Computer Science Artificial Intelligence, BSc Hons University of Greenwich, London

This module introduces the Software Engineering concepts that are needed to develop software systems that can meet basic functional requirements within a given problem domain. It covers the main steps in the process of developing such systems, from requirements analysis through to their implementation and testing. A major part of the module involves students working in teams to develop a web-based software system, which gives practical experience in teamwork and managing software projects and their products.

We offer a range of options specific to artificial intelligence and other courses in informatics. You will build on Year 1, covering more advanced programming and data structures, together with the related mathematics and broader professional and societal issues. All of our ai engineering degree programmes start with a common core of mathematics courses and informatics courses, with increasing choices for specialisation in later years depending on your interests. If you are taking a joint degree, you will also have to take compulsory courses in your second subject.

The University of Edinburgh

SDIPs aims to improve business processes and support the development of new to market products and services using innovative digital technologies. Studying Artificial Intelligence (AI) and Robotics enables you to experience a comprehensive degree in the multi-discipline areas of computing, software, robotics, autonomous vehicles (automotive) and 3D games design. Postgraduate students who are ordinarily resident in Northern Ireland may be able to apply for support from Student Finance Northern Ireland. We offer comprehensive English language courses for students whose IELTS scores are below 6.0. This module focuses on implementing AI algorithms and building autonomous systems.

• The first year of the programme provides you with a firm foundation in mathematics, computer science and general engineering.
• This means students can revise taught material in a way that suits them best, whether it’s replaying a recording of a class or adapting written material shared in class using specialist software.
• We welcome applications from students studying a wide range of international qualifications.
• If you are considering bringing your own computer, most of the software we use is on Windows machines though there is some use of Linux.

The module provides access to effective commercial development environments and ensures students have practical awareness of computer systems requirements. Students are required to meet strict deadlines, and to manage and plan their overall workload. Teaching and supervision on the course is undertaken by experienced academic staff who understand the value of your knowledge development applied to commercial and industrial contexts. You will find all our staff have extensive industrial or research-based backgrounds. Our philosophy is that of applied scholarship – thus, our approach to education is based on research-informed teaching that has direct value to industry and commerce and is of direct value to you as a professional in the IT industry. You can be confident therefore, that you will be part of an academic community that understands the value of research and knowledge creation, the impact of computing education, and the significance of its application to the world we live in.

More flexible ways to learn

We will consider students who have taken GCE A Level examinations or the International Baccalaureate (IB) for entry onto our undergraduate programmes. Holders of the Tawjihiyya are not usually eligible for direct entry onto our undergraduate courses without completion of a suitable foundation programme, such as one of our foundation pathways. We will https://www.metadialog.com/ consider students who have taken GCE A Level examinations or the International Baccalaureate (IB) for entrance to onto our undergraduate programmes. Holders of the Thanewiyah are not normally eligible for direct entry onto our undergraduate courses without completion of a suitable foundation programme, such as one of our foundation pathways.

You’ll specialise in artificial intelligence and knowledge engineering, as well as machine learning and the development of computational and engineering models of complex cognitive and social behaviours. The third year will enhance the knowledge of dynamics and system theory through the study simulation, control, dynamics and communications, which are crucial in the study of robotics. You will study advanced programming and software engineering as the basis for the artificial intelligence theme. In addition you will study power engineering and electromagnetic compatibility which are essential for any robotic system. This four-year course includes a foundation year (Year Zero), followed by a further three years of study. During your Year Zero, you study four academic subjects relevant to your chosen course as well as a compulsory English language and academic skills module.

Computer science at the University of Greenwich

This module provides an introduction to machine learning techniques, ranging from supervised learning, unsupervised learning, and deep learning. Also included are the evaluation metrics and procedures of various learning methods. The module focuses on classification and regression learning tasks and their applications to real-world problems. Computers, embedded systems, and digital systems in general have become an essential part of most people’s lives, whether directly or indirectly. The aim of this module is to introduce the software and hardware underpinnings of such systems at an introductory yet challenging level suitable for future computer scientists and engineers. Topics covered in the module include both top-view as well as bottom-view approaches to understanding digital computers.

You can progress onto a range of postgraduate studies, including (but not limited to) an MSc in disciplines concerning Computer Science, Artificial Intelligence, Data Science, Software Engineering, and Computer Games. You will learn of range of skills which will be key to enhancing your future employability. This module is intended as a theoretical and methodological introduction to the most widely used and effective current techniques, strategies, and toolkits for natural language processing. Natural Language Processing (NLP) is a rapidly developing field with broad applicability throughout the hard sciences, social sciences, and the humanities. The ability to harness, employ and analyse linguistic and textual data effectively is a highly desirable skill for academic work, in government, and throughout the private sector. Deep learning (also called deep neural network) is a sub-field of Artificial Intelligence (AI), aiming at extracting knowledge automatically from large data sets in a hierarchical way.