Skip to content

Artificial Intelligence MSc Courses Queen’s University Belfast

Artificial intelligence AI data specialist level 7

ai engineer degree

Artificial Intelligence (AI) is increasingly successful in solving complex and key problems from self-driving cars and medicine to information retrieval and gaming. Recent advances exploit machine learning techniques where AI systems extract patterns from vast amounts of examples (big data) using large-scale computing infrastructure, such as the cloud. On the BSc Artificial Intelligence you’ll specialise in this rapidly evolving area of computer science.

This module will cover classical and modern knowledge engineering techniques including logic, ontology, knowledge graph, and uncertainty reasoning. This course will provide students of our MSc in AI programme with the opportunity to develop their own AI research project, under the supervision of a member of staff. Typical projects include extending, improving or adapting existing AI theories or techniques to solve different problems, comparing competing techniques or tools to solve a particular problem, and ai engineer degree so on. Students will improve their problem-solving and communication skills, as well as broaden, deepen and consolidate knowledge obtained in other components of the degree. You will be encouraged and supported in the creation of a portfolio to record aspects of your academic and personal skills. The module also identifies and explores ethical, legal, communication, and other non-technical factors that contribute to the success (or failure) of the development of IT systems in a professional environment.

Mechanical Engineering MEng/BEng (Hons)

This course presents the fundamental techniques of Artificial Intelligence, used in system such as Google Maps, Siri, IBM Watson, as well as industrial automation systems, and which are core to emerging products such as self-driving vehicles. This course will equip the student to understand how such AI technologies operate, their implementation details, and how to use them effectively. This course therefore provides the building blocks necessary for understanding and using AI techniques and methodologies. Spin-out successes from the University of Aberdeen include ARRIA NLG, one of the world’s leading natural language generation companies. David’s expertise focuses on control engineering, electrical circuit analysis, analogue electronics and hardware-based digital electronics.

ai engineer degree

We’ve witnessed improvements in everything from computer vision through speech analysis to natural language processing as a result of the advent of cheap GPGP… This module covers the mathematics, techniques, and applications of modern cryptography. We will look at the history of code making and code breaking, and draw lessons for the future from the mistakes and successes of the past. Through the abstraction of design principles from biological systems, it is possible to develop a range of core competences, including mechatronic systems, sensor and actuator technologies. In fact, at this stage in its development, there are more people needed to fill related roles than there are with the qualifications required.


The computer science modules teach advanced topics, including cyber security and software design, as well as core topics, such as object-oriented programming and database and web application development. The other two modules teach artificial intelligence and machine learning and deploying software with machine learning operations. In the last decade the advances in Artificial Intelligence have made it at the forefront of technology, with many advances improving our daily lives.

You will also be able to use the University’s facilities, including libraries and common student spaces. You will also attend classes in the Nucleus building at the King’s Buildings campus. The King’s Buildings campus is around 15 minutes by bus from the Central Campus.

In addition, the module discusses examples of computation applied to neurobiology and cognitive psychology. During your degree you’ll work on real projects for real clients as part of core and optional modules. That means outstanding facilities, study spaces and support, including 24/7 online access to our online library service. It examines both the production and perception of speech, taking a multi-disciplinary approach (drawing on linguistics, phonetics, psychoacoustics, etc.). It introduces sufficient digital signal processing (linear systems theory, Fourier transforms) to motivate speech parameter extraction techniques (e.g. pitch and formant tracking). Have a look at our careers page for an overview of all the employability support and opportunities that we provide to current students.

  • UDL means we offer a wide variety of support, facilities and technology to all students, including those with disabilities and specific learning differences.
  • Specific advice is also available for international students about the UK job market and employers’ expectations and requirements.
  • At Essex we pride ourselves on being a welcoming and inclusive student community.
  • If you are taking a joint degree, you will also have to take compulsory courses in your second subject.
  • This programme aims to give a well-integrated balance of theoretical underpinnings and practical experience, strongly informed by the research expertise of our academic staff.
  • The module also aims to specify and discuss the problems of image understanding and of various computer vision applications.

The emphasis is placed on design of analogue functions specifically as part of… This module provides an introduction to intensive group project work in collaboration with an industrial or academic customer. Students work in groups of at least four people on a project typically based on an idea from an industrial partner, or from an a… To introduce the student to the concepts of programming using the C programming language, with an emphasis on programming for embedded systems. To embed an understanding of Object Oriented development and grow specific skills in using C++ in a variety of situations.

Is AI hard to study?

Contrary to the popular misconception, AI isn't complicated or hard to learn. But you must have a knack for programming, mathematics, and statistics to grasp the fundamental concepts. These skills will empower you to analyse data, develop efficient algorithms, and implement AI models.

Leave a Reply

Your email address will not be published. Required fields are marked *