CIT2010 Machine Learning
Students will explore key topics such as supervised and unsupervised learning, classification, regression, clustering, and model evaluation. Through hands-on exercises, they will apply techniques including decision trees, k-means clustering, and basic neural networks for predictive modeling and pattern discovery. The course emphasizes practical implementation using industry-standard tools, along with essential skills in data preprocessing and model validation.
Prerequisite
CIT1020 Introduction to Artificial Intelligence