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Practical Data Science using R

Short Course
Practical Data Science using R

This short course has been specifically designed for professionals who wish to build strong analytical skills to process and manipulate different types of data. By attending this course, you will be able to develop strong practical analytical skills, which will enable you to transform data into knowledge that can inform your business practices.

R is an open-source programming language for statistics, data analysis and visualisation. It consists of an extensive set of packages that provide functionality for almost every single data-related task (i.e. load data from excel sheets, collecting data from Social Media sites, finding hidden patterns in data, visualising trends, detecting outliers, and so on). R provides simple and easy-to use packages for advanced and mathematically complex machine learning and data mining models and is considered as one of the most powerful tools in Data Science and Analytics.

This course has one study option

Mode of Attendance

  • On Campus

Mode of Study

  • Full Time

Start Date

To be confirmed

Course Length

2 days

Session 1

Introduction to R and RStudio and Data Exploration

An overview of R and RSTudio, and learn how to load, process and explore different datasets. You will learn how to explore data by means of simple summary statistics, linear regression models and basic visualisation techniques (i.e. Histograms, Box plots, and others).

Session 2

Data manipulation and Visualisation

You will learn how to manipulate, aggregate and summarise data using the most popular packages in ‘R’ such dplyer.  You will learn how to handle missing values, redundant features, reshape your datasets and others to prepare it for further analytics. You will learn to tell the story of large and complex datasets visually using the R package ‘ggplot2’

Session 3

Data Modelling

Build and evaluate different state-of-the-art machine learning algorithms using real-life datasets (SVM, Random Forest …). You will learn the underlying concepts of these models in a very practical way. You will then be able to apply these models to real datasets, evaluate and communicate the results in visual form. 

Session 4

Interactive Reports

An overview of markdown in ‘R’. You will learn how to produce an interactive reproducible results that communicate the workflow in an easy-to interpret reproducible format.

 

Modules

The University regularly reviews its courses. Course content and structure may change over time. See our course and module disclaimer for more information.

Learning Methods

The key concepts will be delivered via short lectures to give you the opportunity to spend most of the time applying your learning via hands-on interactive labs.

Staff delivering this course

Dr Eyad Elyan is a Senior Lecture in the School of Computing and the course leader of the MSc Data Science. Dr Elyan has strong background and research interest in Advanced Machine Learning and Data Analytics, and had led several projects with industrial partners and public funding bodies (i.e. Innovate UK, OGIC, Data Lab, Historic Environment) to successful completion.

 

Academic Support

The Inclusion Centre advises and supports students who disclose a sensory or mobility impairment, chronic medical condition, mental health issue, dyslexia and other specific learning differences. Applicants are encouraged to arrange a pre-entry visit to discuss any concerns and to view the facilities.

Online Learning & Support

Whether you are learning on campus or by online learning, students benefit from using our collaborative virtual learning environment, CampusMoodle. You will be provided with 24/7 online access to your learning material and resources, along with the ability to interact with your class members and tutors for discussion and support.

Study Skills Support

The Study Support Team provides training and support to all students in:

  • Academic writing
  • Study skills (note taking, exam techniques, time management, presentation)
  • Maths and statistics
  • English language
  • Information technology support

Library Support

The Library offers support for your course, including the books, eBooks, and journals you will need. We also offer online reading lists for many modules, workshops and drop-ins on searching skills and referencing, and much more.

 

For professionals who wish to build strong analytical skills to process and manipulate different types of data.

 

 
  • Whole course - £500 

Payment for this course can be arranged throughout the year at a time convenient to applicants.

Additional Costs

The following course-related costs are not included in the course fees:

Disclaimer

For new intakes course fees are reviewed and published annually for each mode of delivery. Tuition fees are fixed for the duration of a course at the rate confirmed in the offer letter.  For further information see:

 

Have a question about the course? Get in touch with the team and we'll do our best to help.

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Taking this course, you will have access to some of the world's best facilities. 

We've invested more than £100 million in the development of our campus, new facilities and new resources.

University Wide Facilities

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