Deep Learning

This course prepares students to explain the concepts of artificial neural networks and deep learning, implement CNN, RNN and Transformer architectures to solve problems, and apply training and optimisation techniques for deep learning models. Study materials: Artificial Intelligence (AI).

Topics

1. Artificial neural networks and backpropagation
2. Convolutional neural networks (CNN)
3. Recurrent neural networks (RNN)
4. Transformer architecture and attention mechanisms
5. Training and regularisation techniques
6. Model optimisation algorithms
7. Performance evaluation of deep learning models

Each course outcome derives from one programme outcome.

1. CPMK-AIDE-02

   Students are able to build an applied decision basis by optimising computing performance through simultaneous processing, and apply the principles of computing ethics

   CPLP03
2. CPMK-AIDE-01

   Students are able to design and implement advanced artificial intelligence modelling to analyse diverse large-volume data through the management of structured data storage infrastructure.

   CPLP03

CPLP03

Develop advanced artificial intelligence models and manage big data, and build applied decision support with attention to optimal performance and computing ethics.