Masters degrees in Artificial Intelligence equip postgraduates with a knowledge of the theory, design, application and development of biologically, socially and linguistically motivated computer systems.
Taught MSc degrees are typical for this field, though research-oriented MRes and MPhil programmes are also available at some institutions. Entry requirements normally include an appropriate undergraduate degree, such as Computer Science or Robotics.
Are you interested in applications of Artificial Intelligence in communication techniques? Are you triggered by the question of how human reasoning can be represented in computer systems? Would you like to work for a company like Google or Philips? Then our interdisciplinary Master’s track Cognitive Science and Artificial Intelligence is your right choice!
The CSAI program draws on breakthrough discoveries and insights in the two closely related scientific disciplines Cognitive Science and Artificial Intelligence. Cognitive Science is the study of human reasoning, emotions, language, perception, attention, and memory. Artificial Intelligence is the study and design of computers and software that are capable of intelligent behavior.
Are you interested in applications of Artificial Intelligence in communication techniques? Are you triggered by the question of how human reasoning can be represented in computer systems? Would you like to work for a company like Google or Philips? Then our interdisciplinary Master’s track Cognitive Science and Artificial Intelligence is your right choice!
The CSAI program draws on breakthrough discoveries and insights in the two closely related scientific disciplines Cognitive Science and Artificial Intelligence. Cognitive Science is the study of human reasoning, emotions, language, perception, attention, and memory. Artificial Intelligence is the study and design of computers and software that are capable of intelligent behavior.
Graduates will be able to contribute to advancements in working fields like artificial intelligence and robotics, data science, data mining, knowledge technology and decision support systems.
This is a small selection of positions you may apply for after you have completed your programme:
•Intelligent Software Developer
•Web Analyst
•Social Media Analyst
•Data Journalist
•Social Robot Developer
•Web Data Entrepreneur
•E-Health and Healthcare Quality Analyst
Artificial Intelligence is a fast-paced and challenging field that is making visible inroads into our everyday life. This Master's programme focuses on the theoretical symbolic foundations within Artificial intelligence. We examine the semantics of natural language and of reasoning and argumentation. Moreover, we also look at the foundations of autonomy and collaboration between distributed software systems. These are applied for instance in virtual characters in serious games, in logistic applications like train schedules and in autonomous cars. Other application areas are social simulation for policy management and change of behaviour.
The Master’s in Artificial Intelligence offers you an integrative and cutting-edge approach to the field from the viewpoints of Informatics, Logic, Cognition, Psychology, Philosophy, and Linguistics.
Students can choose from three tracks:
Choosing from a broad range of courses you can tailor the programme to your personal interests within Artificial Intelligence.
As a graduate of the Artificial Intelligence programme, you will have a solid understanding of the logical, philosophical, and cognitive foundations of AI research. You will also have a good overview of the main AI techniques and an in-depth understanding of how to apply these techniques in at least one of the areas within multi-agent systems, reasoning, or cognitive processing. In addition, you will have the skills to carry out AI research in academic or R&D environments and to identify how AI techniques can provide intelligent solutions to IT problems in companies and organisations.
Artificial Intelligence is rapidly changing the way we live, work and learn. Both governments and industries have recognised the need for strategic development of AI -- technology giants such as Google, Microsoft and Facebook have each established their own AI research institutes, and the UK government recently announced its £75 million investment in the November 2017 Budget.
There is however a real shortage of AI talents worldwide, both to serve the industry and drive future research. Artificial Intelligence jobs are amongst the best paid in industry nowadays – an AI Specialist typically earns among the highest salaries (New York Times, 22nd Oct 2017), while having a solid AI background is strongly desired in multiple research disciplines.
MSc Artificial Intelligence importantly recognises such need for training cutting-edge AI talents, and is specifically designed to maximise student employability on AI-specific jobs.
• comprehensive: covering all five of the most popular AI topics
• up-to-date: each topic backed up by a world-leading group with cutting edge research
• unique: offering Game AI that represents some of the most advanced AI to date (e.g., AlphaGo)
• practical: focusing on developing practical machine-learning skills across all five AI topics
The programme brings together our teaching, research and industrial contacts to allow students to mix the different AI topics that best suits their personal requirements and future plans. Students will be offered lectures that explain the fundamental AI concepts, universal machine-learning tools essential for any AI job profile, and specific practical and research skills on all five of the AI topics. Students will gain experience with cutting-edge tools such as Deep Neural Networks (DNN), Recurrent Neural Networks (RNN), and Deep Reinforcement Learning (Deep RL) via regular exercises and practical labs. Students will be taught by world-renowned academics in their specific subject areas, and have regular contacts with them throughout the duration of the programme.
MSc Artificial Intelligence is currently available for one year full-time study or two years part-time study.
Semester 1: Four modules that operate on a 3+1 scheme
3 core modules that cover the foundational machine learning techniques and introduction of Artificial Intelligence for Games (e.g., AlphaGo); and 1 optional module to select from three other AI topics (vision, music and language).
Semester 2: Four modules themed around all five AI topics offered
The module selection allows students to focus on topic-specific research or industry applications for AI. More importantly, these module options allow students to gain advanced and up-to-date knowledge on selected AI topics.
Semester 3:
Students carry out a large project on the AI topic that they want to specialise in, after agreeing on a specific topic with an academic supervisor in the first semester, and completing the preparation phase over the second semester.
Undertaking a masters programme is a serious commitment, with weekly contact hours in addition to numerous hours of independent learning and research needed to progress at the required level. When coursework or examination deadlines are approaching, independent learning hours may need to increase significantly. Please contact the course convenor for precise information on the number of contact hours per week for this programme.
Part-time study options often mean that the number of modules taken is reduced per semester, with the full modules required to complete the programme spread over two academic years. Teaching is generally done during the day and part-time students should contact the course convenor to get an idea of when these teaching hours are likely to take place. Timetables are likely to be finalised in September but you may be able to gain an expectation of what will be required.
Important note regarding Part Time Study
We regret that due to complex timetabling constraints, we are not able to guarantee that lectures and labs for part time students will be limited to two days per week, neither do we currently support any evening classes. If you have specific enquiries about the timetabling of part time courses, please contact the MSc Administrator
· Computational Intelligence and Games
· Machine Learning
· Data Mining
· MSc Project module
· Introduction to Computer Vision
· Machine Learning for Visual Data Analysis
· Deep Learning and Computer Vision
· Music Perception and Cognition
· Music and Speech Modelling
· Music Analysis and Synthesis
· Natural Language Processing
· Advanced Natural Language Processing
· Artificial Intelligence
· Information Retrieval
· Advanced Robotics Systems
· Multi-platform Game Development
*All new courses are required to undergo a two-stage internal review and approval process before being advertised to students. Courses that are marked "subject to approval" have successfully completed the first stage of this process. Applications are welcome but we will not make formal offers for this course until it has passed this second (and final) stage.
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.
AI is rapidly changing the way we live, work and learn. Both governments and industry have recognised the need for strategic development of AI -- technology giants such as Google, Microsoft and Facebook have each established their own AI research institutes, and the UK government recently announced its £75 million investment in the November 2017 Budget.
There is however a real shortage of AI talents worldwide, both to serve the industry and drive future research. AI jobs are amongst the best paid in industry nowadays – an AI Specialist typically earns among the highest salaries (New York Times, 22nd Oct 2017), while having a solid AI background is strongly desired in multiple research disciplines.
MSc Artificial Intelligence importantly recognises such need for training cutting-edge AI talents, and is specifically designed to maximise student employability on AI-specific jobs.
The programme brings together our teaching, research and industrial contacts to allow students to mix the different AI topics that best suits their personal requirements and future plans. Students will be offered lectures that explain the fundamental AI concepts, universal machine learning tools essential for any AI job profile, and specific practical and research skills on all five of the AI topics. Students will gain experience with cutting-edge tools such as Deep Neural Networks (DNN), Recurrent Neural Networks (RNN), and Deep Reinforcement Learning (Deep RL) via regular exercises and practical labs. Students will be taught by world-renowned academics in their specific subject areas, and have regular contacts with them throughout the duration of the programme.
The industrial placement consists of 8-12 months spent working with an appropriate employer in a role that relates directly to your field of study. The placement is currently undertaken after you have completed, passed the taught component of the degree and submitted your MSc project. The placement will provide the opportunity to apply key technical knowledge and skills gained from your taught modules and will enable you to gain a better understanding of your own abilities, aptitudes, attitudes and employment potential. The module is only open to students enrolled on a programme of study with integrated placement.
In the event that you are unable to secure a placement, we will transfer you onto the 1 year FT taught programme without the Industrial Experience. This change will also apply to any student visa you hold at the time.
MSc Artificial Intelligence is currently available for one year full-time study or two years part-time study.
Semester 1: Four modules that operate on a 3+1 scheme
3 core modules that cover the foundational machine learning techniques and introduction of Artificial Intelligence for Games (e.g., AlphaGo); and 1 optional module to select from three other AI topics (vision, music and language).
Semester 2: Four modules themed around all five AI topics offered
The module selection allows students to focus on topic-specific research or industry applications for AI. More importantly, these module options allow students to gain advanced and up-to-date knowledge on selected AI topics.
Semester 3:
Students carry out a large project on the AI topic that they want to specialise in, after agreeing on a specific topic with an academic supervisor in the first semester, and completing the preparation phase over the second semester.
Undertaking a masters programme is a serious commitment, with weekly contact hours being in addition to numerous hours of independent learning and research needed to progress at the required level. When coursework or examination deadlines are approaching independent learning hours may need to increase significantly. Please contact the course convenor for precise information on the number of contact hours per week for this programme.
Part-time study options often mean that the number of modules taken is reduced per semester, with the full modules required to complete the programme spread over two academic years. Teaching is generally done during the day and part-time students should contact the course convenor to get an idea of when these teaching hours are likely to take place. Timetables are likely to be finalised in September but you may be able to gain an expectation of what will be required.
· Computational Intelligence and Games
· Machine Learning
· Data Mining
· MSc Project module
· Introduction to Computer Vision
· Machine Learning for Visual Data Analysis
· Deep Learning and Computer Vision
· Music Perception and Cognition
· Music and Speech Modelling
· Music Analysis and Synthesis
· Natural Language Processing
· Advanced Natural Language Processing
· Artificial Intelligence
· Information Retrieval
· Advanced Robotics Systems
· Multi-platform Game Development
*All new courses are required to undergo a two-stage internal review and approval process before being advertised to students. Courses that are marked "subject to approval" have successfully completed the first stage of this process. Applications are welcome but we will not make formal offers for this course until it has passed this second (and final) stage.
Understanding naturally intelligent systems, building artificially intelligent systems, and improving the interactions between humans and artificial systems.
As humans, we may be intrigued by the complexity of any daily activity. How do we perceive, act, decide, and remember? On the one hand, if we understand how our own intelligence works, we can use this knowledge to make computers smarter. On the other hand, by making computers behave more like humans, we learn more about how our own cognition works.
The AI Master’s programme at Radboud University has a distinctly cognitive focus. This cognitive focus leads to a highly interdisciplinary programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.
See the website http://www.ru.nl/masters/ai
Slowly the human brain has been revealing its mystery to the scientific community. Now that we are actually able to model and stimulate aspects of cognition, AI researchers have gained a deeper understanding of cognition. At the world-renowned Donders Institute, the Max Planck Institute and various other leading research centres, we train our students to become excellent researchers in this area.
At Radboud University we also teach students how to develop practical applications that will become the next generation of products, apps, therapies and services. Our department has been awarded several prizes for its pioneering role in bringing innovations from science to society, e.g. in Assistive Technology for people with disabilities. You’ll be taught the skills needed to conduct and steer such innovation processes. Many Master’s research projects have both a scientific and a practical component.
Computational modelling is the central methodology taught and used in this programme. Depending on the area of study, the computational models can range from behavioural models of millions of individuals interacting on the web, to functional models of human or robot decision-making, to models of individual or networks of artificial neurons. At Radboud University we offer the following three specialisations (on campus simply known as Computation, Robot and Web):
- Computation in Neural and Artificial Systems
Learn how to create artificial information systems that mimic biological systems as well as how to use theoretical insights from AI to better understand cognitive processing in humans.
- Robot Cognition
Understand all aspects of Human-Robot interaction: the programming that coordinates a robot’s actions with human action as well the human appreciation and trust in the robot.
- Web and Language Interaction
Learn how to build the intelligence used to power the future of the Web.
To finalise your AI master's programme, you have the choice of either an Internship (18EC) and Research Project (30EC) or a single larger Extended Research Project (48EC). During the internship you have the chance to acquire additional AI relevant skills either at a research lab or at a company. During the Research Projects phase, you get to put what you have learned during your master's programme into practice. You can perform your research work in the AI department, at other research departments at the University (e.g. the Behaviour Science Institute or Donders Institute) or at an external company (such as Philips or TNO). You are also encouraged to go abroad for your internship and/or research project (previously students have gone to Stanford University in California and Aldebaran Robotics in Paris). To help you decide on a thesis topic, there is an annual Thesis Fair where academics and companies present possible project ideas.
Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or a university with an AI department. Other graduates have started their own companies or work for companies interested in cognitive design and research.
Find out how to apply here http://www.ru.nl/masters/ai
- Information for international students
Radboud University would like to meet you in your country (http://www.ru.nl/meetus) in order to give all the information you need and to answer any questions you might have about studying in the Netherlands. In the next few months, an advisor of Radboud University will be attending fairs in various countries, always accompanied by a current or former student.
Furthermore, we understand if you would like to see the Radboud Campus and the city of Nijmegen, which is why we organise an Master's Open Day for international students, which you are welcome to attend (http://www.ru.nl/openday).
- Information for Dutch students
Radboud University offers students in the Netherlands plenty of opportunities to get more information on your programme of choice, or get answers to any questions you might have and more. Apart from a Master's Evening and a Master's Day, we also organise Orientation Days and a Master’s Afternoon for HBO students.
Our research led MSc in Artificial Intelligence covers the fundamental aspects of traditional symbolic and sub-symbolic aspects. This one year degree offers wide-ranging options including intelligent agents, complexity science, computer vision, robotics and machine learning techniques and helps develop a broad skill set suitable for further study or application development.
On this degree, you will learn from world-class researchers working in artifical intelligence fields such as computer vision, evolutionary computing, intelligent agents, game theory, deep learning and other machine learning methods. You will develop core data analysis skills and explore both traditional and state-of-the-art aspects of artificial intelligence and machine learning.
This research-led MSc takes a contemporary approach and covers the fundamental aspects of traditional symbolic and sub-symbolic aspects.
The programme will give you a solid awareness of the key concepts of artificial intelligence. You will also learn the techniques that form the current basis of machine learning and data mining. You will develop a wide-ranging skill set that supports further study or that you can use in application development.
As a result of the leading research being undertaken at Southampton, the course is able to offer a wide range of options that cover state-of-the-art modern techniques, which directly reflect research directions in ECS. These include:
View the programme specification document for this course
This programme provides an excellent platform for further research in either industry or academia.
Graduates from our MSc programme are employed worldwide in leading companies at the forefront of technology. ECS runs a dedicated careers hub which is affiliated with over 100 renowned companies like IBM, Arm, Microsoft Research, Imagination Technologies, Nvidia, Samsung and Google to name a few.
Visit our careers hub for more information.
Taught by experienced research staff from the Centre for Computational Intelligence (CCI), an internationally recognised centre highly rated in the most recent Government Research Assessment Exercise, you gain a professional qualification that gives substantially enhanced career and research prospects in both traditional computing areas and in the expanding area of computational intelligence.
Computational Intelligence encompasses the techniques and methods used to tackle problems not well solved by traditional approaches to computing. The four areas of fuzzy logic, neural networks, evolutionary computing and knowledge based systems encompass much of what is considered to be computational (or artificial) intelligence. There are opportunities to use these techniques in many application areas such as robot control and games development depending on your interests.
Modules include work based on research by the Centre of Computational Intelligence. With an established international reputation, their work focuses on the use of fuzzy logic, artificial neural networks, evolutionary computing, mobile robotics and biomedical informatics, providing theoretically sound solutions to real-world decision making and prediction problems. Past students have published papers with their CCI project supervisors and gone on to PhD study.
• Internationally recognised reputation
our internationally recognised Centre of Computational Intelligence (CCI) inputs into the course allowing you to understand the current research issues related to artificial intelligence
• Benefit from our Research Expertise
modules include work-based on research by our Centre for Computational Intelligence (CCI) and focus on the use of fuzzy logic, artificial neural networks, evolutionary computing, mobile robotics and biomedical informatics; providing theoretically sound solutions to real-world decision making and prediction problems
• Flexible study options
full-time, part time or distance learning study options available; making the course suitable for recent graduates and professionals in work
• Dedicated robotics laboratory
have access to our Advanced Mobile Robotics and Intelligent Agents Laboratory. The laboratory contains a variety of mobile robots ranging from the Lego Mindstorms and Pioneers to the Wheelbarrow robot for bomb disposal
• Employment Prospects
artificial Intelligence is a growing industry worldwide, employment opportunities exist in areas such as games development, control systems, software engineering, internet businesses, financial services, mobile communications, programming, and software engineering
First semester
• Research Methods
• Artificial Intelligence Programming
• Mobile Robots
• Fuzzy Logic
Second semester
• Artificial Neural Networks
• Computational Intelligence Optimisation (CIO)
• Applied Computational Intelligence
• Data Mining, Techniques and Applications
(Intelligence Systems only)
• Intelligent Mobile Robots (Intelligent Systems
and Robotics only)
Third semester
• Individual Project
We offer a great opportunity to boost your career prospects through an optional one year placement as part of your postgraduate studies. We have a dedicated Placement Unit which will help you obtain this. Once on your placement you will be supported by your Visiting Tutor to ensure that you gain maximum benefit from the experience. Placements begin after the taught component of the course has been completed - usually around June - and last for one year. When you return from your work placement you will begin your project.
The course consists of an induction unit, eight modules and an individual project. The summer period is devoted to work on the project for full-time students. If you choose to study via distance learning, you would normally take either one module per semester for four years or two modules per semester for four years plus a further year for the project.
Teaching is normally delivered through lectures, seminars, tutorials, workshops, discussions and e-learning packages. Assessment is via coursework only and will usually involve a combination of individual and group work, presentations, essays, reports and projects.
Distance learning material is delivered primarily through our virtual learning environment. Books, DVDs and other learning materials will be sent to you. We aim to replicate the on-site experience as fully as possible by using electronic discussion groups, encouraging contact with tutors through a variety of mediums.
On-site students will have the lessons delivered by the module tutors in slots of three hours. In the full-time route, you can expect to have around 12 hours of timetabled taught sessions each week, with approximately 28 additional hours of independent study. There are also three non-teaching weeks when fulltime students can expect to spend around 40 hours on independent study each week.
Taught by experienced research staff from the Centre for Computational Intelligence (CCI), an internationally recognised centre highly rated in the most recent Government Research Assessment Exercise, you will gain a professional qualification that gives substantially enhanced career and research prospects in both traditional computing areas and in the expanding area of computational intelligence.
To learn more about this course and DMU, visit our website:
Postgraduate open days: http://www.dmu.ac.uk/study/postgraduate-study/open-evenings/postgraduate-open-days.aspx
Applying for a postgraduate course:
Funding for postgraduate students
Taught by experienced research staff from the Centre for Computational Intelligence (CCI), an internationally recognised centre highly rated in the most recent Government Research Assessment Exercise, you gain a professional qualification that gives substantially enhanced career and research prospects in both traditional computing areas and in the expanding area of computational intelligence.
Computational Intelligence encompasses the techniques and methods used to tackle problems not well solved by traditional approaches to computing. The four areas of fuzzy logic, neural networks, evolutionary computing and knowledge based systems encompass much of what is considered to be computational (or artificial) intelligence. There are opportunities to use these techniques in many application areas such as robot control and games development depending on your interests.
Modules include work based on research by the Centre of Computational Intelligence. With an established international reputation, their work focuses on the use of fuzzy logic, artificial neural networks, evolutionary computing, mobile robotics and biomedical informatics, providing theoretically sound solutions to real-world decision making and prediction problems. Past students have published papers with their CCI project supervisors and gone on to PhD study.
• Internationally recognised reputation
our internationally recognised Centre of Computational Intelligence (CCI) inputs into the course allowing you to understand the current research issues related to artificial intelligence
• Benefit from our Research Expertise
modules include work-based on research by our Centre for Computational Intelligence (CCI) and focus on the use of fuzzy logic, artificial neural networks, evolutionary computing, mobile robotics and biomedical informatics; providing theoretically sound solutions to real-world decision making and prediction problems
• Flexible study options
full-time, part time or distance learning study options available; making the course suitable for recent graduates and professionals in work
• Dedicated robotics laboratory
have access to our Advanced Mobile Robotics and Intelligent Agents Laboratory. The laboratory contains a variety of mobile robots ranging from the Lego Mindstorms and Pioneers to the Wheelbarrow robot for bomb disposal
• Employment Prospects
artificial Intelligence is a growing industry worldwide, employment opportunities exist in areas such as games development, control systems, software engineering, internet businesses, financial services, mobile communications, programming, and software engineering
First semester
• Research Methods
• Artificial Intelligence Programming
• Mobile Robots
• Fuzzy Logic
Second semester
• Artificial Neural Networks
• Computational Intelligence Optimisation (CIO)
• Applied Computational Intelligence
• Data Mining, Techniques and Applications
(Intelligence Systems only)
• Intelligent Mobile Robots (Intelligent Systems
and Robotics only)
Third semester
• Individual Project
We offer a great opportunity to boost your career prospects through an optional one year placement as part of your postgraduate studies. We have a dedicated Placement Unit which will help you obtain this. Once on your placement you will be supported by your Visiting Tutor to ensure that you gain maximum benefit from the experience. Placements begin after the taught component of the course has been completed - usually around June - and last for one year. When you return from your work placement you will begin your project.
The course consists of an induction unit, eight modules and an individual project. The summer period is devoted to work on the project for full-time students. If you choose to study via distance learning, you would normally take either one module per semester for four years or two modules per semester for four years plus a further year for the project.
Teaching is normally delivered through lectures, seminars, tutorials, workshops, discussions and e-learning packages. Assessment is via coursework only and will usually involve a combination of individual and group work, presentations, essays, reports and projects.
Distance learning material is delivered primarily through our virtual learning environment. Books, DVDs and other learning materials will be sent to you. We aim to replicate the on-site experience as fully as possible by using electronic discussion groups, encouraging contact with tutors through a variety of mediums.
On-site students will have the lessons delivered by the module tutors in slots of three hours. In the full-time route, you can expect to have around 12 hours of timetabled taught sessions each week, with approximately 28 additional hours of independent study. There are also three non-teaching weeks when fulltime students can expect to spend around 40 hours on independent study each week.
To learn more about this course and DMU, visit our website:
Postgraduate open days: http://www.dmu.ac.uk/study/postgraduate-study/open-evenings/postgraduate-open-days.aspx
Applying for a postgraduate course:
Funding for postgraduate students
The MSc in Artificial Intelligence is a one-year taught programme run by the School of Computer Science. The course consists of two semesters of taught modules followed by an 11-week project leading to the submission of a 15,000-word dissertation in August.
Students on this course may switch to an MSc in Advanced Computer Science or in Information Technology after the first semester.
The taught portion of the MSc programme includes eight modules: five compulsory and three optional from a wide range available. Teaching methods include lectures, seminars, tutorials and practical classes. Most modules are assessed through practical coursework exercises and examinations. Class sizes typically range from 10 to 50 students.
All students are assigned an advisor who meets with them at the start of the year to discuss module choices and is available to assist with any academic difficulties during the year. A designated member of staff provides close supervision for the MSc project and dissertation.
Further particulars regarding curriculum development.
The modules in this programme have varying methods of delivery and assessment. For more details of each module, including weekly contact hours, teaching methods and assessment, please see the latest module catalogue which is for the 2017–2018 academic year; some elements may be subject to change for 2018 entry.
The Department of Automatic Control and Systems Engineering (ACSE) at the University of Sheffield
Develop your skills and enhance your career prospects with a masters degree in Cybersecurity and Artificial Intelligence
EURECOM: a leading Graduate School and Research center in the field of Digital Science
