussion part 3.mp4 -

117.58 MB

005 Lists Data Structures General Discussion part 4.mp4 -

123.61 MB

07 Details About Dataframe Data Structures
001 Dataframe-Maker Exercise.mp4 -

72.03 MB

002 List-Maker Exercise Begin General Dataframe Discussion.mp4 -

96.72 MB

003 Extracting Subdata Frames.mp4 -

103.32 MB

01 Introduction and Overview of R
001 Introduction to Comprehensive R Programming Course.mp4 -

8.86 MB

07 Details About Dataframe Data Structures
005 Merging Dataframes.mp4 -

101.23 MB

006 End Dataframes Discussion Matrix Exercise.mp4 -

123.2 MB

08 More Matrix and List Examples
001 Covariance Matrix Exercise Solution.mp4 -

59 MB

Description

Miscellaneous
     Course
Description
The Comprehensive Programming in R Course is actually a combination of two
R programming courses that together comprise a gentle, yet thorough introduction to the practice of general-purpose
application development in the R environment. The original first course (Sections 1-8) consists of approximately 12
hours of video content and provides extensive example-based instruction on details for programming R data structures.
The original second course (Sections 9-14), an additional 12 hours of video content, provides a comprehensive overview
on the most important conceptual topics for writing efficient programs to execute in the unique R environment.
Participants in this comprehensive course may already be skilled programmers (in other languages) or they may be
complete novices to R programming or to programming in general, but their common objective is to write R applications
for diverse domains and purposes. No statistical knowledge is necessary. These two courses, combined into one course
here on Udemy, together comprise a thorough introduction to using the R environment and language for general-purpose
application development.

The Comprehensive Programming in R Course (Sections 1-8) presents an detailed,
in-depth overview of the R programming environment and of the nature and programming implications of basic R objects in
the form of vectors, matrices, dataframes and lists. The Comprehensive Programming in R Course (Sections 9-14) then
applies this understanding of these basic R object structures to instruct with respect to programming the structures;
performing mathematical modeling and simulations; the specifics of object-oriented programming in R; input and output;
string manipulation; and performance enhancement for computation speed and to optimize computer memory resources.

What are the requirements?
Students will need to install the no-cost R console and the no-cost RStudio
application (instructions are provided).
What am I going to get from this course?
Acquire the skills needed to
successfully develop general-purpose programming applications in the R environment
Possess an in-depth
understanding of the R programming environment and of the requirements for, and programming implications of, writing
code using basic R objects: vectors, matrices, dataframes and lists.
Understand the object-oriented characteristics
of programming in R and know how to create S3 and S4 Class objects and functions that process these S3 and S4
objects.
Know how to program mathematical functions, models and simulations in R.
Know how to write R programs
that effectively use and manipulate text and string variable objects.
Know how to use the scan(), readline(),
cat(), print() and readLines() functions in R for efficient data input and output and for effective user-prompting.
Know how to 'tweak' R programs for maximum performance efficiency.
What is the target audience?
Anyone
interested in writing computer applications that execute in the R environment.
The common objective of students is
common objective is to write R applications for diverse domains and purposes.
Students may already be skilled
programmers (in other languages) or they may be complete novices to R programming or to programming in general,
Undergraduate or graduate students looking to acquire marketable job skills prior to graduation.
Analytics
professionals looking to acquire additional job skills.                                                            Show Demonoid some love
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The Comprehensive Programming in R Course

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