From software agents used in networking systems to in unmanned vehicles, intelligent systems are being adopted more and more often. This Masters degree will equip you with specialist knowledge in this exciting field and allow you to explore a range of topics in computer science. Core modules will give you a foundation in topics like systems programming and algorithms, as well as the basics of machine learning and knowledge representation. You’ll also choose from optional modules focusing on topics like bio-inspired computing or text analytics, or broaden your approach with topics like mobile app development. You’ll gain a broad perspective on intelligent systems, covering evolutionary models, statistical and symbolic machine learning algorithms, qualitative reasoning, image processing, language understanding and bio-computation as well as essential principles and practices in the design, implementation and usability of intelligent systems. Specialist facilities You’ll benefit from world-class facilities to support your learning, including:
- a state-of the art cloud computing lab with a 10-node cluster
- a large High Performance Computing (HPC) resource consisting of several clusters which are used for all forms of predictive modelling, data analysis and simulation
- a visualisation lab including a Powerwall, benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker
- Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices
- Twin Immersion Corp CyberGloves
- rendering cluster and labs containing both Microsoft and Linux platforms, among others.
Modules include: MSc Project, Bio-Inspired Computing, Knowledge Representation and Reasoning, Artificial Intelligence. Optional modules include: Data Science, Algorithms, Data Mining and Text Analytics, Semantic Technologies and Applications, Scientific Computation, Machine Learning, Intelligent Systems and Robotics.
You’ll be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.
A bachelor degree with a 2:1 (hons) in computer science or a comparable subject with a substantial computing element. Relevant work experience will also be considered. We expect you to have significant programming competence and prior experience of systems development and knowledge of data structures and algorithms.
Fees and funding
No fee information has been provided for this course