The Intelligent Systems MSc degree course is designed to give graduates the understanding, practical knowledge and expertise to evaluate, design and build intelligent systems using an extensive range of tools and techniques.
The Intelligent Systems MSc will prepare you for work developing intelligent control and engineering systems. You will study Artificial Intelligence, Agents and Multi-agent Systems, Pattern Recognition, Computer Vision and Biologically Inspired Methods. There are also opportunities to explore a broad range of optional modules allowing you the freedom to develop your study pathway to reflect your interests.
You will complete the course in one year, studying September to September and taking a combination of required and optional modules totalling 180 credits, including 60 credits that will come from an individual project of 15,000 words.
For graduates in engineering, computing or a related scientific discipline, with a good knowledge of computer programming and mathematics, from this programme you will gain specialist training in designing, building and evaluating intelligent systems using a range of tools and techniques in preparation for a career in research or industry.
Teaching
We use lectures, seminars and group tutorials to deliver most of the modules on the programme. You will also be expected to undertake a significant amount of independent study.
Assessment
The primary method of assessment for this course is a combination of written examinations, essays, coursework and individual or group projects and oral presentations. The research project will be assessed through a dissertation.
Our graduates have gone on to pursue successful careers in industry, commerce and academia.
As the need and scope for robots in all aspects of society grows, so does the market for those trained in Control and Systems Engineering, especially those with a background in Autonomous and Intelligent Systems.
The MSc in Autonomous and Intelligent Systems covers all major aspects of Control and Systems Engineering with an emphasis on system autonomy and intelligence. Autonomous systems is a fast changing area and has applications in a range of modern engineering disciplines including computer science, mechanical engineering, electrical and electronic engineering and materials science engineering.
Through lab work, you will get hands on experience of working with various types of autonomous and intelligent systems, and have the opportunity to build a system from scratch using the specialist labs in the University.
In your project dissertation, you will be able to pick an area you are passionate about and develop a solution to a real world problem in the area. You will be able to choose from a range of project ideas, including bionic systems, manufacturing lines, autonomous vehicles, or drones. You will get support from your project supervisor - an academic dedicated to helping you with your project - to complete your dissertation.
You could pursue a career with a large international organisation or government department. Our graduates work in sectors such as manufacturing, power generation and sustainable energy, with companies including British Airways, Jaguar Land Rover, NASA, IBM, Rolls-Royce and Unilever.
A masters from Sheffield is the mark of someone with the skills to apply their knowledge in industry, anywhere in the world. Our MSc in Advanced Control and Systems Engineering is accredited by the Engineering Council UK, IET and InstMC. These marks of assurance mean our degrees meet the high standards set by the engineering profession
A Sheffield masters is a strong foundation for a career in industry or research.
We have strong links with industrial partners such as Rolls-Royce and BAE Systems. Our industrial partners help us to design our courses, making sure you learn the right skills.
Rolls-Royce has a research and development centre here, using our expertise to explore today’s challenges. Our masters students often work side by side with researchers at these facilities.
The 2014 Research Excellence Framework (REF) rates us No 1 in the UK for research output, ahead of Oxford and Cambridge, and No 3 for overall research excellence. Our world-class reputation attracts highly motivated staff and students.
You’ll be taught by staff who work on real-world projects, developing new ideas – for submarines, robots, Formula One and even space exploration. Their approach to teaching is just as innovative: ideas like the award-winning take-home lab kit and e-puck mobile robotics activities help you develop the problem-solving skills you need for a trailblazing career.
· Multivariable Control Systems
· Agent based modelling and multi-agent systems
· Data modelling and machine learning
· Intelligent and Vision Systems
· Cybersecurity for Control Systems
Our teaching uses lectures, tutorials, laboratory work and individual assignments. All of the lectures and tutorials are just for our systems and control students. This means you form a unique bond as a cohort of colleagues and friends, learning together and from each other. Assessment is by examination, lab assignments, coursework and project dissertation.
As well as conventional labs, we have portable equipment that you can use to explore core concepts away from the normal teaching environment. It supports our teaching, giving you the chance to learn by doing, when you want to, not just in classes.
From software agents used in networking systems to embedded systems in unmanned vehicles, intelligent systems are being adopted more and more often. This programme will equip you with specialist knowledge in this exciting field and allow you to explore a range of topics in computer science.
Core modules will give you a foundation in topics like systems programming and algorithms, as well as the basics of machine learning and knowledge representation. You’ll also choose from optional modules focusing on topics like bio-inspired computing or text analytics, or broaden your approach with topics like mobile app development.
You’ll gain a broad perspective on intelligent systems, covering evolutionary models, statistical and symbolic machine learning algorithms, qualitative reasoning, image processing, language understanding and bio-computation as well as essential principles and practices in the design, implementation and usability of intelligent systems.
Specialist facilities
You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.
We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology.
This international Master’s programme gives insights into cutting edge resarch in robotics and artificial intelligence. The programme is centred around a "raise your robot" theme. You get access to a robot platform from day one, which you will give more and more advanced capabilities as the courses are progressing.
The programme is offered by the nationally and internationally renowned Centre for Applied Autonomous Sensor Systems (AASS) at Örebro University. As a student, you will be immersed in one of Sweden's largest academic research centres in robotics and intelligent systems. The outcomes of our ongoing international research projects feed into all of the courses. Vice versa, student projects and thesis works typically contribute to our research projects with industry partners.
This MSc focuses on state-of-the-art technologies for autonomous control and machine learning with applications in robotics, sensor networks, big data analytics, and autonomous agents.
Emphasis is given to topics that support a new emerging generation of self-sustaining and intelligent devices created for the Internet of Things, Ubiquitous Computing, and Industry 4.0 environments.
This degree is designed to provide a wide-ranging background in autonomous technologies that can be applied in a variety of disciplines.
In addition to traditional technologies related to robotics, embedded systems, design, and control, students will be exposed to system-level design methods and state-of-the-art theory behind some of the newest and most promising fields of artificial intelligence.
Applications include autonomous mobile systems, digital manufacturing, Big Data analytics, Internet of things device engineering, and artificial intelligence programming.
The MSc is delivered jointly by the Departments of Electronic & Electrical Engineering, and Design, Manufacture & Engineering Management.
This ensures you have access to academic leaders in the fields of machine learning, autonomous systems, digital manufacturing and design engineering.
You’ll take two semesters of compulsory and optional taught classes. These are followed by a three-month research project in your chosen area. Opportunities exist to do the project through the departments' competitive MSc industrial internships.
The internships are offered in collaboration with selected department industry partners. You’ll address real-world engineering challenges facing the partner, with site visits, access and provision of relevant technical data and/or facilities provided, along with an industry mentor and academic supervisor.
We’ve a wide range of excellent teaching spaces including interactive flexible learning spaces, and state-of-the-art facilities. Our Technology and Innovation Centre (TIC) is home to a number of world class labs where students will have an opportunity to undertake research projects in relevant areas. The University is also home to some key and relevant industry engagement research centres, including:
Interaction with industry is provided through our internships, teaching seminars and networking events. The departments deliver monthly seminars to support students’ learning and career development.
Xilinx, Texas Instruments, MathWorks, and Leonardo are just a few examples of the industry partners you can engage with during your programme of study.
We use a blend of teaching and learning methods including interactive lectures, problem-solving tutorials and practical project-based laboratories.
Our technical and experimental officers are available to support and guide you on individual subject material. Each module comprises approximately five hours of direct teaching per week.
To enhance your understanding of the technical and theoretical topics covered in these, you're expected to undertake a further five to six hours of self-study, using our web-based virtual learning environment (MyPlace), research journals and library facilities.
The teaching and learning methods used ensure you'll develop not only technical engineering expertise but also communications, project management and leadership skills.
A variety of assessment techniques are used throughout the course. Each module has a combination of written assignments, individual and group reports, oral presentations, practical lab work and, where appropriate, an end-of-term exam.
Assessment of the summer research project consists of four elements, with individual criteria:
Job titles include:
Employers include:
The MSc Machine Intelligence aims to equip students and engineering professionals through a diverse range of research informed learning, with the skills to maintain a future-thinking career. The programme goes beyond current technology, looking at predicting future innovation by equipping learners with the tools to see through media hype and effectively analyse the evolution of future technologies and engage with these technologies as they emerge.
Whether you're looking to deepen and diversify your industrial experience or continue your education through an innovative Master's degree, this programme provides an ideal opportunity to develop your technical and intellectual skills, staying one step ahead.
The programme provides the opportunity to explore: future technologies; robotics; cybernetics and intelligent systems; distributed systems; advanced design and ergonomics; securing future technologies; and future business thinking, all set within a forward-thinking context. This programme offers the opportunity to participate in a highly motivated intellectual environment with research-active tutors and like-minded peers, whilst exploring and engaging with cutting-edge future technologies.
The aims of the programme are to:
Assessments include examinations, coursework, group work and an individual project.
Postgraduate students from this programme will find employment opportunities as futurologists, engineers, scientists and technical managers in the private sector (engineering design firms, engineering consultancy, communications companies, social media companies and similar), in the public sector (local government, town and country planning), an entrepreneur or they may wish to pursue further qualifications such as a PhD within the Faculty of Engineering and Science at the University of Greenwich to become even more specialised. City banks, currency and stocks trading companies, consultancies, government agencies and NGOs will also be interested in employing the type of future orientated intelligent systems engineers that will graduate from this MSc.
Online resources: Students will require access to existing online resources such as Moodle, e-mails, library online resources, databases, Web of Knowledge, Scopus, Internet of Things, Internet of Everything.
Hardware: Computers, laboratory equipment to include but not limited to: experimental and laboratory equipment to support practical based learning (hardware and software development systems, robotic hardware, mobile robots, cybernetics hardware and software, Internet of Things, Sensors and Systems, WiFi development, 3D printers, laser cutters, 3D scanners, cutting edge single board computers)
Software: Matlab, Simulink, C/C++ compilers, development systems, networking and communication protocol monitoring and development.
Robotics: A specialist robotics laboratory has been developed containing a Robothespian industrial robotic arm, mobile robots and other robotic actuators and systems.
This course is designed in collaboration with transport industry partners to equip you to meet the needs of the rail and road industries. There is an increased demand for advancements in electrical, electronic, control and communication systems for transport, with a particular focus on themes like higher efficiency and sustainability, safety and driving assistance, position and traffic control for smart transport planning.
Modern electrical, electronic, control and communication systems for intelligent transport require today engineers with a combination of skills and solutions from cross-disciplinary abilities spanning electrical, electronic, control and communications. In this context, the overall aim of this Conversion Masters is to provide you with an enriching learning experience, and to enhance your knowledge and skill-base in the area of modern road vehicle and rail transport systems design.
This conversion course is intended both for engineers in current practice and for fresh honours graduates to facilitate their professional development, mobility and employability.
This course aims to enhance your knowledge and skills in the area of intelligent and efficient transport systems design. You will develop advanced practical skills that will help you determine system requirements, select and deploy suitable design processes and use the latest specialist tool chains to test and/or prototype a device or algorithm. The programme will help you acquire the cross-disciplinary skills and abilities that today are vital to be able to implement effective solutions for modern electrical, electronic and communication systems applied to intelligent transport. The broad range of disciplines covered by the course will enable you to enter a career that requires a cross-disciplinary approach with a practical skillset.
The subject areas covered within the course offer you an excellent launch pad which will enable you to enter into this ever expanding, fast growing and dominant area within the electrical engineering sector, and particularly in the area of intelligent and efficient transport systems. Furthermore, the course will provide the foundations required to re-focus existing knowledge and enter the world of multi-disciplined jobs.
Core Modules
The course provides the foundations required to re-focus existing knowledge and enter the world of multi-disciplined jobs. Graduates can expect to find employment, for example, as Electrical systems design engineers; Control systems engineers, Transport systems engineers; Plant control engineers; Electronic systems design engineer; Communication systems design engineers; Sensor systems engineers; Computer systems engineer. Examples of typical industries of employment can be: Transport; Automobile; Aviation; Electrical systems; Electronic systems; Assembly line manufacturers; Robotics and home help; Toy; Communication systems; Logistics and distribution; Consumer industry; Life-style industry; Security and surveillance; Petro-chemical.
Intelligent and autonomous systems are increasingly important in all areas of human life and activity from medicine and space exploration to agriculture and entertainment.
Understanding and developing autonomous systems involves a range of skills and knowledge including designing interactive systems with both human and machine elements, and modelling and building systems that can sense and learn.
Machine learning is at the heart of autonomous and intelligent systems, including computer vision and robotics. It also underpins the recent developments in data analytics across many fields.
You will learn to use new knowledge to solve complex machine learning and autonomous systems problems. You’ll develop a range of skills including the theory of machine learning, artificial intelligence, autonomous systems design and engineering, and the implications for humans of interacting more and more with intelligent and autonomous systems.
You will be taught by academics from the Department of Computer Science with expertise in machine learning, autonomous systems, artificial intelligence and human-computer interaction. This course has been designed in collaboration with the Department of Electronic and Electrical Engineering who offer expertise in robotics.
You will study in a research-led department with a supportive postgraduate community. You’ll learn in our bespoke computer laboratory and be exposed to the latest ideas and technology. The department has strong links to industry both nationally and internationally.
With machine learning and autonomous systems forming an essential part of a number of key industries, our MSc graduates will be highly sought after by employers.
You’ll gain the knowledge and transferable skills for a career in a wide range of industries, or for further study at PhD level. Graduates from the department have gone on to work in a wide variety of sectors, including IT consultancy, software development, banking and education.
The Department of Automatic Control and Systems Engineering (ACSE) at the University of Sheffield
