If you want to get involved in our next industry revolution - Industry 4.0 this degree will go a long way to providing you with many skills needed in this high growth industry area which has continued from where the mass communications revolution. You must have covered either computer science or electrical and electronic engineering as your first degree or a suitable combination to study this Master's degree. The digital age is changing the way we live, communicate, interact and our quality of life rapidly. Cloud based networks are now normal, autonomous vehicles are being explored, visual recognition, GIS aligning to our search interests, data mining to inform us automatically at any point in time what is happening around us and new methods to inform us of danger, awareness, alerts and so on.
Artificial Intelligence provides in depth knowledge of data mining, natural language, information visualisation and communication used in Industry 4.0 innovation industries such as autonomous vehicles, sensor data collection and computation, visual computer recognition software and machine to machine technologies. It is also said that artificial intelligence has the potential to change how we research and act to provide immediate solutions to energy, travel, and gridlock before it happens by setting up more alerts and warnings to us. We now already have the capabilities in smart technology to alert us on maps, apps, weather stations, lighting, sensors and other electronic and wired machine to machine devices to provide instant relevant information.
You are also advised to visit the organisation websites via the link below to find out about the innovations which may be influenced by AI:
Scottish Innovation Centres - http://www.innovationcentres.scot/
SEMESTER 1
Compulsory Courses
Foundations in AI
Machine Learning
Evaluation Systems of AI Systems
Engineering of AI Systems
SEMESTER 2
Compulsory Courses
Data Mining and Visualisation
Natural Language Generation
Software Agents and Multi-Agent Systems
Knowledge Representation and Reasoning
SEMESTER 3
You can broaden and deepen your skills with industry client opportunities where possible
Find out more detail by visiting the programme web page
https://www.abdn.ac.uk/study/postgraduate-taught/degree-programmes/1034/artificial-intelligence/
Find out about fees:
https://www.abdn.ac.uk/study/international/tuition-fees-and-living-costs-287.php
*Please be advised that some programmes have different tuition fees from those listed above and that some programmes also have additional costs.
View all funding options on our funding database via the programme page
https://www.abdn.ac.uk/study/postgraduate-taught/finance-funding-1599.php
https://www.abdn.ac.uk/funding/
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Find out more about living in Aberdeen:
https://abdn.ac.uk/study/student-life
Living costs
https://www.abdn.ac.uk/study/international/finance.php
You may also be interested in:
Investigating the true nature of intelligence is one of today’s most fascinating research avenues. Advances in the study of cognitive processes and models, natural language and perception, human knowledge, representation, and reasoning attest to this. One of the scientific community’s key research objectives is the development of an intelligent robot. The Master of Artificial Intelligence explores and builds on this challenge, will you?
The Master of Artificial Intelligence programme at KU Leuven explores and builds on these fascinating challenges. For many years, it has provided an internationally acclaimed advanced study programme in artificial intelligence. The multidisciplinary programme trains students from a variety of backgrounds - including engineering, sciences, economics, management, psychology, and linguistics - in all areas of knowledge-based technology, cognitive science, and their applications. The one-year programme, taught entirely in English, is the result of a collaboration between many internationally prominent research units from seven different faculties of the university. It allows you to focus on engineering and computer science, cognitive science, or speech and language technology.
The AI program aims at instructing and training students on state of the art knowledge and techniques in Artificial Intelligence, with specific focus either on Engineering and Computer Science (ECS), on Speech and Language Technology (SLT) or on Big Data Analytics (BDA), depending on the selected option within the program. It aims at introducing the students to the concepts, methods and tools in the field.
It aims at instructing students on the achievements in a number of advanced application areas and make them familiar with their current research directions. It aims to bring students to a level of knowledge, understanding, skills and experience that are needed to actively conduct basic or applied research on an international level. In particular, it aims to provide students with a critical scientific attitude towards the central themes of A.I.
As a master-after-master program, it is assumed that the students entering this program have already achieved the general skills and attitudes defined for any master program. Nevertheless, it is also within the aims of the program to further strengthen the skills and attitudes, within the specific scientific context that AI offers.
ECS-option: In the ECS option, in addition to the above, the program aims at instilling a problem-solving attitude towards the practice of AI. Upon completion of the program, students should be familiar with the fundamentals of AI, be aware of its reasonable expectations, have practical experience in solving AI-problems and be acquainted with a number of advanced areas within the field.
SLT-option: In the SLT-option, in addition to the general aims, the program aims to provide all necessary background and skills which are required to fully understand and to actively participate in the fast developing multi-disciplinary field of Language and Speech. This includes a thorough understanding of the theories and models that shape the field, as well as practical experience with a variety of technologies that are used and currently developed.
BDA-option: In the BDA-option, in addition to the general aims, the program aims for the same additional goals as the ECS-option, but specialized to Big Data Analytics. In particular, it aims at instilling a problem-solving attitude towards the practice of Big Data Analytics. Upon completion of the program, students should be familiar with the fundamentals of Big Data Analytics, be aware of its reasonable expectations, have practical experience in solving BDA-problems and be acquainted with a number of advanced areas within the AI-subfield of BDA.
With a Master's degree in artificial intelligence you will be welcomed by companies working in:
Information technology
You will also be qualified to work in banking or provide support for the process industry, biomedicine and bioinformatics, robotics and traffic systems. Some graduates go on to begin a PhD programme.
At the Centre for Intelligent Systems and their Applications (CISA) we enable computer systems to reproduce or complement human abilities, work with people, and support collaboration between humans. We conduct world-leading research in the foundations of Artificial Intelligence (knowledge representation and reasoning, emergence of meaning, theory and ontology change, creativity, mathematical proof) and in intelligent collaborative systems (multiagent systems, social computation, scientific collaboration platforms, web semantics and linked data).
Our research methods are inspired by developing formal models of knowledge, reasoning, and interaction that can be used to understand and automate aspects of human intelligence, but are also understandable and usable to the human designers and users of AI systems.
To achieve this, we combine theoretical research into computational models, architectures, and algorithms with a strong element of applied research. This has led to a strong track record in using our methods to address real-world problems in healthcare, scientific collaboration, social computing, emergency systems, transportation, engineering, aerospace and others.
You'll find a wide range of research areas within CISA conducted in the four research groups the Institute currently hosts:
CISA includes one of the most innovative collaborations between research and business - our Artificial Intelligence Applications Institute (AIAI). Through its resources and the engagement of CISA staff and students in consultancy, training and joint projects, we help companies and government agencies to apply newly researched techniques.
You will carry out research work within a research group under the guidance of a supervisor. You may also attend taught courses that are relevant to your research topic, as prescribed by your supervisor. You will be expected to attend seminars and meetings of relevant research groups. Periodic reviews of progress are conducted to assist with research planning.
A programme of transferable skills courses facilitates broader professional development in a wide range of topics, from writing and presentation skills to entrepreneurship and career strategies.
The School of Informatics holds a Silver Athena SWAN award, in recognition of our commitment to advance the representation of women in science, mathematics, engineering and technology. The School is deploying a range of strategies to help female staff and students of all stages in their careers and we seek regular feedback from our research community on our performance.
The award-winning Informatics Forum is an international research facility for computing and related areas. It houses more than 400 research staff and students, providing office, meeting and social spaces.
It also contains two robotics labs, an instrumented multimedia room, eye-tracking and motion capture systems, and a full recording studio amongst other research facilities. Its spectacular atrium plays host to many events, from industry showcases and student hackathons to major research conferences.
Nearby teaching facilities include computer and teaching labs with more than 250 machines, 24-hour access to IT facilities for students, and comprehensive support provided by dedicated computing staff.
Among our entrepreneurial initiatives is Informatics Ventures, set up in 2008 to support globally ambitious software companies in Scotland and nurture a technology cluster to rival Boston, Pittsburgh, Kyoto and Silicon Valley.
While your research studies are a perfect route to a career in academia, your degree could also take you into the commercial world of applied AI and collaborative systems.
Software developers using AI technologies are among those who rely on the insights of our research. NASA and animation company Pixar are just two of the organisations that have recently employed our graduates.
This programme is studied full-time over one academic year and part-time students must study at least two taught technical modules per academic year. It consists of eight taught modules and a standard project.
Example module listing
The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.
To support your learning, we hold regular MSc group meetings where any aspect of the programme, technical or non-technical, can be discussed in an informal atmosphere. This allows you to raise any problems that you would like to have addressed and encourages peer-based learning and general group discussion.
We provide computing support with any specialised software required during the programme, for example, Matlab. The Faculty’s student common room is also covered by the University’s open-access wireless network, which makes it a very popular location for individual and group work using laptops and mobile devices.
Specialist experimental and research facilities, for computationally demanding projects or those requiring specialist equipment, are provided by CVSSP.
The taught postgraduate Degree Programmes of the Department are intended both to assist with professional career development within the relevant industry and, for a small number of students, to serve as a precursor to academic research.
Our philosophy is to integrate the acquisition of core engineering and scientific knowledge with the development of key practical skills (where relevant).
To fulfil these objectives, the programme aims to:
Intended capabilities for MSc graduates:
This programme in Mobile Media Communications aims to provide a high-quality advanced training in aspects of multimedia signal processing for audio and video content production, processing and transmission.
The programme examines ways that relevant digital data can be captured or generated, and the digital streams processed, compressed, analysed and communicated over broadcast channels, mobile networks or internet.
Along with a basis of image, video and audio processing, it provides a grounding in communications related elements that include, for example, coding, networking and data transmission. Students will be able to tailor their learning experience through selection of elective modules to suit their career aspiration.
Key to the programme is cross-linking between signals, and delivery of audio and video content. The Programme has strong links to current research in the Department of Electronic Engineering’s Centre for Vision, Speech and Signal Processing.
We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.
In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.
Medical imaging is a rapidly-growing discipline within the healthcare sector, involving clinicians, physicists, computer scientists and those in IT industries.
This programme delivers the expertise you'll need to forge a career in medical imaging, including radiation physics, image processing, biology, computer vision, pattern recognition, artificial intelligence and machine learning.
This programme is studied full-time over 12 months and part-time over 48 months. It consists of eight taught modules and an extended project.
Example module listing
The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.
To support your learning, we hold regular MSc group meetings where any aspect of the programme, technical or non-technical, can be discussed in an informal atmosphere. This allows you to raise any problems that you would like to have addressed and encourages peer-based learning and general group discussion.
We provide computing support with any specialised software required during the programme, for example, Matlab.
The Department’s student common room is also covered by the university’s open-access wireless network, which makes it a very popular location for individual and group work using laptops and mobile devices. There is also a Faculty quiet room for individual study.
We pride ourselves on the many opportunities that we provide to visit collaborating hospitals. These enable you to see first-hand demonstrations of medical imaging facilities and to benefit from lectures by professional practitioners.
To support material presented during the programme, you will also undertake a selection of ultrasound and radiation detection experiments, hosted by our sister MSc programme in Medical Physics.
The taught postgraduate Degree Programmes of the Department are intended both to assist with professional career development within the relevant industry and, for a small number of students, to serve as a precursor to academic research.
Our philosophy is to integrate the acquisition of core engineering and scientific knowledge with the development of key practical skills (where relevant).
To fulfil these objectives, the programme aims to:
Medical Imaging is a rapidly growing discipline within the healthcare sector, incorporating engineers, physicists, computer scientists and clinicians. It is driven by the recent rapid development of 3-D Medical Imaging Systems, fuelled by an exponential rise in computing power.
New methods have been developed for the acquisition, reconstruction, processing and display of digital medical-image data with unprecedented speed, resolution and contrast.
This programme in Medical Imaging is aimed at training graduates for careers in this exciting multi-disciplinary area, and our graduates can expect to find employment in the medical imaging industry or the public health care sector.
It represents a blend of fundamental medical physics topics concerned with image acquisition and reconstruction coupled with imaging science and image engineering topics such that graduates understand how images are formed and how advanced machine-based methods can be bought to bare to provide new diagnostic information.
We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.
In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.
This degree provides in-depth training for students interested in a career in industry or in research-oriented institutions focused on image and video analysis, and deep learning.
State-of-the-art computer-vision and machine-learning approaches for image and video analysis are covered in the course, as well as low-level image processing methods.
Students also have the chance to substantially expand their programming skills through projects they undertake.
Read about the experience of a previous student on this course, Gianmarco Addari.
This programme is studied full-time over 12 months and part-time from 24 to 60 months. It consists of eight taught modules and a standard project.
Example module listing
The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.
This programme in Computer Vision, Robotics and Machine Learning aims to provide a high-quality advanced training in aspects of computer vision for extracting information from image and video content or enhancing its visual quality using machine learning codes.
Computer vision technology uses sophisticated signal processing and data analysis methods to support access to visual information, whether it is for business, security, personal use or entertainment.
The core modules cover the fundamentals of how to represent image and video information digitally, including processing, filtering and feature extraction techniques.
An important aspect of the programme is the software implementation of such processes. Students will be able to tailor their learning experience through selection of elective modules to suit their career aspirations.
Key to the programme is cross-linking between core methods and systems for image and video analysis applications. The programme has strong links to current research in the Department of Electronic Engineering’s Centre for Vision, Speech and Signal Processing.
To support your learning, we hold regular MSc group meetings where any aspect of the programme, technical or non-technical, can be discussed in an informal atmosphere. This allows you to raise any problems that you would like to have addressed and encourages peer-based learning and general group discussion.
We provide computing support with any specialised software required during the programme, for example, Matlab. The Faculty’s student common room is also covered by the University’s open-access wireless network, which makes it a very popular location for individual and group work using laptops and mobile devices.
Specialist experimental and research facilities, for computationally demanding projects or those requiring specialist equipment, are provided by the Centre for Vision, Speech and Signal Processing (CVSSP).
Computer vision specialists are be valuable in all industries that require intelligent processing and interpretation of image and video. This includes industries in directly related fields such as:
Studying for Msc degree in Computer Vision offers variety, challenge and stimulation. It is not just the introduction to a rewarding career, but also offers an intellectually demanding and exciting opportunity to break through boundaries in research.
Many of the most remarkable advancements in the past 60 years have only been possible through the curiosity and ingenuity of engineers. Our graduates have a consistently strong record of gaining employment with leading companies.
Employers value the skills and experience that enable our graduates to make a positive contribution in their jobs from day one.
We draw on our industry experience to inform and enrich our teaching, bringing theoretical subjects to life. Our industrial collaborations include:
This course gives an excellent preparation for continuing onto PhD studies in computer vision related domains.
We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.
In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.
Application period/deadline: November 1, 2017 - January 24, 2018
• Research-oriented degree provides an exciting opportunity to study in a leading-edge research environment
• The studies combine both theoretical and practical approach
• Specializations in Applied Computing, Artificial Intelligence, and Computer Egineering
The International Master’s Degree Programme in Computer Science and Engineering (CSE) is a two-year research-oriented programme concentrating on intelligent digital solutions to real world problems. During the past decades, Computer Science and Engineering has had a significant impact into our daily lives. The development continues and soon computers will not be used as separate devices anymore. Instead they will blend into our living environments and offer us rich sets of services through natural and intuitive user interfaces. The graduates from Computer Science and Engineering will play a key role in this development.
The two-year programme has three specialisation options:
• Applied Computing
• Artificial Intelligence
• Computer Engineering
Applied Computing focuses on the next generation of interactive systems that place humans at the focus of the technological development. Adopting a multidisciplinary real-world approach, students have to spend a substantial amount of time working in group projects to develop a variety of systems ranging from interactive online services to games and mobile applications, with a strong focus on innovation and design.
Artificial Intelligence focuses in various fields of AI, such as machine learning, machine vision, and data mining. This specialisation provides students with a solid theoretical understanding and practical skills on processing and analyzing digital data and the ability to create intelligent solutions to real world problems with modern AI techniques.
Computer Engineering focuses on both hardware and software aspects of computing with emphasis on embedded system development. In this specialisation, students also study signal processing and its applications, and work with projects on modern signal processors and embedded computers. The specialisation gives the students a good basis to work with Internet of Things (IoT) applications.
In addition to the core specialization options, students can take optional courses to widen their specialization expertise into:
• Biomedical signal analysis
• Machine learning
• Machine vision
• Signal processing
• Embedded systems
• Ubiquitous computing
This Master’s programme is provided by the Faculty of Information Technology and Electrical Engineering, and students are strongly encouraged to work closely with research groups in the faculty that are international leaders in their fields. The Center for Machine Vision and Signal Analysis (CMVS) is renowned world-wide for its 35 years of expertise in computer vision research. The Center for Ubiquitous Computing (UBICOMP) has created a unique research environment for Ubiquitous Computing including multitouch wall-sized displays, smartphone sensing middleware and sensor networks. Biomimetics and Intelligent Systems Group (BISG) is a fusion of expertise from the fields of computer science and biology. During the studies the research groups provide students trainee and master’s thesis positions, with the possibility to continue as a doctoral student, and even as a post-doctoral researcher.
The programme will provide the graduates with sufficient skills to work in a wide variety of positions offered by research institutes and companies mainly operating in the field of information and communications technology (ICT). The graduates are most likely to be employed in research and development related positions, but also management positions and entrepreneurship fit into the profile.
Possible titles include:
• Research Scientist
• Software Engineer
• System Designer
• Project Manager
• Specialist
Students applying for the programme must possess an applicable B.Sc. degree in computer science, electrical engineering or relevant fields such as physics or applied mathematics.
For all enquiries, please refer to our enquiry form: http://www.oulu.fi/university/admissions-contact
