Data science is a rapidly developing field of study within both academia and industry. Demand for data scientists and business analysts is high in many industries including IT, business, security and health sectors, intelligent transport, energy efficiency, and creative industries. This course will prepare you for a future career as a data scientist or business analyst, working in any profession where large amounts of data are collected and there is a need for skills in data acquisition, information extraction, aggregation and representation, and data analysis using state-of-the-art machine learning technologies.
You will benefit from a firm grounding in the core disciplines of data analytics and information processing, partnered with a broad appreciation of aspects of other disciplines where data science can form natural synergistic relationships. We will help you to build your skills and professional network. Utilising our research expertise and industrial links, you will conduct data projects with internal departments and external university partners.
For further course details please see "Course Web Page" below.
Early Childhood Education: Policy and Practice
• International best practice and early childhood education
• Early childhood education policy and practice in Ireland
• Theory and practice of play in early childhood education
• Critiquing Aistear as a play-based curriculum framework
• Role of the practitioner in developing the selfregulated learner
Psychology of Early Childhood
• Key concepts and debates in psychology of early childhood
• Learning theories: How do young children learn?
• Emotional and behavioural development in early childhood
• Early childhood in context
• Assessment & evaluation
Language and Literacy in Early Childhood Education
• Literacy as social practice
• Emergent literacy
• Oral language development
• Formal and informal literacy skills
• The role of story in early years education
• Key philosophical underpinnings and history of inquiry-based learning
• Key pedagogical principles underpinning inquirybased learning models
• Creating and resourcing an inquiry-based environment
• Assessment in inquiry-based learning
• Inquiry-based learning exemplified in mathematics and science
• Research methodologies and research ethics
• The research design process
• Research proposal
To apply to our postgraduate taught programmes, you must meet the University's General Entrance Requirements and any course-specific requirements.
These vary depending on the course and are detailed online.
(a) have gained
(i) a second class honours degree or better from a university of the United Kingdom or the Republic of Ireland, or from a recognised national awarding body, or from an institution of another country which has been recognised as being of an equivalent standard; or
(ii) an equivalent standard (normally 50%) in a Graduate Diploma, Graduate Certificate, Postgraduate Certificate or Postgraduate Diploma or an approved alternative qualification;
and the qualification must be in the subject areas of computing, engineering or related discipline
(b) provide evidence of competence in written and spoken English (GCSE grade C or equivalent).
If English is not your first language this course requires a minimum English level of IELTS (academic) 6.0 with no band score less than 5.5, or equivalent.
Visit ulster.ac.uk/englishrequirements for more details.
This course is open to international (non-EU) students (full-time only).
For full entry requirements please see "Course Web Page" below.
Application is through the University's online application system (see "Application Weblink" below).
How is the course assessed?
Assessment is linked to the modular nature of the course. It consists of assignments, essays, case studies and a literature review in year 1, followed by a research proposal and dissertation in Year 2.
ECTS Credits: 90
Full-Time (Magee)/Part-Time (Magee or Belfast).
Post Course Info
The key message from employability and work-related learning initiatives is that enhancing opportunities to develop work-related learning and employability enhances the learning of the subject being studied. We understand the importance of including real industrial and commercial contexts to our student's experience, so this MSc Data Science will pursue opportunities for industrially linked teaching material and student project work. In this regard, we will utilise our business and industry links to facilitate an industrially relevant student project. Such projects create valuable experiences for the student, and additionally, they can also help to build new and ongoing collaborations with departments and companies, with the potential to tap into funding streams designed for industry-academic research and development.
A recent statement from Ulster University's Careers Office indicates that Data analysts are in high demand across all sectors, such as finance, consulting, manufacturing, pharmaceuticals, government and education. Data analysts can work in large companies such as the 'big four' consultancies or financial services firms, or consumer retail firms, small and medium sized businesses such as marketing agencies' or the public sector.