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    Modern AI representation systems and problem-solving techniques with a particular emphasis on machine learning.

    About this paper

    Paper title Advanced Artificial Intelligence
    Subject Artificial Intelligence
    EFTS 0.1667
    Points 20 points
    Teaching period Semester 2 (On campus)
    Domestic Tuition Fees ( NZD ) $1,448.79
    International Tuition Fees Tuition Fees for international students are elsewhere on this website.
    COSC 343
    Students with limited programming experience should also take AIML 401.

    Computer Science Adviser

    Teaching staff

    Dr Lech Szymanski (Lecturer)

    Paper Structure

    In this paper we will focus on the hard problems to be solved in artificial intelligence (AI), concentrating on the issue of how to get information about the world and how to make use of it. We will consider techniques for machine learning and probabilistic reasoning. Almost every human ability results from learning from experience: we will look at how these learning processes can be modelled computationally.

    Topics to be considered include:

    • Search and optimisation algorithms (including genetic algorithms)
    • Probabilistic reasoning methods (including Bayesian methods)
    • Machine learning algorithms (with a focus on neural networks and deep learning)
    Teaching Arrangements

    There are two lectures per week, weekly lab sessions, and three tutorials.


    Artificial Intelligence: A Modern Approach (Fourth Edition), by Stuart Russell and Peter Norvig, Pearson 2020.

    Graduate Attributes Emphasised

    Interdisciplinary perspective, Scholarship, Communication, Ethics
    View more information about Otago's graduate attributes.

    Learning Outcomes

    Students who successfully complete the paper will:

    • Gain a practical understanding of a selection of core concepts in AI research: planning and search, probabilistic reasoning, machine learning, decision trees, neural networks, sequential decisions, and deep learning.
    • Strengthen their understanding of each core concept through practical exercises and experience with implemented systems.


    Semester 2

    Teaching method
    This paper is taught On Campus
    Learning management system

    Computer Lab

    Stream Days Times Weeks
    A1 Wednesday 16:00-17:50 29-35, 37-42


    Stream Days Times Weeks
    A1 Monday 09:00-09:50 29-35, 37-42
    Wednesday 09:00-09:50 29-35, 37-42


    Stream Days Times Weeks
    A1 Tuesday 09:00-10:50 37-39
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