Applied Data Science MSc

Applied Data Science MSc

School of Engineering


Post- graduate





Contact UCLan

Course Enquiries
University of Central Lancashire
Preston, PR1 2HE, UK.

Tel: +44 (0)1772 892400

  • Duration:

    Full-time: One year; Part-time: Two years

  • Level:


  • Mode:


  • Delivery:

    Campus, Full-time and Part-time

  • Campus:


  • Start Date:


  • Award Type:


Why study this programme?

The ongoing progress in the mathematical tools, the growing prevalence of very large datasets, ever-increasing computational power and progress in automated data acquisition established data science as a mature discipline with rapidly growing number of exploitations in wide spectrum of applications.

This course is designed to develop students’ knowledge and skills in modern data science practice. Through careful planning and engagement, students can have a course bringing them to the up-front of the field. It combines a project-based approach with opportunity for personal development through a flexible and supportive learning experience.

Course content
Three key strands

  • Artificial Intelligence
  • Internet of Things
  • Robotics

The underpinning practical and theoretical skills, such as programming, project management, statistics, develop along with timetabled teaching sessions and individual/group projects.

The course will be based on the UCLan main campus.

  • For full-time, it is a one-year course.
  • For part-time, it takes 2-years.

Entry Requirements

2.2 or above in science, technology, engineering and math subjects, or equivalent industrial experience (interviews might be required)

Programme at a Glance

Semester 1 only

  • Research methods
Semester 2 only
  • Applied Instrumentation

Semester 1 and 2

  • Artificial Intelligence and Machine learning
  • Internet of Things
  • Big Data Analytics and Visualization
  • Programming with Data
  • Object-Oriented Software Development
  • Digital Signal and Image Processing B
  • Visual Information Processing
  • Advanced Robotics and Intelligent System Design

Semester 1/2/3
  • MSc Project

Postgraduate Advice Event

Find out more about Postgraduate courses at our Postgraduate Advice Event on 8 November 2018

Further Information


The course team has a dedicated lab for teaching purposes in the Engineering Innovation Centre (EIC) building. There will be equipment like modern graphics processing unit (GPU) cards for running simulations of data science projects.

The course team has domain experts with expertise in data science and related applications such as medical imaging, signal analysis for non-invasive inspection, computer aided diagnosis.

There will be a data science lab in the our new Enginnering Innovation Centre (EIC) with modern Graphic Processing Unit cards.

How to Apply

You can apply for many of the postgraduate UCLan courses using our Online Application System.

For other postgraduate courses you can apply directly to UCLan by downloading a Postgraduate Application Form (.pdf 190KB) please also see our Postgraduate Application Guidance Notes (.pdf 158KB).


For detailed information about studying this course at UCLan, please see the course handbook for your year of entry:

For information on possible changes to course information, see our Important Information.


Apply now or see further information about postgraduate study and research. International students should visit our international pages.

Contact Us

Tel: +44 (0)1772 892400


Fees 2019/20

Full-time: £6,700 per year (UK/EU)
Part-time: £3,345 per year for first 2 years (UK/EU)

Tuition Fees are per year unless otherwise stated.

Further information:

For 2018/19 fees please refer to our fees page.

Industry Links

The course team is working closely with the ADMT (Advanced Digital Manufacturing Technology) research centre and the CVML (Computer Vision and Machine Learning) research group.

Students can benefit from working with the modern manufacturing facilities including for example Kuka robots and working on real-life manufacturing projects through the industrial links. Furthermore, through the collaborative links with the health sector, the interested students could contribute to the ongoing biomedical data analytics projects.


  • The students will have a school expo to present their project to external audience.
  • The students will have the 3-minute competition for their projects.
  • The graduates will be equipped with skills in working on modern data science projects as an individual as well as in a team
  • The students can apply for PhD upon graduation.