Level 9 About NFQ
Dr Linzi RyanEmail Phone
Department of Design Innovation
PG Course Leader
***Extended Application Deadline until Monday 31st August***
Graduates of this programme can find careers in areas such as Product R&D in service and manufacturing industries, Manufacturing R&D, marketing, consumer engagement and customer services.
In this course, you will learn how to make impact on businesses and organisations through Design Innovation in the new industrial age. Design thinking is a creative problem-solving process that focuses on gaining a deep understanding of user’s needs in order to challenge assumptions and produce innovative and impactful solutions. You will learn the innovation techniques of design thinking to uncover user needs and insights, and how to combine these techniques with big data analytics. You will also learn the broad concepts of Artificial Intelligence (AI) and machine learning to utilise technology from a human centred perspective.
Human and machine learning are more integrated than ever before. This course will provide you with a combination of soft and hard analytical skills that can be used to inform business strategy and innovation in both manufacturing and service industries. The design innovation approach at the core of this programme will provide you with the tools to anticipate changes in the workplace, and to realise the opportunities of product/service convergence.
Creativity, socio-emotional intelligence and complex reasoning are the skills that are rising in importance across every work role (Accenture 2018). ‘The New Economy’ requires new ‘combinatorial skillsets’ in industry and professional services that balance human insight, data fluency and fast paced entrepreneurship.
This new program will teach you these cross-disciplinary skills through modules from the Department of Design Innovation, the School of Business and the Department of Computing. A new year-long bespoke module will deliver career guidance to empower you by providing employability skills, such as C.V. preparation and presentation skills, encourage personal lifelong learning plans, and experiential learning.
1 To identify human needs and behaviours of all stakeholders within a business context through in-depth user-centred research and design.
2 To demonstrate competence in using techniques and skills to synthesise and prototype new innovation strategies and concepts.
3 To demonstrate an understanding of Artificial Intelligence and how to adopt and apply it as part of innovation strategy.
4 To identify and evaluate the principal concepts of big data management, techniques and practice in descriptive, predictive, and prescriptive analytics.
5 To demonstrate competence in using exploratory and analytical tools to utilise user needs to define and prototype digital service/production innovations within the workplace.
Level 8 or prior knowledge equivalence as set in RPEL
Through the Department of Design Innovation, the course utilises ethnographic research methods to inform, develop, implement and validate new services. In a Design context, you will be encouraged to evaluate methods such as participant observation and in-depth interviews and consider other, less tangible elements: the challenges of ‘figuring out’ a socio-cultural context, symbolic meaning or the indeterminacy of meaning. This is combined with a core module from the Business School Living Lab to teach the principal concepts of big data management, and techniques, with hands-on-experience in descriptive, predictive, and prescriptive analytics. This combination of soft and hard analytical skills can be used to inform business strategy and innovations. Underpinning this are Computer Science modules that provide foundation tools for computational thinking and problem solving, in areas such as AI and machine learning.
Where appropriate, modules employ live projects from industry partners with established working/research relationships with Maynooth. A year-long bespoke module for the course delivers career guidance providing employability skills, such as C.V. preparation and presentation skills, as well as invited industry speakers and site visits to contextualise course learnings in real world scenarios. Topics could include Sustainable Development, Ethics and Corporate Social Responsibility, issues around citizens/workers’ rights, data privacy and democracy within the emerging AI context. Students are offered a choice of optional modules depending on their interests and career intentions in computer AI or electronic engineering control systems. Two blended learning modules in user interface (UI) and user experience (UX) design, and Service Innovation, will be delivered using online content delivery and face-to-face practical labs.
The majority of the learning occurs in preparation for the taught element, the lab work, and project work that flows from the taught element. This involves individual independent study, reading and research, coupled with group work. The Design modules are taught in studio in group and individual applied practicals involving research, ideation, prototyping and presentation of findings and concepts. Guest speakers and live projects will bring industry engagement into the studio and may involve some site visits.
The Postgraduate Diploma in Design Innovation for Workplace 4.0 is an exciting new programme at Maynooth University that will prepare graduates to design, implement and validate creative solutions to problems in the emerging digitally connected workplace; Workplace 4.0. Traditional manufacturing and industrial practices are being transformed by the integration of the latest smart technologies such as automation, Internet-of-things, big data and machine learning. As more small and medium-sized businesses are driven towards a digital transformation, the need for graduates who understand how to digitally enhance business offerings and operations is increasing.
This Postgraduate Diploma will future-proof graduates with a technical qualification and industry relevant skills to anticipate changes in the modern workplace and inform business strategy and innovations. Students on this programme will learn the innovation techniques of design thinking combined with big data analytics, and will cover foundational tools for computational thinking and problem solving in areas such as Artificial Intelligence and Machine Learning. Immersing students in workplace and strategic challenges, these skills will be developed through module work, team projects and collaboration with industry: enhancing graduate employability is at the core of this programme.
This is a one-year full-time conversion course for students who have completed a Level 8 degree (minimum 2:1) in any subject, such as in the Arts & Humanities. Applicants without a Level 8 degree and with relevant employment history can apply to the programme under MU’s Recognition of Prior Experiential Learning (RPEL) Policy. Graduates of this programme can find careers in technological orientated sectors, such as in manufacturing and the service industry. However, the skills developed over the course of this programme are transferable to many careers and working environments, and are highly sought after in all sectors of the economy.
Product R&D in service and manufacturing industries
This course will suit any future management trainee, and current managers wishing to keep abreast of new technology, and requiring an understanding of the digital workplace.
Classes are spread over the course of the full week.
Primarily on campus at Maynooth University but this course will have extended online elements due to the ongoing Covid-19 crisis.
Dr Linzi RyanAddress
Department of Design Innovation
Applicants also have the opportunity to apply through Recognition of Prior Experiential Learning. Please visit https://www.maynoothuniversity.ie/graduate-studies/recognising-professional-experience for further information and to download the RPEL form for inclusion in your application.
Please upload the following documentation with your application:
- Degree certificate and final transcript.Applicants looking to apply via RPEL can indicate this in their application, and should upload a completed RPEL form with their application submission. You do not need to include a PAC Number in this form.
- Proof of applicant category, e.g proof of employment, proof of DEASP payment, etc.
- Proof of nationality (unless in receipt of a DEASP payment or formerly self-employed)
- Evidence that you have been resident in an EU/EEA/Swiss state for three of the last five years (unless in receipt of a DEASP payment or formerly self-employed)