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R is a programming language designed for statistical data analysis and producing graphical output. Building on the core concepts introduced in our R Beginner course, the R Programming Intermediate course focuses on practical skills in data manipulation, exploratory data analysis, customised data visualisations, and basic modelling techniques.
Guided by an experienced Data Analyst, you’ll work through hands-on exercises to strengthen your R coding skills and apply a range of functions to real-world datasets.
By the end of this course, participants will be able to:
You should have completed the R Beginner course and be familiar with basic R syntax, data types, subsetting data, and using contributed packages. Basic experience with RStudio is also helpful.
Select your country to view prices, and course dates.
R BeginnerLearn the basic principles of R programming, the language for statistical and data analysis.
R AdvancedBuild on your base knowledge of the R language and learn how to run data analysis more efficiently.
Machine Learning in RLearn the basic processes of machine learning using R programming. Led by an experienced data scientist.
Introduction
Review of R data types and structures
Review of common syntax for accessing data in data frames
Importing Data
Importing data in RStudio
Packages and functions to import data into R
Using code to import data
Importing data from text files (csv)
Importing data from Excel
Workflow in R
Creating reusable scripts
Manipulating Data
The tidyverse
Summarising data
Ordering data
Working with dates
Convert character to date
Extract years from dates
Extract months from dates
Extract days from dates
Manipulating Data (cont’d)
Extract days of the week from dates
Add columns to a data frame
Working with strings
Selecting and reordering columns in a data frame
Selecting rows based on values
Grouping data
Summarising data
Manipulating Data (cont’d)
Identifying blank values and non-number numbers
Working with data that contains missing values and non-number numbers
Removing missing values from a data set
Replacing values
Concatenate strings
Bin continuous variables into categories
Working with Relational Data
Add new variables to a data frame from another
Mutating joins and merge()
Filtering joins
Exporting data to a file
Basic Exploratory Data Analysis
Choosing the right chart for your goal
Choosing the right chart for your data
Univariate analysis of numeric variables
Univariate analysis of categorical variables
Basic Exploratory Data Analysis cont'd
Multivariate analysis of numeric variables
Multivariate analysis of numeric and categorical variables
Multivariate analysis of categorical variables
Univariate Analysis
Exploring the data distribution
Central tendency
Spread
Outliers
Shape of the distribution
Visual Representation of Distributions
Histograms
Boxplots
Dot charts / dot plots
Stem and leaf plots
Bar and column charts
Multivariate Analysis
Scatterplots and scatterplot matrix
Correlations
Bar and column charts
Line charts
Customising charts in R
Other graphics options
Basic Modelling
Modelling for prediction
Create a linear model
How good is the model?
Assumptions
Making predictions from the model
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.
"Great trainer, structure, material and manual. I have completed programming courses before but this one just made more sense! Looking forward to the Intermediate course." - R Beginner Sydney
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 has long been popular with statisticians and academics who make up part of the large 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.
Is R compatible with Microsoft?
Microsoft has recognized the power of R and offers not only their own enhanced distribution of R, Microsoft R Open, but the ability to use R within Microsoft products and services such as Power BI, SQL Server / SQL Server Machine Learning Services and Visual Studio. Microsoft has also developed several packages for use in R, including the Microsoft Machine Learning Package for R.
What is Remote Training?
Remote training at Nexacu means our experienced trainers will deliver your training virtually. 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 in the course. Students have the same level of participation and access to the trainer as they would in classroom training sessions.
R BeginnerLearn the basic principles of R programming, the language for statistical and data analysis.
R AdvancedBuild on your base knowledge of the R language and learn how to run data analysis more efficiently.
Machine Learning in RLearn the basic processes of machine learning using R programming. Led by an experienced data scientist.
At Nexacu, we are proud to be the trusted training partner for hundreds of leading organisations across Australia, New Zealand, and around the world. From government agencies to multinational corporations, we help teams build practical skills and achieve real outcomes through expert-led training.
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Custom workbook included with a step by step exercises
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