R Programming Beginner - Training Course
Learn the basic concepts of R programming for data analysis
- R
- R syntax
- data types and objects
R Programming Beginner - Training Course
Learn the basic principles of R programming, the language for statistical and data analysis.
We don't have courses scheduled in your city currently. Please see our remote course options or contact us to register your interest.
We don't have courses scheduled in your city currently. Please see our remote course options or contact us to register your interest.
We don't have courses scheduled in your city currently. Please see our remote course options or contact us to register your interest.
We don't have courses scheduled in your city currently. Please see our remote course options or contact us to register your interest.
We don't have courses scheduled in your city currently. Please see our remote course options or contact us to register your interest.
We don't have courses scheduled in your city currently. Please see our remote course options or contact us to register your interest.
Frequently Asked Questions
Course Introduction
Our R courses were designed by Tamara Shatar, who holds a PhD in Agricultural Data Science. She focused her extensive experience and skills in modelling using machine learning, simulation and other techniques to create a course with depth and applicability.
The course is consistently well-reviewed by students.
"I found this 1 day course to be packed full of information - a very heavy load but masterfully delivered. It is very clear that we were learning from someone who is extremely capable and experienced with both the software solution AND it's real world application. I liken the experience to taking golf lessons from Tiger Woods or basketball coaching from Michael Jordan. All questions were addressed as if they were always part of the planned course content - seamless. Thank you so much for this opportunity." - R Beginner Sydney Remote
What is R?
R is an open source and free programming language that was developed for statistical analysis and the production of high-quality graphics. It is commonly used by statisticians and academics internationally who make up part of the extensive and active user community behind R. This community has contributed over 15,000 packages that extend the base functionality of R, making it easy to implement a vast range of techniques for data manipulation, analysis, and visualisation.
Why make data-driven decisions?
A range of different industries have adopted R to make sense of their data. From customer segmentation, to demand forecasting, R can be used to improve operations by uncovering patterns within data, using a range of statistical methods, including sophisticated machine-learning techniques.
What is Remote Training?
Remote training at Nexacu means our experienced trainers will deliver your training live online. With remote learning, students can access our usual classroom training courses via video conferencing, ask questions, participate in the discussion, and share their screen with the trainer if they need help at any point. Students have the same level of participation and access to the trainer as they would in classroom training sessions.
R Programming Beginner Course Details
R Programming Beginner Course Details
R Programming Beginner Course Details
R Programming Beginner Course Details
R Programming Beginner Course Details
R Programming Beginner Course Details
R Programming Beginner Course Details
R Programming Beginner Course Details
R Programming Beginner Course Details
R Programming Course Outlines
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What do I need to know to attend?
No specific pre-requisites for the course.
We recommend completing the R Beginner course together with R Intermediate.
R Programming Beginner Learning Outcomes
You will understand and be able to:
- use R data types and objects
- write basic syntax
- create and manipulate objects
- use functions
- create basic data visualisations
R Programming Beginner Course Content
- Introduction
- Introduction to R
- Base R and contributed packages
- Download and installation of base R
- Installing R packages
- The RStudio IDE
- Download and installation
- Overview of the RStudio environment
- The main panes
- Working directory
- Workspace
- Projects
- Create a project
- Using R as a Calculator
- Executing commands from the command line and the source pane
- Arithmetic operators
- Relational operators
- Logical operators
- Creating Objects
- Objects in R
- Assignment operators
- Naming rules
- Basics of R Syntax
- Creating objects
- Viewing objects in RStudio
- Viewing objects in the console
- Data Types and Classes
- Basic data types
- Data structures in R
- Vectors
- Factors
- Matrices
- Arrays
- Lists
- Data frames
- Tibbles
- Which data structure should I use?
- Changing data types
- Implicit coercion
- Explicit coercion
- Naming parts of data objects
- Column names
- Row names
- Dimension names
- Names
- Accessing Data within Data Structures
- Referring to data by position
- Referring to data by name
- Replace parts of an object
- Replace names
- Replace values
- Add to a data object
- Add elements to vectors
- Add rows or columns
- Add by position
- Add by name
- Removing data from a data object
- Remove elements from vectors
- Remove rows or columns from matrices
- Remove rows or columns from data frames and lists
- Evaluation in R
- Vector arithmetic
- Order of operations
- Vector recycling
- Vectorised operations
- Applying functions to elements of data structures
- Using Functions
- What is a function?
- Syntax for using functions in R
- Arguments
- Getting help with a function
- Overview of help documentation in R
- Basic statistical summary functions
- Masking of functions
- Explicitly specifying the package name when calling a function
- Package: conflicted
- Importing Data
- Importing data in RStudio
- Importing data from text files (csv)
- Exporting Data
- Export data to text file
- Basic Data Visualisation
- The plot function
- Add reference lines
- Add text
- Add a legend
- Exporting plots