The Comprehensive Programming in R Course
The Comprehensive Programming in R Course. How to design and develop efficient general-purpose R applications for diverse tasks and domains.
The name of this course is The Comprehensive Programming in R Course. The knowledge you will get with this indescribable online course is astonishing. How to design and develop efficient general-purpose R applications for diverse tasks and domains..
Not only will you be able to deeply internalize the concepts, but also their application in different fields won’t ever be a problem. The instructor is Geoffrey Hubona, Ph.D., one of the very best experts in this field.
Description of this course: The Comprehensive Programming in R Course
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.
Requirements of this course: The Comprehensive Programming in R Course
What are the requirements? Students will need to install the no-cost R console and the no-cost RStudio application (instructions are provided).
What will you learn in this course: The Comprehensive Programming in R Course?
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.
Target audience of this course: The Comprehensive Programming in R Course
Who 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.
Geoffrey Hubona, Ph.D.
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