Students admitted to the Master of Computing are required to pass 40 modular credits, and are given the flexibility to complete their programme by selecting one of the below options:
Coursework Option
Students are required to pass ten modules (40 modular credits), meeting the following requirements:
- three modules (12 modular credits) from the AI core module list
- two modules (8 modular credits) from AI elective module list
- remaining five modules (20 modular credits) can be chosen from level 4000 to 6000 modules offered by the School of Computing
Out of the required maximum ten modules, students are allowed a maximum of two level 4000 modules.
Dissertation Option
The dissertation option gives individual students the opportunity for independent study and research in the area of their selected specialisation. Students who opt to take the dissertation will need to complete the programme as follows:
- three modules (12 modular credits) from the AI core module list
- MComp dissertation equivalent to four modules (16 modular credits) on a topic related to AI
- remaining three modules (12 modular credits) can be chosen from level 4000 to 6000 modules offered by the School of Computing
Out of the six modules, students are allowed at most two level 4000 modules (8 modular credits).
The dissertation will be carried out under the supervision of an academic staff, and the selection of the topic/area will be done in consultation with the advisor in the area of expertise.
AI Core Module List
• CS5446 AI Planning and Decision Making
• Choose one:
- CS5339 Theory and Algorithms for Machine Learning, OR
- CS5242 Neural Networks and Deep Learning, OR
- IS5152 Data-Driven Decision Making
• CS5340 Uncertainty Modelling in AI
AI Elective Module List
• CS4243 Computer Vision and Pattern Recognition
• CS4244 Knowledge Representation and Reasoning
• CS4248 Natural Language Processing
• CS5215 Constraint Programming
• CS5228 Knowledge Discovery and Data Mining
• CS5242 Neural Networks and Deep Learning
• CS5246 Text Mining
• CS5260 Neural Networks and Deep Learning II
• CS5469 Fundamentals of Logic in Computer Science
• CS5477 3D Computer Vision
• CS5478 Intelligent Robots: Algorithms and Systems
• CS5339 Theory and Algorithms for Machine Learning
• CS5461 Algorithmic Mechanism Design
• CS6207 Advanced Natural Language Processing
• CS6208 Advanced Topics in Artificial Intelligence
• CS6216 Advanced Topics in Machine Learning
• CS6244 Robot Motion Planning and Control
• IS5152 Data-Driven Decision Making
• IS5006 Intelligent System Deployment
• IS4242 Intelligent Systems - Tools, Techniques, and Applications
• BT4014 Analytics Driven Design of Adaptive Systems
• BT4240 Machine Learning for Predictive Data Analytics
*Important:
- Modules in this list may be subject to change as decided by the Departments.
- Modules that are in the core and elective AI lists can be counted as either part of the core or elective requirement, but not both.
Preclusion:
- Students who have previously taken CS4261 is precluded from taking CS5461.