Enhance your knowledge and expertise in computer science or electronics, and address the challenges in industry where machine learning techniques are being used increasingly in a wide number of applications. This course is supported by Intel’s AI Academy through their online and data processing resources.
Artificial intelligence and machine learning is a growing industry worldwide. Societies are adapting to the new technology landscape, becoming more flexible and also inheriting an attitude of lifelong learning, collaboration, innovation and entrepreneurship.
Using a range of skills from data science, to programming and hardware architectures that allow suitable artificial intelligence solutions to be produced and implemented, this course focuses on up-to-date theoretical and practical developments within machine learning, neural networks, signal processing and remote sensing and how these occur in the intelligent systems. It also allows you to become acquainted with current developments in artificial intelligence, and be able to apply yours skills in intelligent system design and development.
You will be trained in subjects that address the challenges of the current industry, studying modules that focus on data acquisition technologies and data processing techniques, including the development of AI systems, allowing you to become acquainted with digital signal processing, remote sensing and Internet of Things platforms, learning to program processors produced by ARM Ltd, a major player in the world of microelectronic component software/hardware design, based in Cambridge.
You will also explore neural networks and artificial networks, deep learning in Python using Scikit-learn, machine learning models and model evaluation using performance matrices, parametric and non-parametric algorithms or decision trees. Develop fundamental methods and algorithms that enable intelligent systems to interact with their environment through feedback, autonomously learn from data, and interconnect with each other to form collaborative networks, turning mathematical and theoretical insight into enhanced autonomy and performance of real-world physical systems. The practical skills gained help to prepare you for jobs related to intelligent systems and machine learning.
In most cases, artificial intelligence will have a supportive role to empower the human factor to perform better in handling complex and critical situations which require judgement and creative thinking.
Employment opportunities exist in vast areas and postgraduates typically follow careers in internet businesses, financial services, control systems, software engineering, mobile communications, programming and many more.
Throughout the course, we’ll use a range of assessment methods to measure your progress. You’ll complete exams, essays, research reports, oral presentations, and a dissertation on a subject of your choice.
The Faculty of Science & Engineering is one of the largest of the four faculties at Anglia Ruskin University. Whether you choose to study with us full-time or part-time, on campus or at a distance, there’s an option whatever your level – from a foundation degree, BSc, MSc, PhD or professional doctorate.
Whichever course you pick, you’ll gain the theory and practical skills needed to progress with confidence. Join us and you could find yourself learning in the very latest laboratories or on field trips or work placements with well-known and respected companies. You may even have the opportunity to study abroad.
Everything we do in the faculty has a singular purpose: to provide a world-class environment to create, share and advance knowledge in science, technology and engineering fields. This is key to all of our futures.
You can pay your fees upfront, in full or in instalments – though you won't need to pay until you've accepted an offer to study with us. This information also applies to EU students starting a course in the 2020/21 academic year.How to pay your fees directly
You can pay your fees upfront, in full or in two instalments. We will also ask you for a deposit of £4,000 or a sponsorship letter. Details will be in your offer letter.Paying your fees
It’s important to decide how to fund your course before applying. Use our finance guide for postgraduate students to learn more about postgraduate loans and other funding options.
We offer a fantastic range of ARU scholarships and bursaries, which provide extra financial support while you're at university.
Whether you're studying entirely online or through a blend of on-campus and online learning in September 2020, you'll need a computer and reliable internet access to successfully engage with your course. A small number of our courses require additional technical specifications or specialist materials. Before starting the course, we recommend that you check our technical requirements for online learning. Our website also has general information for new students about starting university in September 2020.
Our published entry requirements are a guide only and our decision will be based on your overall suitability for the course as well as whether you meet the minimum entry requirements. Other equivalent qualifications may be accepted for entry to this course, please email firstname.lastname@example.org for further information.
We welcome applications from international and EU students, and accept a range of international qualifications.
Whether you're studying entirely online or through a blend of face-to-face and online learning in September 2020, you'll need a computer and reliable internet access to successfully engage with your course. Before starting the course, we recommend that you check our technical requirements for online learning.
If English is not your first language, you'll need to make sure you meet our English language requirements for postgraduate courses.
If you don't meet our English language requirements, we offer a range of courses which could help you achieve the level required for entry onto a degree course.
Full-time, full-time with placement postgraduate ()
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