Course Description
This course introduces fundamental concepts and skills associated with the design and implementation of different natural language processing systems covered from morphology, syntax and semantics. The main topics include regular expressions, (weighted) minimum edit distance, language modelling, Nävie Bayes (generative model), maximum entropy (discriminative model), text classification, sequence labelling, POS tagging, syntax parsing and computational lexical semantics. The course also includes an overview of practical natural language processing applications.
Intended Learning Outcomes
CILO-1: An ability to apply knowledge of mathematics, science, and engineering.
CILO-2: An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability.
CILO-3: An ability to identify, formulate, and solve engineering problems.
CILO-4: An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice.