8443 modules
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SESA6093 2030-31
Machine Learning for Aerospace Engineering
This course is designed for students and researchers in academia and industry who are focused on advanced topics in aerospace engineering, particularly in aerodynamic loads and aeroelastic analysis predictions. It also caters to technical decision-makers who seek to understand emerging machine learning and projection-based techniques for future development strategies. The content is tailored to equip students with both foundational knowledge and practical skills, ensuring they can apply modern machine learning and reduced-order model techniques to real-world aerospace challenges and make informed decisions in research and industrial settings. -
GGES6031 2026-27
Machine Learning for Geospatial Data Science
The module provides students with practical skills in applied machine learning while fostering a multidisciplinary perspective that integrates remote sensing, GIS, and data science. It introduces a data-driven mindset and builds a bridge between geography and computer/data science. The module will cover fundamentals of programming and data science techniques, application of machine learning/deep learning in geospatial data science and fundamentals of cloud computing. -
ELEC6253 2028-29
Machine Learning for Wireless Communications
The aim of the module is to introduce students to the fundamentals of machine learning and then to apply the advanced machine learning principles for the design and optimisation of wireless communications systems and mobile networks.
Recently, the research and development in wireless communications have been focused on the techniques for the fifth generation (5G) wireless systems and the potential to make these networks intelligent by adding machine learning. Therefore, this course motivates to deliver a general introduction and fundamentals of machine learning followed by the application of machine learning in the design of physical layer techniques in wireless communications and in the optimisation of mobile networks.
Exclusions: Cannot be taken with COMP3222 or COMP3223 or COMP6245 or COMP6246 or COMP6208. -
ELEC6253 2026-27
Machine Learning for Wireless Communications
The aim of the module is to introduce students to the fundamentals of machine learning and then to apply the advanced machine learning principles for the design and optimisation of wireless communications systems and mobile networks.
Recently, the research and development in wireless communications have been focused on the techniques for the fifth generation (5G) wireless systems and the potential to make these networks intelligent by adding machine learning. Therefore, this course motivates to deliver a general introduction and fundamentals of machine learning followed by the application of machine learning in the design of physical layer techniques in wireless communications and in the optimisation of mobile networks.
Exclusions: Cannot be taken with COMP3222 or COMP3223 or COMP6245 or COMP6246 or COMP6208. -
ELEC6253 2029-30
Machine Learning for Wireless Communications
The aim of the module is to introduce students to the fundamentals of machine learning and then to apply the advanced machine learning principles for the design and optimisation of wireless communications systems and mobile networks.
Recently, the research and development in wireless communications have been focused on the techniques for the fifth generation (5G) wireless systems and the potential to make these networks intelligent by adding machine learning. Therefore, this course motivates to deliver a general introduction and fundamentals of machine learning followed by the application of machine learning in the design of physical layer techniques in wireless communications and in the optimisation of mobile networks.
Exclusions: Cannot be taken with COMP3222 or COMP3223 or COMP6245 or COMP6246 or COMP6208. -
ELEC6253 2025-26
Machine Learning for Wireless Communications
The aim of the module is to introduce students to the fundamentals of machine learning and then to apply the advanced machine learning principles for the design and optimisation of wireless communications systems and mobile networks.
Recently, the research and development in wireless communications have been focused on the techniques for the fifth generation (5G) wireless systems and the potential to make these networks intelligent by adding machine learning. Therefore, this course motivates to deliver a general introduction and fundamentals of machine learning followed by the application of machine learning in the design of physical layer techniques in wireless communications and in the optimisation of mobile networks.
Exclusions: Cannot be taken with COMP3222 or COMP3223 or COMP6245 or COMP6246 or COMP6208. -
COMP3222 2027-28
Machine Learning Technologies
Machine Learning is about extracting useful information from large and complex datasets. The module will cover the practical basis of how learning algorithms are can be applied. You will gain hands-on experience in laboratory-bases sessions.
Exclusions: Cannot be taken with COMP3206 or COMP3223 or COMP6229 or COMP6245 or COMP6246. -
COMP3222 2026-27
Machine Learning Technologies
Machine Learning is about extracting useful information from large and complex datasets. The module will cover the practical basis of how learning algorithms are can be applied. You will gain hands-on experience in laboratory-bases sessions.
Exclusions: Cannot be taken with COMP3206 or COMP3223 or COMP6229 or COMP6245 or COMP6246. -
COMP3222 2028-29
Machine Learning Technologies
Machine Learning is about extracting useful information from large and complex datasets. The module will cover the practical basis of how learning algorithms are can be applied. You will gain hands-on experience in laboratory-bases sessions.
Exclusions: Cannot be taken with COMP3206 or COMP3223 or COMP6229 or COMP6245 or COMP6246. -
COMP3222 2025-26
Machine Learning Technologies
Machine Learning is about extracting useful information from large and complex datasets. The module will cover the practical basis of how learning algorithms are can be applied. You will gain hands-on experience in laboratory-bases sessions.
Exclusions: Cannot be taken with COMP3206 or COMP3223 or COMP6229 or COMP6245 or COMP6246.