Full-time: One year; Part-time: Two years
Campus, Full-time and Part-time
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.
Three key strands:
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.
2.2 or above in science, technology, engineering and math subjects, or equivalent industrial experience (interviews might be required)
Find out more about Postgraduate courses at our Postgraduate Advice Event on 8 November 2018
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.
You can apply for many of the postgraduate UCLan courses using our Online Application System.
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.
For 2018/19 fees please refer to our fees page.
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.