Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Language
English
Taught by
Geoffrey Hubona, Ph.D.
Rating
4 views
Course Overview
How to design and develop efficient general-purpose R applications for diverse tasks and domains.
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.
Course Content
- 10 section(s)
- 120 lecture(s)
- Section 1 Introduction and Overview of R
- Section 2 What are Vector Data Structures in R ?
- Section 3 More Discussion of Vector Data Structures
- Section 4 Finish Vectors and Begin Matrices
- Section 5 Finish Matrices and Begin Lists Discussion
- Section 6 Continue Lists Discussion
- Section 7 Details About Dataframe Data Structures
- Section 8 More Matrix and List Examples
- Section 9 Programming in R Environments
- Section 10 Performing Math and Simulations
What You’ll Learn
- 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.
Reviews
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MMatej Buršík
Great well rounded course for comprehensive understanding of R. My only issues is that occasionally, the video ended in the middle of the sentence and the exercises where relatively easy compared to some of the material presented in the videos.
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FFabian S.
A good introduction to the real programming aspects of the R language. This course even teaches programming classes, which is very rarely found in other R courses, but important. Sometimes, the course feels a bit boring and a little bit redundant at some points, but the overall gain of the course is great and fulfills the desire to get into the programming of R and not just calling library functions to data frames. Based on this introduction a deeper dive into programming R is possible.
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CCharles Knell
As someone who has been training in and using R for several years, some of this material was familiar, but there were enough "in the weeds" topics of which I was vaguely aware to keep me interested and learning useful things. Geoffrey's presentation and preparation could use some work, but this was only a minor distraction.
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RRodrigo Garcia
Halfway through and still pretty good. It is explained with great detail, although it could use some more real-life examples
