Course Content
Compulsory modules:
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Advanced AI in Robotics (20 credits)
The module aims to provide students the advanced artificial intelligence (AI) knowledge and practical skills at the intersection of robotics and intelligent systems.
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3D Bio-Inspired Robot Design (20 credits)
This module provides students with the opportunity to gain experience and develop skills in bio-inspired design for robotics and robotic aesthetics, grounded on human-centered design research approach and rapid prototyping method.
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Mobile Robotics (20 credits)
The module aim is to provide students with the foundation of autonomous mobile robotic including aspects such as mapping, navigation, planning and localisation. It also aims to introduce students the algorithmic strategies that enable the coordination of multi-robot systems and robot swarms.
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Applications for Social and Service Robots (20 credits)
The module aims to provide students the advanced knowledge and applications for social and service robotics, an interdisciplinary field incorporating taxonomy of robots, from the current research and design to the real-world implementation.
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Vision with Deep Learning (20 credits)
This module aims to provide students with the basic knowledge of combining robotics and deep learning.
- Research & Professional Practice (20 credits)
The aim of this module is to equip the student with the skills, knowledge, and techniques necessary to produce a technology related dissertation with a research or technical focus.
- Technology Dissertation (40 credits)
The aim of the technology project is for the student to apply knowledge, skills and techniques developed during directed and independent study to solve a real-world technology related project.
Optional modules:
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Sensors and Actuators (20 credits)
This module will introduce the broad spectrum of activities that comprise robotic and electronic engineering, and the analytical methods needed to support it.
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Frontiers in Technology (20 credits)
The purpose of the module is to provide students with knowledge and understanding of emerging and future developments in the field of technology, as well as a critical understanding of contemporary Ethical, Digital, Global and Entrepreneurial competencies and their application to ‘real world’ technology research.
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Programming for Data Analysis (20 credits)
The aim of this module is to help students to develop an understanding of programming and problem-solving strategies, as well as to develop, analyse and critically assess solutions to real-world data analysis problems.
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Information Security (20 credits)
This module aims to provide an insight into the implementation of data security in computer systems and to encourage students to appreciate the practical and theoretical management principles associated with information security.
To obtain an MSc degree, you must follow and successfully complete a total of 180 credits. PgC (60 credits) and PgD (120 credits) may be awarded as standalone or exit awards.
Learning & Teaching
A range of teaching methods are used in the Cardiff School of Technologies, including lectures, practical workshops, tutorials, seminars and real-world case studies, all supported by online learning via Moodle. With a student-centred approach, the School operates an open-door policy to staff to support students, along with support from our careers team and academic skills.
Studios
Studios are a major part of the teaching strategy for the programme. Studios are an interactive and effective way of delivering core material and establishing a framework for a module against which other material can be set.
Workshops
Workshops involve a student or students working more actively to understand the topic of study. This can include strategies such as presenting previously prepared work to peers and a lecturer. In these classes students are able to practise and refine their skills in a supportive environment where they can receive feedback from a member of academic staff. Practical workshops represent a valuable transition between theory and the workplace.
Workshops are used to extend specific theoretical or practical concepts as well as introducing problem solving exercises. Workshops are used in most modules and provide students with valuable experience in practical and presentational skills as well as providing staff with a method of assessing student-centred learning.
Case Studies
Case studies are a teaching and learning strategy, employed in a range of modules; they also are a useful assessment tool. Students are presented with or asked to develop real or simulated complex problems which they are required to analyse in detail and then synthesise/present their own solution in writing or orally.
Moodle
The majority of modules will be supported by Moodle and provide students with a wide range of learning material and study guidance.
Additional Information
A student-centred approach to learning and teaching is encouraged through the use of a broad range of teaching strategies, such as technical labs and individual and group projects. Due to the nature of the programme, online and campus-based practical workshops are key to developing students’ technical understanding and abilities, underpinned by solid theoretical expertise. Students are expected to further develop their knowledge and understanding through directed self-study and reflective independent learning time - in additional to the timetabled delivery.
Students have the opportunity to experience state-of-the-art facilities and specialist equipment in the EUREKA Robotics Centre – such as humanoid service robots, an industrial-grade robotic arm, and 3D printers with advanced applied artificial intelligent features.
Short Term Mobility and ERASMUS+ opportunities are available for students to apply for field trips to countries such as China, Malaysia and the EU to build a robotics career network and gain knowledge and insights from international global robotics leaders. An industrial panel and partners of the EUREKA Robotics Centre support the industrial standard of curriculum design and in addition, partners are invited to deliver guest lectures and contribute to assessment and feedback.
Students are also encouraged to publish their work on blogs, EUREKA Robotics website, robotics apps stores, social media & press, and academic conferences to exchange knowledge and share learning & research outcomes. Critical peer review or expert reviews will be the development process towards generating new robotics design, problem solving, error debugging and failure recovery.
Students are supported academically and pastorally by the Programme Team, led by the Programme Director. Each student is also appointed a Personal Tutor from within the School, who provides a point of contact for general academic and pastoral issues. The EDGE (Ethical, Digital, Global and Entrepreneurial) educational environment is embedded into every module, and most senior academic staff are Fellows of the Higher Education Academy (HEA) and Chartered IT Professionals (to-be) with real-world industry experience, coupled with the UK’s world-class quality of teaching.
Assessment
Assessments take the form of research papers, practical assignments, presentations, individual and group reports, as well as individual and team projects. Through the use of formative assessment with frequent, short-term feedback early in the course and during the weekly workshops, presentations, class-based peer assessment and academic support in library, the assessment strategy is designed to encourage students and to build their confidence.
Summative feedback will be given in the consistent form on Moodle and Turnitin-GradeMark Feedback Studio, with the variety features of rubrics, in-text and general feedback.
In designing the assessment format for modules of the MSc in Robotics and AI, the following factors are considered:
- The module learning outcomes at postgraduate level, with particular emphasis on the student’s ability to analyse, synthesise, evaluate and communicate information derived from module content; learned knowledge from other areas/qualifications; work experience; Independent systematic information-seeking strategies.
- Assessment performance criteria.
- Encouraging students to apply their skills to specific real-world computing and technology problems.
- The validity and reliability of the assessment methods, which are monitored and verified by module leaders, field groups and programme teams.
- The need for assessment to allow for review and reflection by the student.
Employability & Careers
The need for trained experts in Robotics and Artificial Intelligence is growing globally.
The learning, teaching, assessment and feedback of the MSc in Robotics and AI are designed to develop a professional portfolio of project work and robotics & AI artefacts as students move into graduate employment.
This innovative programme is built with emphasis on work-based learning towards employability, ethical and social entrepreneurship. It aims to develop professionals and entrepreneurs with a global knowledge of a wide range of robotics and AI theories and scientific applications through the lenses of social entrepreneurship.
Opportunities for short term mobility and internships will provide an enhanced learning experience and a portfolio of real-world projects that graduates can take into their chosen careers.
Entry Requirements & How to Apply
Applicants should have an Honours degree at least 2:2 or its equivalent in a relevant area, e.g., Robotics, Artificial intelligence, Computer Science, Information Systems, Mathematics or an appropriate Engineering specialism.
Programming skills in Python/Java/C/C++ are highly desirable.
Relevance shall be determined by the Programme Director with reference to the applicant’s transcript, and, if required, via an interview. Other disciplines will be considered on a case-by-case basis.
Equivalence shall be determined by:
- International Admissions Team for applicants from outside the United Kingdom.
- The Programme Director for applicants who present professional qualifications such as from the BCS. Such an applicant would be interviewed by the Programme Director to establish suitability.
English Language Requirements:
Applicants whose first language is not English should refer to English Language Requirements to confirm the level and evidence of fluency required for entry to the programme.
Students with extant level 7 qualifications wishing to enter the course may apply on the basis of RPL for admission with Credit. In such cases the regulations detailed in the Academic Handbook will apply and allows for a maximum RPL of 120 credits on a Master’s programme. In this case the remaining 60 credits would consist of the research methods module and the dissertation.
The admissions process is controlled by Cardiff Metropolitan University’s centralised admissions team in consultation with the Programme Director.
All applications from International students will be subject to an initial assessment of academic qualifications, English Language proficiency and overall suitability for the programme by the International Admissions Teams. However, the final decision remains the responsibility of the Programme Director.
How to Apply:
Applications for this course should be made direct to the University via our
self-service facility. For further information please visit our How to Apply pages at
www.cardiffmet.ac.uk/howtoapply.
Additional Information
International Applicants:
Before making an application, international students should contact the International Office at Cardiff Met to discuss the necessary procedures in relation to studying with us. For further information visit
www.cardiffmet.ac.uk/international.
Tuition Fees and Financial Support:
For up to date information on tuition fees and the financial support that may be available. Please refer to
www.cardiffmet.ac.uk/fees.
Part-time fees:
Charges are per Single Module unless specified:
Undergraduate = 10 Credits; Postgraduate = 20 Credits
Generally we find most students will complete 60 credits per year for both Undergraduate and Postgraduate study; to obtain a true costing please clarify this by contacting the Programme Director directly.
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