Applied Natural Language Processing

    Unit code: NIT6003 | Study level: Postgraduate
    (Generally, 1 credit = 10 hours of classes and independent study.)
    City Campus
    Footscray Park
    Online Real Time
    VU Brisbane
    VU Sydney
    NIT5150 - Advanced Object Oriented Programming
    (Or equivalent to be determined by unit coordinator)


    This unit applies machine learning and deep learning techniques to obtain leading results on solving the problems of natural language processing (NLP). NLP is considered as a critical step to create effective communications and interactions between machines and human beings. Through these applications in NLP the students will learn about the basic concepts of NLP, methodologies to represent human natural language in machines, and the application of cutting-edge techniques to train machines to achieve human-like abilities to understand natural language in a more effective way. The students will learn how to use machines to comprehend text that are used in most AI systems. Using the technology students will apply human factors and ethical considerations to the design and development of solutions to real world problems.

    Learning Outcomes

    On successful completion of this unit, students will be able to:

    1. Critically review natural language processing (NLP) applications and developments;
    2. Disaggregate and appraise the components in a typical NLP application architecture;
    3. Investigate and apply knowledge discovery processes and associated models to complex NLP application scenarios;
    4. Analyse state-of-art NLP techniques and evaluate the performance using various datasets; and
    5. Extrapolate knowledge and skills to design and develop an NLP application to support sustainable innovation, understand the importance of human factors and ethical considerations and provide business solutions.


    For Melbourne campuses

    Assessment type: Laboratory Work
    Grade: 20%
    Lab submission (2)
    Assessment type: Project
    Grade: 40%
    Projects (2)
    Assessment type: Case Study
    Grade: 40%
    In-class Problem Solving Case Study for a scenario based real world problem (concepts, modelling, programming and scenario analysis)

    Required reading

    Speech and language processing: an introduction to natural language processing, computational linguistics, and speech recognition
    Jurafsky, D & Martin, JH (2020)| Stanford University.

    As part of a course

    This unit is studied as part of the following course(s):

    Search for units, majors & minors