Awards
Target Award
Award Description:Master of Science - MS
Non Recruitable Target
Recruitable Target
Alternative Exit
Alternative Exit
Accreditation
Institution of Engineering and Technology (IET)
Programme Offerings
Full-Time
F2F-JMU-JAN
F2F-JMU-JAN
F2F-JMU-SEP
F2F-JMU-SEP
Sandwich Year Out
F2F-JMU-JAN
F2F-JMU-SEP
Educational Aims of the Course
The MSc programme in Sensors, Data and Management is designed to develop a high level of technical expertise together with the emotional competencies to be able to practice successfully as a professional engineer and an adaptive leader in a diverse interdisciplinary engineering industry environment. Engineers are increasingly expected to take on important technical leadership and management responsibilities early in their careers and the knowledge, skills and practical experience gained from this programme is designed to produce graduates who are able to make an immediate impact to their employers' organisations. Graduates of this programme should be able to: Demonstrate a high level understanding of the principles driving future developments in the area of Sensors, Data analytics, IoT etc. Demonstrate an advanced level of analytical and experimental skills that will allow the successful graduate to design new systems, and provide them with the skills to critically analyse existing designs, their functionality and expected performance. Demonstrate the range of soft skills underpinning the personal and social competencies and the traits of a mature leader both in their work and personal environment. Demonstrate communication skills commensurate with the achievement of a post-graduate qualification and the duties associated with the status of a chartered engineer. Demonstrate enhanced transferable skills and professional behavioural traits that will allow students that complete the programme to hold responsible technical and managerial roles involving engineering. Demonstrate a well-developed academic base that provides for further learning/research/personal and professional development. Demonstrate an ability to conduct scholarly activity and undertake self-driven research/project work and to deliver high quality results, and to provide the required skill set should students decide to undertake further academic study. In addition, the 240 credit MSc programme aims to apply engineering, technology and scientific knowledge to a real-world design problem, analysed and developed through the application of effective group team-working and project management skills.
Learning Outcomes
1.
Demonstrate comprehensive knowledge and critical awareness of essential facts, concepts, theories and principles of electronics surrounding sensors and mathematical concepts surrounding big data analysis, and their underpinning science and mathematics.
2.
Demonstrate a comprehensive understanding of the principles of management and engineering business practice techniques for evaluation of technical and business risks and their limitations and potential pitfalls.
3.
Critically evaluate designs, processes and products, and identify and make improvements by using problem-solving skills and appropriate software /and hardware.
4.
Critically evaluate and select the most appropriate research methodologies for the solution of professional and commercial problems in a timely and robust manner.
5.
Apply appropriate analytical and modelling techniques to a range of engineering problems and demonstrate the ability to apply the appropriate strategies to the application of analysis tools to solve practical engineering problems.
6.
Prepare and present technical/business reports and presentations to a professional level and to speak with authority on their engineering discipline.
7.
Produce a design/system that satisfies a given specification.
8.
Instigate, plan and manage engineering/technical projects, taking into account the commercial, industrial, and customer requirements.
9.
Communicate effectively in a professional manner by the means of written and spoken technical English.
10.
Display and evidence enhanced self-learning skills appropriate to the attainment of an FHEQ level 7 qualification.
11.
Work within time constraints and an ability to prioritise workloads in order to deliver to deadlines.
12.
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
13.
Generate and synthesise evidence required in the solution of complex engineering problems.
14.
Conduct a research study to critically evaluate state-of-the-art from literature in a field related to the study and make suggestions for improving some of the issues encountered in the methods for specific applications.
15.
Work on an independent project that will add knowledge to the existing state-of-the-art in a research area related to the field of study.
16.
Design experimentation/simulation to model new concepts/hypothesis in a related field of study.
17.
Critically analyse results from experimentation in a related field and discuss the implications of those results.
18.
Propose methodologies to extend existing projects to achieve improvement and extended learning.
19.
Appreciate the social, environmental, ethical, economic and commercial considerations affecting the exercise of their engineering judgement.
20.
Demonstrate a comprehensive and systematic understanding of the scientific principles of Electronics and Communication engineering and related engineering disciplines.
21.
Demonstrate comprehensive knowledge and understanding of mathematical and computer models relevant to electronics, data science and related engineering disciplines, and an appreciation of their limitations.
22.
Evaluate developing technologies related to sensors, data and their applications.
23.
Use fundamental knowledge to investigate new and emerging technologies and synthesise solutions comprising sensor and data analysis to engineering problems.
24.
Apply mathematical and computer-based models for solving problems in engineering, and the ability to critically evaluate the limitations of particular cases related to handling big data and employing sensors in practical application scenarios.
25.
Critically evaluate the limitations of current knowledge and the changing nature of technologies and society, and the need to gain new knowledge through further study and team-based project work in the field of sensors, big data and their applications.
Teaching, Learning and Assessment
Acquisition of knowledge is achieved mainly through lectures and directed student-centred learning. Student-centred learning is used where appropriate resource material is available. Understanding is reinforced through practical work, case-studies and simulation work. Testing of the knowledge base is through a combination of unseen written examinations, assessed coursework in the form of case-study reports and coursework assignment submissions. Intellectual skills are developed through activity-based learning, group activities, panel discussions, design case-studies, simulation work and coursework assignments. Open-ended practical and project work is designed to permit students to demonstrate achievement of all the learning outcomes in this category. Analysis, design and problem solving skills are assessed through a combination of unseen written examinations, assessed coursework in the form of case-study reports and coursework assignment submissions. Subject practical skills are developed in a coordinated manner throughout the programme. A common thread through the programme is the utilisation of a computer simulation environment to undertake modelling, design and analysis. One of the avenues of developing the soft skills is through the modules on leadership skills and industrial context. The experiential learning of both subject specific practical skills and the emotional competencies will be through the industrial placement in the second year of study. Practical skills are assessed through case-study coursework reports, group and individual projects, research reports, and through oral and written examinations. Development of practical and soft skills are assessed through portfolio, self-reflection and peer-review. In addition to the learning and development that takes place through two specific practical based modules and industrial placement experience, transferable skills permeate every activity within the programme content and assessment. Intellectual and knowledge based skills are assessed through design and problem solving coursework with reports, portfolio, self-reflective report. Soft skills such as interpersonal skills are also assessed via presentation, report writing and peer review. Application of skills are also embedded within the self-management process of the project.
Programme Structure
Programme Structure Description
Students on the 2-year programme who undertake a placement will be enrolled on module 7405MENR Sandwich Year Placement and will be awarded a further 60 credits for successful completion. Students on the 2-year programme who do not undertake a placement, will be enrolled on module 7000FETGDP Group Design Project and … For more content click the Read More button below.
Structure
Level 7
Approved variance from Academic Framework Regulations
Variance approved 28/01/2022: Where a module comprises two or more assessment elements (e.g. examination and coursework), successful completion of the module should require a mark of greater than 10% less than the module pass mark in each element, as well as the overall module mark being above the normal pass … For more content click the Read More button below.