Big Data is used by some of the world’s biggest organisations, and is defined by its size, complexity and the fact that regular data processing applications are unable to handle it. This course in data science is one of the first in the UK to address the challenges data presents. During your first year you will study topics that include statistics, software engineering and social media. The second year focuses on subjects such as the semantics of data and interoperability strategies, and during your final year you will link your knowledge to applications such as information visualisation. (Computing Program, Computer Science Program)
Assessment forms an integral part of the learning process. The assessment aims to enhance the learning experience rather than simply provide academic benchmarks. It allows your progress to be monitored during the course and to be enhanced by feedback from tutors, and also provides an opportunity for you to integrate your prior learning when undertaking a more focused assignment or presentation task. The assessments for level 6 will be carried out using several methods with exams and in particular developmental portfolios playing a key role. The assessment methods used relate closely to the learning outcomes of the course and individual unit, while allowing you scope for creativity in fulfilling them e.g. by self-selection of case study examples to present within a written report within a particular health context. Assessments will in many cases be vocationally ‘sensitive’ and be designed to promote awareness of contextual policies and to promote engagement with real-life local, large and small scale architectural engineering projects.
Advanced level entry via suitable certification will be considered from relevant local diplomas which map against levels 4 and 5 and allow direct entry onto level 6 of the degree. International students - http://www.beds.ac.uk/howtoapply/international/apply Additional: Applicants with other entry qualifications will be assessed individually by the Course co-ordinator for recognised prior learning (RPL). This might include applicants with complete or partially complete other professional qualifications.
Final Year Module No. Name of Module Credit Point CIS013-3 Research Methodologies and EmergingTechnologies 30 CIS032-3 Data Engineering, Presentation and Retrieval 30 CIS015-3 Social and Professional Project Management 30 CIS017-3 Undergraduate Individual Project 30 TOTAL 120 Total Credit = 120