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.
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:
Visit the Autonomous Robotic Intelligent Systems MSc page on the University of Strathclyde website for more details!
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