Course overview


Artificial Intelligence (AI) encompasses the techniques and methods used to tackle problems that traditional approaches to computing struggle to solve. The four areas of fuzzy logic, evolutionary computing, neural networks, and natural language processing encompass much of what is considered artificial intelligence. Depending on your interests, you can apply what you learn in areas such as robot control and game development. 

You will study neural systems, natural language processing, and research methods and applications while developing your skills in our dedicated robotics laboratory, equipped with various mobile robots. The applied computational intelligence module considers knowledge-based systems and AI's historical, philosophical, and future implications and focuses on current research and applications.  


Key features


  • Artificial intelligence is a growing industry across the globe. Students can delve into game development, control systems, software engineering, internet businesses, financial services, mobile communications, programming, and software engineering.
  • The programme module features work based on research by our IAI and focus on the use of fuzzy logic, artificial neural networks, evolutionary computing, and mobile robotics, providing theoretically sound solutions to real-world decision-making and prediction problems.
  • Students will be introduced to concepts such as AI laboratories featuring cutting-edge workstations and technologies such as the Emotiv Flex Gel Sensor Kit and Emotiv PRO, the Lynxmotion Hexapod robot, Turtlebots, HTC Vive development kits, a 3D printer, and Lego EV3 Kits.
  • With available full-time or part-time learning and study options, your studies can keep pace with work and other commitments. This makes the course ideal for recent graduates and professionals already employed.
  • The programme leaders are experienced professionals dedicated to ensuring students receive a high-quality education. They are readily available to answer any questions or concerns students may have regarding the accreditation process or the course content. 
  • DMU Dubai students can now benefit from the Industry Advisory Board, which comprises leading experts and professionals at the enterprise level. The board provides valuable insights and guidance to ensure the curriculum remains relevant and current with industry trends and demands.
  • Benefit from Education 2030, where a simplified ‘block learning’ timetable means you will study one subject at a time and have more time to engage with your learning, receive faster feedback and enjoy a better study-life balance
  • Applicants will typically hold an undergraduate degree with a minimum pass of 2:2 or equivalent overseas qualification. 
  • Professional qualifications deemed to be of equivalent standing will be considered on an individual basis. 
  • Work experience is not a requirement. However, applications from those without formal qualifications but with significant professional experience in the relevant field will be considered individually.

If English is not your first language, an IELTS score of 6.0 or equivalent when you start the course is essential. 

Education 2030

We want to ensure you have the best learning experience possible and a supportive and nurturing learning community. That’s why we’re introducing a new block model for delivering the majority of our courses, known as Education 2030. This means a more simplified timetable where you will study one subject at a time instead of several at once. You will have more time to engage with your learning and get to know the teaching team and course mates. You will receive faster feedback through more regular assessment, and have a better study-life balance to enjoy other important aspects of university life.

Read more about Education 2030

Course modules

  • Block 1: Neural Systems and Natural Language Processing
  • Block 2: Artificial Intelligence for Mobile Robots
  • Block 3: Fuzzy Logic and Evolutionary Computing
  • Block 4: Research Methods & Applications
  • Blocks 5 & 6: Thesis Project 
See more detailed module descriptions

Note: All modules are indicative and based on the current academic session. Course information is correct at the time of publication and is subject to review. Exact modules may, therefore, vary for your intake in order to keep content current. If there are changes to your course we will, where reasonable, take steps to inform you as appropriate.

Teaching and assessments

The course consists of an induction unit, four modules and an individual 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.

Academic expertise

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.

Contact and learning hours

Students will normally attend around 12 hours of timetabled taught sessions each week, with approximately 28 additional hours of self-directed independent study and research to support your assignments and dissertation per week.

Meet your programme leader

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