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Internet of Things - MSc

Key information

Qualification type

MSc - Master of Science

Subject areas

Internet Software (Use)

Course type


Course Summary

The MSc in Internet of Things course aims to train computing and engineering professionals to follow a career where they can apply leading-edge computing, engineering, sensor technology, networks and data science skills across a range of application domains. The Internet of Things (IoT) has become one of the most discussed technology trends of recent years mainly due to the expected impact that it will have and, as a result, how it will change the way people live, work and travel. As a discipline, it covers elements of Computing Science, Engineering, and Data Science. The course content has been informed by internationally leading research being conducted by the School of Computing and the School of Engineering. The delivery of the course is supported by a large-scale pervasive and mobile computing environment, a suite of contemporary sensing technologies and rapid prototyping facilities. This intensive one-year specialist master’s course on Internet of Things is aimed at highly-motivated graduates with a good honours degree in computing, engineering or a related discipline. While the course has a particular focus on the employment needs of the local economy, the skills and abilities developed are easily transferred to a more global stage. The Internet of Things is an exciting and exponentially growing area both within industry and academic. It sits at the intersection between Computing Science, Engineering and Data Science. The proposed MSc in Internet of Things will, therefore, prepare students for both an industrial career with skills in computing, networks, sensor technologies and data analytics in addition to providing a relevant platform to embark on research studies. These types of skills are in high demand within the sector across the key verticals of Smart Cities, Industrial IoT, Connected Health and Smart Homes.

The Internet of Things is expected to have a significant impact on industry with predictions of its success and growth constantly rising. It is at the same time the most anticipated and least understood initiative within IT departments. Figures at the start of 2018 suggest that nearly 70% of organisations have developed plans to embrace IoT in their organisation within the next year. As the expectations of how IoT will redefine an organisation’s operations grow so too are the expectations to have appropriately knowledgeable and skilled staff in the areas of computing, engineering and data science in addition to having an appreciation for business processes and market potential. Taking all of this into consideration, graduates from the MSc in Internet of Things will be well placed to progress into a wide variety of careers, across a range of industrial settings and application domains. There are also opportunities for graduates from the MSc Internet of Things to embark on further research by enrolling for PhD study affiliated with the research centres within the School of Computing and the School of Engineering. Computing related PhD studies can be perused in the areas of Pervasive Computing and Artificial Intelligence within the School of Computing whilst sensor technology, networking and RTOS research can be undertaken within the School of Computing.

Different course options

Full time | Jordanstown Campus | 1 year | JAN

Study mode

Full time


1 year

Start date



Within this module a variety of database and data storage paradigms will be explored, ranging from more traditional relational systems to NoSql and object stores, time series databases, semantic store and graph stores.Consideration will be given to big data and the problem with storing and querying high volumes of highly variable data which is stored and processed at a high speed. The cloud computing paradigm will also be introduced and how to avail of its power and resources.The core concepts of distributed computing will be examined in the context of Hadoop. Students will be taught, practically and theoretically, about the components of Hadoop, workflows, functional programming concepts, use of MapReduce, Spark, Pig, Hive and Sqoop.

Tuition fees

UK fees
Course fees for UK / EU students

For this course (per year)


Average for all Postgrad courses (per year)


International fees
Course fees for non-UK / EU students

For this course (per year)


Average for all Postgrad courses (per year)


Entry requirements

Applicants must: (a) have gained (i) a second class lower division honours degree or better, in the subject areas of computing, engineering or cognate area 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 and (b) provide evidence of competence in written and spoken English (GCSE grade C or equivalent). In exceptional circumstances, as an alternative to (a) (i) or (a) (ii) and/or (b), where an individual has substantial and significant experiential learning, a portfolio of written evidence demonstrating the meeting of graduate qualities (including subject-specific outcomes, as determined by the Course Committee) may be considered as an alternative entrance route. Evidence used to demonstrate graduate qualities may not be used for exemption against modules within the programme.