Overview

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Academic contacts

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Offerings

DUBAI-ISC-TJD-INT-2023-2023
DUBAI-ISC-TSD-INT-2023-2023
KAPLAN-SGP-TJA-INT-2023-2023
KAPLAN-SGP-TMA-INT-2022-2022
KAPLAN-SGP-TMA-INT-2024-2024
KAPLAN-SGP-TSA-INT-2023-2023
MURDOCH-S1-EXT-2022-ONGOING
MURDOCH-S1-INT-2018-ONGOING

Requisites

Enrolment rules

Enrolment in a graduate-level IT course.

Other learning activities

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Learning activities

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Learning outcomes

1.

Provide critical analysis of the AI paradigms, with their advantages over traditional computing
approaches in solving real world problems

2.

Explain the theoretical foundations of various types of AI technologies for specific applications with focus on data intensive applications

3.

Evaluate AI systems and, in particular, their suitability and shortcomings for specific applications and
domains

4.

Demonstrate and discuss the use of AI tools available for developing AI systems.

5.

Articulate the ethical and societal implications of AI.

Assessments

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Additional information

Unit content:

* Introduction to AI Systems * Knowledge Engineering * Problem Solving * Knowledge and Reasoning *
Rule-Based Systems * Fuzzy Systems * Machine Learning * Genetic and Evolutionary Algorithms * AI
Applications * Ethics and Safety of AI