This three day course is aimed at those wishing to learn how to use R with Tidyverse packages to work with and handle Data. When combined with our Introduction to Data Science course you would be set up well to follow an R learning journey into Data Science, Machine Learning, and Artificial Intelligence.

During the programme you will be introduced to R and specific development environments and packages for working with Data, with a focus on Tidyverse packages including dplyr, tidyr, stringr, ggplot2 and more.

Along the way you will see how to clean and manipulate tabular data, apply simple statistical techniques and create engaging data visualisations.

Throughout the course you will engage with activities and discussions with one of our Data Science technical specialists and complete technical lab activities to practice the techniques you have learnt and develop ideas for further practice.

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No prior experience with R is necessary, though it is assumed that you will be familiar with core data concepts such as simple table structures and data types – all the pre-requisites you need are covered by our Data Fundamentals (coming soon) course.

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Delegates will learn how to

  • To apply your knowledge of data practically using R for handling data in roles that involve data analysis, data engineering, data science, machine learning and AI, and Data related Ops roles.
  • If you are in a Software or IT related role where you work with R, this course will support you in learning how to work with Data.
  • To ensure you have the necessary pre-requisite knowledge when combined with Introduction to Data Science should you wish to progress onto Data Science and Machine Learning with R (coming soon).
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Introduction to Programming for Data Handling

  • Describe the pros and cons of using programming languages to work with data
  • Identify the languages most suitable for data handling
  • Explain the challenges of using programming languages versus data analysis tools

Introduction to R, RStudio, and Quarto

  • Describe the key attributes of the R programming language.
  • Explain the role of RStudio and Quarto for R programming.
  • Use RStudio to write a basic R program.
  • Write a program which uses string, integer, float and boolean data types.

Data Structures, Functions, and Pipes

  • Construct dataframes and tibbles to solve data problems.
  • Write reusable functions which can be used to alter data & automate repetitive tasks.
  • Use a selection of R’s built-in functions and trustworthy packages along with base R and dplyr’s Pipe.

Data Sources

  • Read from csv, excel, and json files.
  • Connect to databases using DBI paired with a backend

Data Manipulation

  • Create, manipulate, and alter dataframes and tibbles.
  • Use base R and tidyverse methods for indexing, slicing, querying, filtering, grouping, pivoting, and merging tables.

Data Cleaning and Preparation

  • Identify data quality metrics, missing data and apply techniques to deal with it.
  • Deduplicate, transform and replace values.
  • Use string methods to manipulate text data.
  • Write regular expressions which munge text data.

Methods for Visualising Data

  • Construct and tailor data visualisations using ggplot2.
  • Meaningfully visualise aggregate data.

If you enjoy this course and want to learn more about using R within a Data or Software related role, we recommend progression onto one of the following:

  • Statistics for Data Analysis in R (coming soon)
  • Data Science and Machine Learning with R (coming soon)
  • R Programming (coming soon)
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Why choose QA

Dates & Locations

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Frequently asked questions

How can I create an account on myQA.com?

There are a number of ways to create an account. If you are a self-funder, simply select the "Create account" option on the login page.

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Find more answers to frequently asked questions in our FAQs: Bookings & Cancellations page.

How do QA’s virtual classroom courses work?

Our virtual classroom courses allow you to access award-winning classroom training, without leaving your home or office. Our learning professionals are specially trained on how to interact with remote attendees and our remote labs ensure all participants can take part in hands-on exercises wherever they are.

We use the WebEx video conferencing platform by Cisco. Before you book, check that you meet the WebEx system requirements and run a test meeting (more details in the link below) to ensure the software is compatible with your firewall settings. If it doesn’t work, try adjusting your settings or contact your IT department about permitting the website.

How do QA’s online courses work?

QA online courses, also commonly known as distance learning courses or elearning courses, take the form of interactive software designed for individual learning, but you will also have access to full support from our subject-matter experts for the duration of your course. When you book a QA online learning course you will receive immediate access to it through our e-learning platform and you can start to learn straight away, from any compatible device. Access to the online learning platform is valid for one year from the booking date.

All courses are built around case studies and presented in an engaging format, which includes storytelling elements, video, audio and humour. Every case study is supported by sample documents and a collection of Knowledge Nuggets that provide more in-depth detail on the wider processes.

When will I receive my joining instructions?

Joining instructions for QA courses are sent two weeks prior to the course start date, or immediately if the booking is confirmed within this timeframe. For course bookings made via QA but delivered by a third-party supplier, joining instructions are sent to attendees prior to the training course, but timescales vary depending on each supplier’s terms. Read more FAQs.

When will I receive my certificate?

Certificates of Achievement are issued at the end the course, either as a hard copy or via email. Read more here.

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