Immerse yourself in the emerging interdisciplinary field of engineering, computing and statistics. Combine a project-based approach with flexible learning on our MSc in Applied Data Science. The course tackles four key strands of data science learning: data science, artificial intelligence, the Internet of Things, and robotics.
The ongoing progress in mathematical tools and automated data acquisition, combined with the growth of very large datasets and computational power, has established data science as a mature discipline with a broad spectrum of applications.
This course is designed to develop your knowledge and skills in modern data science practice. Practical and theoretical skills, such as programming, project management and statistics, are developed through a learning approach that combines taught sessions with individual and group projects.
Why study with us
- Choose an optional module based on your own academic interests. Options are available for software engineering, robotics, sensors and instruments,
- Learn from an expert team. Many of the course tutors have research interests and experience in the field of data science and its applications. A number of staff are also research active.
- Participate in a School Expo, presenting your project to an external audience including industry representatives. The Expo involves a three-minute competition for your project.
What you’ll do
- Access world-class facilities and expertise in data science and related applications, such as medical imaging, signal analysis for non-invasive inspection, and computer-aided diagnosis.
- Located within one of the most intense engineering and manufacturing areas in the UK, our £35m Engineering Innovation Centre provides an integrated space for teaching, research and work on live, real-world projects with commercial partners.
- If you have an interest, you could contribute to the ongoing biomedical data analytics projects brought about by our collaborative links with the health sector.
Module overview
Compulsory modules
• EL4011: Artificial Intelligence and Machine Learning
• EL4012: Internet of Things
• EL4013: Programming with Data
• EL4016: Big Data Analytics and Visualization
• EL4166: Research Methods
• EL4895: MSc Project (Engineering)
Optional modules
• EL4007: Advanced Robotics and Intelligent System Design
• EL4014: Visual Information Processing
• EL4015: Object Oriented Software Development
• EL4147: Digital Signal and Image Processing B
• ER4706: Applied Instrumentation
Course delivery
This course is taught face-to-face at one of our UK campuses.
Every effort has been made to ensure the accuracy of our published course information. However, our programmes are subject to ongoing review and development. Changing circumstances may cause alteration to, or the cancellation of, courses. Changes may be necessary to comply with the requirements of accrediting bodies or revisions to subject benchmarks statements. As well as to keep courses updated and contemporary, or as a result of student feedback. We reserve the right to make variations if we consider such action to be necessary or in the best interests of students.
The University is located within one of the most intense engineering and manufacturing areas in the UK. The advanced manufacturing sector in Lancashire employs around 73,300 people, accounting for 12% of total employment.
Our School of Engineering has links with major employers in aerospace, automotive and civil engineering including BAE Systems and JLR, as well as with sector support and supply chain organisations such as the NW Aerospace Alliance and the Northern Automotive Alliance.
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.
Thanks to these industrial links, you can experience modern manufacturing facilities including, for example, Kuka robots. And you can work on real-life manufacturing projects.
Future careers
As a graduate, you will be equipped with skills in working on modern data science projects in both an individual and a team capacity.
Upon graduation you may apply for a PhD.
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