Showing 25 course outlines from 126 matches
76
COMPSCI 750
: Computational Complexity2025 Semester Two (1255)
Definitions of computational models and complexity classes: time complexity (e.g., P and NP), space complexity (e.g., L and PSPACE), circuit and parallel complexity (NC), polynomial-time hierarchy (PH), interactive complexity (IP), probabilistic complexity (BPP), and fixed-parameter complexity. Recommended preparation: COMPSCI 320 or 350
No pre-requisites or restrictions
77
COMPSCI 751
: Advanced Topics in Database Systems2025 Semester One (1253)
Database principles. Relational model, relational algebra, relational calculus, SQL, SQL and programming languages, entity-relationship model, normalisation, query processing and query optimisation, ACID transactions, transaction isolation levels, database recovery, database security, databases and XML. Research frontiers in database systems. Recommended preparation: COMPSCI 220, 225 or COMPSCI 718
Restriction: COMPSCI 351, SOFTENG 351
78
COMPSCI 752
: Big Data Management2025 Semester One (1253)
The deep diversity of modern-day data from many companies requires data scientists to master many technologies that rely on new principles to represent, describe, access, and analyse data. The course will provide insight into the rich landscape of big data modelling, management, and analysis in distributed and heterogeneous environments. Recommended preparation: COMPSCI 220, 351
No pre-requisites or restrictions
79
COMPSCI 753
: Algorithms for Massive Data2025 Semester Two (1255)
Modern enterprises and applications such as electronic commerce, social networks, location services, and scientific databases are generating data on a massive scale. Analysis of such data must be carried out by scalable algorithms. This course exposes data science practitioners and researchers to various advanced algorithms for processing and mining massive data, and explores best-practices and state-of-the-art developments in big data. Recommended preparation: COMPSCI 320
No pre-requisites or restrictions
80
COMPSCI 760
: Advanced Topics in Machine Learning2025 Semester Two (1255)
An overview of the learning problem and the view of learning by search. Covers advanced techniques for learning such as: decision tree learning, rule learning, exhaustive learning, Bayesian learning, genetic algorithms, reinforcement learning, neural networks, explanation-based learning and inductive logic programming. Advanced experimental methods necessary for understanding machine learning research.
Prerequisite: COMPSCI 361 or 762
81
COMPSCI 760
: Advanced Topics in Machine Learning2025 Semester One (1253)
An overview of the learning problem and the view of learning by search. Covers advanced techniques for learning such as: decision tree learning, rule learning, exhaustive learning, Bayesian learning, genetic algorithms, reinforcement learning, neural networks, explanation-based learning and inductive logic programming. Advanced experimental methods necessary for understanding machine learning research.
Prerequisite: COMPSCI 361 or 762
82
COMPSCI 761
: Advanced Topics in Artificial Intelligence2025 Semester Two (1255)
Examines the cornerstones of AI: representation, utilisation, and acquisition of knowledge. Taking a real-world problem and representing it in a computer so that the computer can do inference. Utilising this knowledge and acquiring new knowledge is done by search which is the main technique behind planning and machine learning. Research frontiers in artificial intelligence.
Prerequisite: COMPSCI 220 and 225, or COMPSCI 220 and MATHS 254, or COMPSCI 713 and 714, or COMPSCI 718
Restriction: COMPSCI 367
Restriction: COMPSCI 367
83
COMPSCI 762
: Foundations of Machine Learning2025 Semester One (1253)
Machine learning is a branch of artificial intelligence concerned with making accurate, interpretable, computationally efficient, and robust inferences from data to solve a given problem. Students will be introduced to the foundations of machine learning and will gain practical skills to solve different problems. Students will explore research frontiers in machine learning.
Prerequisite: COMPSCI 713 and 714, or COMPSCI 718, or 15 points from DATASCI 100, STATS 101, 108 and COMPSCI 220 or 717 and COMPSCI 225 or MATHS 254
Restriction: COMPSCI 361
Restriction: COMPSCI 361
84
COMPSCI 764
: Deep Learning2025 Semester Two (1255)
Critically analyses the fundamentals of deep neural networks alongside current state-of-the-art advancements in this field. Students will acquire specialised knowledge in state-of-the-art deep learning architectures and gain the ability to apply deep learning in various fields, including natural language processing and computer vision. Includes a significant individual research project.
Prerequisite: COMPSCI 361 or 762, or COMPSCI 713 and 714
85
COMPSCI 765
: Modelling Minds2025 Semester One (1253)
How can researchers of artificial intelligence effectively model subjective aspects of minds, such as emotional states, desires, perceptual experience and intrinsic goals? This course draws upon interdisciplinary methods and considers classic and emerging approaches to try to answer this question. Recommended preparation: COMPSCI 367
No pre-requisites or restrictions
86
COMPSCI 767
: Intelligent Software Agents2025 Semester One (1253)
An introduction to the design, implementation and use of intelligent software agents (e.g., knowbots, softbots etc). Reviews standard artificial intelligence problem-solving paradigms (e.g., planning and expert systems) and knowledge representation formalisms (e.g., logic and semantic nets). Surveys agent architectures and multi-agent frameworks.
Prerequisite: COMPSCI 367 or 761, or COMPSCI 713 and 714
87
COMPSCI 769
: Natural Language Processing2025 Semester Two (1255)
Examines the progress in enabling AI systems to use natural language for communication and knowledge storage. Explores knowledge formalisation, storage, multiple knowledge systems, theory formation, and the roles and risks of belief, explanation, and argumentation in AI. Includes a significant individual research project.
Prerequisite: COMPSCI 361 or 762, or COMPSCI 713 and 714
88
COMPSCI 773
: Intelligent Vision Systems2025 Semester One (1253)
Computational methods and techniques for computer vision are applied to real-world problems such as 2/3D face biometrics, autonomous navigation, and vision-guided robotics based on 3D scene description. A particular feature of the course work is the emphasis on complete system design. Recommended preparation: COMPSCI 373 and 15 points at Stage II in Mathematics
No pre-requisites or restrictions
89
COMPSCI 780
: Postgraduate Project in Computer Science 12025 Summer School (1250)
Prerequisite: Approval of Academic Head or nominee
Restriction: COMPSCI 691 To complete this course students must enrol in COMPSCI 780 A and B, or COMPSCI 780
Restriction: COMPSCI 691 To complete this course students must enrol in COMPSCI 780 A and B, or COMPSCI 780
90
COMPSCI 1000MC
: Cyber Forensics and Security2025 Quarter Four (1258)
No pre-requisites or restrictions
Outline is not available yet
91
COMPSCI 1000MC
: Cyber Forensics and Security2025 Quarter Three (1256)
No pre-requisites or restrictions
Outline is not available yet
92
COMPSCI 1000MC
: Cyber Forensics and Security2025 Quarter Two (1254)
No pre-requisites or restrictions
Outline is not available yet
93
COMPSCI 1001MC
: Data Visualisation and Business Intelligence2025 Quarter Four (1258)
No pre-requisites or restrictions
Outline is not available yet
94
COMPSCI 1001MC
: Data Visualisation and Business Intelligence2025 Quarter Three (1256)
No pre-requisites or restrictions
Outline is not available yet
95
COMPSCI 1001MC
: Data Visualisation and Business Intelligence2025 Quarter Two (1254)
No pre-requisites or restrictions
Outline is not available yet
96
COMPSCI 289
: Research Seminar in Computer Science2025 Semester Two (1255)
An introduction to research topics in computer science. Students will be expected to prepare and deliver a review of research in a topic of their choice. Research articles will be provided during the course, and will consist of key scientific publications.
Prerequisite: Minimum GPA of 5.0 and COMPSCI 110, 120, 130
Outline is not available yet
97
COMPSCI 690A
: Graduate Diploma Research Project2025 Semester One (1253)
Restriction: COMPSCI 380
To complete this course students must enrol in COMPSCI 690 A and B
Outline is not available yet
98
COMPSCI 691B
: Postgraduate Diploma Research Project2025 Semester Two (1255)
Restriction: COMPSCI 780
To complete this course students must enrol in COMPSCI 691 A and B
99
COMPSCI 7000MC
: Cloud Computing for Business Professionals2025 Quarter Four (1258)
No pre-requisites or restrictions
Outline is not available yet
100
COMPSCI 7000MC
: Cloud Computing for Business Professionals2025 Quarter Three (1256)
No pre-requisites or restrictions
Outline is not available yet