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The MSc programme comprises six compulsory taught modules (totaling 120 credits) and a substantial independent Master's Project (60 credits). As part of the programme, students will be required to use various programming languages, including Python and R. Data Science and Machine Learning This module provides an overview of Data Science process/pipeline. It provides systematic understanding of mathematical and statistical knowledge for explorable data analysis (EDA) and to understand the foundations of supervised and unsupervised machine learning algorithms, and with the practical programming skills to apply them to real world datasets. The module discusses the constraints that needs to be considered when designing, implementing, evaluating and visualising solutions to real-world complex problems. Deep Learning and Its Application The module will introduce the fundamentals of deep learning, construction of neural networks and theory of developing successful deep learning algorithms. Students will learn state of the art convolutional neural networks, recurrent neural networks, loss functions and optimisation process along with development tools, and apply them to develop solutions for applications of computer vision and natural language processing. Robotics & AI This module provides an overview of smart robotics and AI. It is designed to provide students with a strong foundation through the core topics and the key technologies of robotics and AI while providing hands-on experience on programming smart robots in the labs. The module will explore practically coding AI techniques for Robotics and the focus is given to design and implement smart robots exhibiting AI behaviours. Knowledge Engineering This module will cover modern topics in a classical field of artificial intelligence, including knowledge representation and reasoning (deductive and inductive), and their effective utilisation in e.g. decision making, automated reasoning and formal verification, and semantic web. Students will gain deep understanding of key concepts and principles, and gain practical skills in critically evaluating and effectively building knowledge-based applications. Intelligence Engineering and Infrastructure The aim of this module is to educate students on best practices for engineering, deploying, testing and orchestration intelligence across modern computing. This will include aspects of Machine learning, federated operation of activities, data engineering, production of tailored computational artefacts (such as models which are tailored for a range of device type), production pipelines, automated testing and automated deployment. Emerging and Advanced Topics in AI This module will cover cutting-edge topics in the field of artificial intelligence, including recent advances in AI theory, algorithms and applications, as well as issues such as privacy, fairness and ethics in artificial intelligence. In doing so a number of examples of advanced AI systems and applications are reviewed. Students will gain deep understanding of key concepts, principles, and challenges, and gain practical skills in critically evaluating and effectively building AI-based applications. The module will also help students develop their skills in independent learning, research skills, writing, as well as practical skills in using software to reproduce results from the literature.
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The MSc programme comprises six compulsory taught modules (totaling 120 credits) and a substantial independent Master's Project (60 credits). As part of the programme, students will be required to use various programming languages, including Python and R. Data Science and Machine Learning This module provides an overview of Data Science process/pipeline. It provides systematic understanding of mathematical and statistical knowledge for explorable data analysis (EDA) and to understand the foundations of supervised and unsupervised machine learning algorithms, and with the practical programming skills to apply them to real world datasets. The module discusses the constraints that needs to be considered when designing, implementing, evaluating and visualising solutions to real-world complex problems. Deep Learning and Its Application The module will introduce the fundamentals of deep learning, construction of neural networks and theory of developing successful deep learning algorithms. Students will learn state of the art convolutional neural networks, recurrent neural networks, loss functions and optimisation process along with development tools, and apply them to develop solutions for applications of computer vision and natural language processing. Robotics & AI This module provides an overview of smart robotics and AI. It is designed to provide students with a strong foundation through the core topics and the key technologies of robotics and AI while providing hands-on experience on programming smart robots in the labs. The module will explore practically coding AI techniques for Robotics and the focus is given to design and implement smart robots exhibiting AI behaviours. Knowledge Engineering This module will cover modern topics in a classical field of artificial intelligence, including knowledge representation and reasoning (deductive and inductive), and their effective utilisation in e.g. decision making, automated reasoning and formal verification, and semantic web. Students will gain deep understanding of key concepts and principles, and gain practical skills in critically evaluating and effectively building knowledge-based applications. Intelligence Engineering and Infrastructure The aim of this module is to educate students on best practices for engineering, deploying, testing and orchestration intelligence across modern computing. This will include aspects of Machine learning, federated operation of activities, data engineering, production of tailored computational artefacts (such as models which are tailored for a range of device type), production pipelines, automated testing and automated deployment. Emerging and Advanced Topics in AI This module will cover cutting-edge topics in the field of artificial intelligence, including recent advances in AI theory, algorithms and applications, as well as issues such as privacy, fairness and ethics in artificial intelligence. In doing so a number of examples of advanced AI systems and applications are reviewed. Students will gain deep understanding of key concepts, principles, and challenges, and gain practical skills in critically evaluating and effectively building AI-based applications. The module will also help students develop their skills in independent learning, research skills, writing, as well as practical skills in using software to reproduce results from the literature.
Admission Requirements
We recognise a range of qualifications for admission to our courses. In addition to the specific entry conditions for this course you must also meet the University’s General Entrance Requirements. Entry Requirements Applicants must: (a) have gained (i) a second class honours degree or better, in the subject areas of Computer Science, Software Engineering, Electronic Engineering, Electrical Engineering, Mathematics, Physics or closely related discipline, from a university of the United Kingdom or the Republic of Ireland, or from a recognised national awarding body, or from an institution of another country which has been recognised as being of an equivalent standard; or (ii) an equivalent standard (normally 50%) in a Graduate Diploma, Graduate Certificate, Postgraduate Certificate or Postgraduate Diploma or an approved alternative qualification excluding Conversion courses; and the qualification must be in the subject areas of Computer Science, Software Engineering, Electronic Engineering, Electrical Engineering, Mathematics, Physics or closely related discipline. and (b) provide evidence of competence in written and spoken English (GCSE grade C or equivalent). For applicants whose first language is not English the minimum English language requirement is an Academic IELTS 6.0 with no band score less than 5.5, Trinity ISE: Pass at level III or equivalent English language tests comparable to IELTS equivalent score. In exceptional circumstances, as an alternative to (a) (i) or (a) (ii) and/or (b), where an individual has substantial and significant experiential learning, a portfolio of written evidence demonstrating the meeting of graduate qualities (including subject-specific outcomes, as determined by the Course Committee) may be considered as an alternative entrance route. Evidence used to demonstrate graduate qualities may not be used for exemption against modules within the programme. English Language Requirements English language requirements for international applicants The minimum requirement for this course is Academic IELTS 6.0 with no band score less than 5.5. Trinity ISE: Pass at level III also meets this requirement for Tier 4 visa purposes. Ulster recognises a number of other English language tests and comparable IELTS equivalent scores. English language requirements Your country Exemptions and transferability The entry requirements facilitate accreditation of prior learning.
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Artificial Intelligence MSc
Belfast, Belfast, United Kingdom
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Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
Admission Requirements
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
How to get a full scholarship
Looking for a fully-funded scholarship to see you into university? Find out how to boost your chances of getting one.
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Find scholarships to study abroad with our lists of international scholarships – categorized by country, by subject, and by type of student.
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Mechanical Engineering MSc
Mechatronic Engineering MEng (Hons)
Mechatronic Engineering MEng (Hons)
Professional Software Development (Data Science) MSc
Professional Software Development (Data Science) MSc
Professional Software Development MSc
Professional Software Development MSc
Renewable Energy and Energy Management PgDip, MSc
Renewable Energy and Energy Management PgDip, MSc
Smart Manufacturing Systems MSc
Smart Manufacturing Systems MSc
Software Engineering MEng (Hons)
Software Engineering MEng (Hons)
Life Sciences and Medicine (6)
Advanced Pharmacy Practice MSc
Advanced Pharmacy Practice MSc
Advanced Practice MSc
Advanced Practice MSc
Applied Behaviour Analysis MSc
Applied Behaviour Analysis MSc
Applied Psychology (Mental Health and Psychological Therapies) MSc
Applied Psychology (Mental Health and Psychological Therapies) MSc
Biomedical Science MSc
Biomedical Science MSc
Biotechnology Research MSc
Biotechnology Research MSc
Dietetics MSc
Dietetics MSc
Health Psychology MSc
Health Psychology MSc
Health and Wellbeing PgDip, MSc
Health and Wellbeing PgDip, MSc
Human Nutrition MSc
Human Nutrition MSc
Leadership in Health and Social Care PgDip, MSc
Leadership in Health and Social Care PgDip, MSc
Optometry MOptom
Optometry MOptom
Personalised Medicine MSc
Personalised Medicine MSc
Pharmaceutical Bioscience MSci (Hons)
Pharmaceutical Bioscience MSci (Hons)
Pharmaceutical Sciences MSc
Pharmaceutical Sciences MSc
Pharmacy MPharm (Hons)
Pharmacy MPharm (Hons)
Psychology MSc
Psychology MSc
Veterinary Public Health (Food Regulatory Affairs) PgDip, MSc
Veterinary Public Health (Food Regulatory Affairs) PgDip, MSc
Natural Sciences (6)
Advanced Composites and Polymers PgDip, MSc
Advanced Composites and Polymers PgDip, MSc
Environmental Management PgDip, MSc
Environmental Management PgDip, MSc
Environmental Management with Geographic Information Systems PgDip, MSc
Environmental Management with Geographic Information Systems PgDip, MSc
Environmental Toxicology and Pollution Monitoring PgDip, MSc
Environmental Toxicology and Pollution Monitoring PgDip, MSc
Food and Nutrition MSc
Food and Nutrition MSc
Geographic Information Systems PgDip, MSc
Geographic Information Systems PgDip, MSc
Remote Sensing and Geographic Information Systems PgDip, MSc
Remote Sensing and Geographic Information Systems PgDip, MSc
Sustainable Management MSc
Sustainable Management MSc
Social Sciences and Management (6)
Access to Justice LLM
Access to Justice LLM
Communication and Public Relations PgDip, MSc
Communication and Public Relations PgDip, MSc
Community Youth Work PgDip, MSc
Community Youth Work PgDip, MSc
Criminology and Criminal Justice MSc
Criminology and Criminal Justice MSc
Education with Specialisms MEd
Education with Specialisms MEd
Film and TV Production MA
Film and TV Production MA
Gender and Human Rights LLM
Gender and Human Rights LLM
Global Sustainable Tourism MSc
Global Sustainable Tourism MSc
Golf Management MSc
Golf Management MSc
Human Resource Management MSc
Human Resource Management MSc
Human Rights LLM
Human Rights LLM
Human Rights Law and Transitional Justice LLM
Human Rights Law and Transitional Justice LLM
International Commercial Law and ADR LLM
International Commercial Law and ADR LLM
International Tourism and Hospitality Management MSc
International Tourism and Hospitality Management MSc
Journalism MA
Journalism MA
Law LLM
Law LLM
Legal Innovation and Technology Law LLM, MSc
Legal Innovation and Technology Law LLM, MSc
Library and Information Management PgDip, MSc
Library and Information Management PgDip, MSc
Peace and Conflict Studies MSc
Peace and Conflict Studies MSc
Photography (MFA) MFA
Photography (MFA) MFA
Photography (MFA) eLearning MFA
Photography (MFA) eLearning MFA
Public Administration MPA
Public Administration MPA
Real Estate MSc
Real Estate MSc
Social Policy MSc
Social Policy MSc
Sport and Exercise Medicine PgDip, MSc
Sport and Exercise Medicine PgDip, MSc
Sport and Exercise Nutrition PgDip, MSc
Sport and Exercise Nutrition PgDip, MSc
Sport and Exercise Psychology MSc
Sport and Exercise Psychology MSc
Sports Coaching and Performance MSc
Sports Coaching and Performance MSc
Strength and Conditioning MSc
Strength and Conditioning MSc
Executive MBA (2)
Executive MBA (Master of Business Administration) MBA
Executive MBA (Master of Business Administration) MBA
Full-Time MBA (2)
MBA (Master of Business Administration) MBA
MBA (Master of Business Administration) MBA