
Artificial Intelligence and Machine Learning — Master’s
Supervised and unsupervised learning, neural networks and their practical applications.
Deep learning architectures and research methodology.
Topics are grouped into chapters and listed in reading order.
2 topics
Convolutional layers, filters, pooling and CNN architecture: how a network learns the spatial structure of images. You will meet LeNet and ResNet, data augmentation and transfer learning.
Chapter 1. Deep learning2 min
The stages of choosing a dissertation topic, formulating a research question and hypothesis, and reviewing the literature. Learn to evaluate sources critically and follow research ethics.
Chapter 2. Research methodology2 min
Textbooks and study guides for this level.

Supervised and unsupervised learning, neural networks and their practical applications.