R Programming - Intermediate Training Course

Learn how to use R for data analysis, instructor-led course.

Classes as per schedules.
R is a programming language specifically developed for statistical data analysis and for producing graphical output. We introduced the core elements of R programming in our R Basics course. This course, R Programming Intermediate, is the second in our R series and focuses on:
  • data manipulation
  • basic exploratory data analysis
  • creating customised data visualisations
  • basic modelling 
Our experienced Data Analyst will guide you through exercises to practice writing R code, use a variety of different functions, produce graphical output, and view the results. Read the full outline here.

R Programming - Intermediate Training Course

Data manipulation, basic exploratory data analysis, customised data visualisations and basic modelling in R.

$745
10 max
1 day
$745
10 max
1 day
$745
10 max
1 day
$745
10 max
1 day
$745
10 max
1 day
$745
10 max
1 day
$745
10 max
1 day
$745
10 max
1 day
$745
10 max
1 day

Remote East

Brisbane

Sydney

Parramatta

Melbourne

Canberra

Adelaide

Perth

Remote West

Upcoming Courses:
Remote East
Date
Course
City
Status
Mon 9 Dec 24
Mon
9
Dec
R Intermediate
Remote East
Status: Scheduled
Scheduled
Tue 4 Feb 25
Tue
4
Feb
R Intermediate
Remote East
Status: Scheduled
Scheduled
Mon 31 Mar 25
Mon
31
Mar
R Intermediate
Remote East
Status: Scheduled
Scheduled
Brisbane
Date
Course
City
Status
Mon 9 Dec 24
Mon
9
Dec
R Intermediate
Brisbane
Status: Scheduled
Scheduled
Tue 4 Feb 25
Tue
4
Feb
R Intermediate
Brisbane
Status: Scheduled
Scheduled
Mon 31 Mar 25
Mon
31
Mar
R Intermediate
Brisbane
Status: Scheduled
Scheduled
Sydney

We don't have courses scheduled in your city currently. Please see our remote course options or contact us to register your interest.

Parramatta

We don't have courses scheduled in your city currently. Please see our remote course options or contact us to register your interest.

Melbourne

We don't have courses scheduled in your city currently. Please see our remote course options or contact us to register your interest.

Canberra

We don't have courses scheduled in your city currently. Please see our remote course options or contact us to register your interest.

Adelaide

We don't have courses scheduled in your city currently. Please see our remote course options or contact us to register your interest.

Perth

We don't have courses scheduled in your city currently. Please see our remote course options or contact us to register your interest.

Remote West

We don't have courses scheduled in your city currently. Please see our remote course options or contact us to register your interest.

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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. 

"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 Programming Intermediate Course Details

Price
$745
Duration
1 day
Times
9am-4pm
Class Size (max)
10
Class Size (avg)
5
Reference Materials
Provided
CPD Hours
6 hours
Delivery
Instructor-led training
Live Online
microsoft_gold

R Programming Intermediate Course Details

Price
$745
Duration
1 day
Time
9am-4pm
Class Size (max)
10
Class Size (avg)
5
Reference Materials
Provided
Training Computer
Provided
CPD Hours
6 hours
Delivery
Instructor-led training
Address
Level 8
201 Charlotte Street
Brisbane QLD 4000
microsoft_gold

R Programming Intermediate Course Details

Price
$745
Duration
1 day
Time
9am-4pm
Class Size (max)
10
Class Size (avg)
5
Reference Materials
Provided
Training Computer
Provided
CPD Hours
6 hours
Delivery
Instructor-led training
Address
Level 24/477 Pitt Street
Sydney
New South Wales 2000
microsoft_gold

R Programming Intermediate Course Details

Price
$745
Duration
1 day
Time
9am-4pm
Class Size (max)
10
Class Size (avg)
5
Reference Materials
Provided
Training Computer
Provided
CPD Hours
6 hours
Delivery
Instructor-led training
Address
Level 7
79 George Street
Parramatta NSW 2150
microsoft_gold

R Programming Intermediate Course Details

Price
$745
Duration
1 day
Time
9am-4pm
Class Size (max)
10
Class Size (avg)
5
Reference Materials
Provided
Training Computer
Provided
CPD Hours
6 hours
Delivery
Instructor-led training
Address
Level 12A
45 William Street Melbourne VIC 3000
microsoft_gold

R Programming Intermediate Course Details

Price
$745
Duration
1 day
Time
9am-4pm
Class Size (max)
10
Class Size (avg)
5
Reference Materials
Provided
Training Computer
Provided
CPD Hours
6 hours
Delivery
Instructor-led training
Address
NEW LOCATION
Level 2
221 London Circuit
Canberra ACT 2600
microsoft_gold

R Programming Intermediate Course Details

Price
$745
Duration
1 day
Time
9am-4pm
Class Size (max)
10
Class Size (avg)
5
Reference Materials
Provided
Training Computer
Provided
CPD Hours
6 hours
Delivery
Instructor-led training
Address
Level 15
33 King William Street
Adelaide 5000
microsoft_gold

R Programming Intermediate Course Details

Price
$745
Duration
1 day
Time
9am-4pm
Class Size (max)
10
Class Size (avg)
5
Reference Materials
Provided
Training Computer
Provided
CPD Hours
6 hours
Delivery
Instructor-led training
Address
Level 7
553 Hay Street
Perth WA 6000
microsoft_gold

R Programming Intermediate Course Details

Price
$745
Duration
1 day
Times
9am-4pm
Class Size (max)
10
Class Size (avg)
5
Reference Materials
Provided
CPD Hours
6 hours
Delivery
Instructor-led training
Live Online
microsoft_gold

R Programming Course Outlines

Contact Us


What do I need to know to attend?

You should have attended our R Beginner course and have a basic understanding of R syntax.

It is assumed that you are familiar with:

  • basic R syntax
  • data types and structures
  • know how to subset data
  • know how to install and use contributed packages and their functions
  • basic familiarity with working in RStudio is helpful.

R Programming Intermediate Learning Outcomes

You will understand and be able to:

  • create and manipulate objects
  • use functions
  • work with relational data

 

  • perform basic exploratory data analysis
  • conduct basic modelling and prediction
  • find functions to perform specific tasks.

R Programming Intermediate Course Content

  • 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

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