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Showing 25 course outlines from 527 matches

201

COMPSCI 350

: Mathematical Foundations of Computer Science
2023 Semester One (1233)
The aim of this course is to present mathematical models for programming languages and computation, and derive some theorems regarding what can and cannot be computed. Abstract programming languages (finite automata, context-free grammars, Turing and register machines) are studied. Basic concepts for programming languages, limits on computational power and algorithmic complexity are presented. Church-Turing thesis and quantum computing are briefly and critically discussed.
Subject: Computer Science
Prerequisite: COMPSCI 220 or PHIL 222, and COMPSCI 225 or MATHS 254
202

COMPSCI 350

: Mathematical Foundations of Computer Science
2022 Semester One (1223)
The aim of this course is to present mathematical models for programming languages and computation, and derive some theorems regarding what can and cannot be computed. Abstract programming languages (finite automata, context-free grammars, Turing and register machines) are studied. Basic concepts for programming languages, limits on computational power and algorithmic complexity are presented. Church-Turing thesis and quantum computing are briefly and critically discussed.
Subject: Computer Science
Prerequisite: COMPSCI 220 or PHIL 222, and 15 points from COMPSCI 225, MATHS 254, 255
203

COMPSCI 350

: Mathematical Foundations of Computer Science
2020 Semester One (1203)
The aim of this course is to present mathematical models for programming languages and computation, and derive some theorems regarding what can and cannot be computed. Abstract programming languages (finite automata, context-free grammars, Turing and register machines) are studied. Basic concepts for programming languages, limits on computational power and algorithmic complexity are presented. Church-Turing thesis and quantum computing are briefly and critically discussed.
Subject: Computer Science
Prerequisite: COMPSCI 220 or PHIL 222, and 15 points from COMPSCI 225, MATHS 254, 255
204

COMPSCI 351

: Fundamentals of Database Systems
2025 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.
Subject: Computer Science
Prerequisite: COMPSCI 220, and COMPSCI 225 or MATHS 254
Restriction: COMPSCI 751, SOFTENG 351
205

COMPSCI 351

: Fundamentals of Database Systems
2024 Semester One (1243)
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.
Subject: Computer Science
Prerequisite: COMPSCI 220, and COMPSCI 225 or MATHS 254
Restriction: COMPSCI 751, SOFTENG 351
206

COMPSCI 351

: Fundamentals of Database Systems
2023 Semester One (1233)
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.
Subject: Computer Science
Prerequisite: COMPSCI 220, and COMPSCI 225 or MATHS 254
Restriction: COMPSCI 751, SOFTENG 351
207

COMPSCI 351

: Fundamentals of Database Systems
2022 Semester One (1223)
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.
Subject: Computer Science
Prerequisite: COMPSCI 220 and 15 points from COMPSCI 225, MATHS 254, 255
Restriction: COMPSCI 751, SOFTENG 351
208

COMPSCI 351

: Fundamentals of Database Systems
2021 Semester One (1213)
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.
Subject: Computer Science
Prerequisite: COMPSCI 220 and 15 points from COMPSCI 225, MATHS 254, 255
Restriction: COMPSCI 751, SOFTENG 351
209

COMPSCI 361

: Machine Learning
2025 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. Understand the foundations of machine learning, and introduce practical skills to solve different problems.
Subject: Computer Science
Prerequisite: COMPSCI 220, and 15 points from DATASCI 100, STATS 101, 108, and 15 points from COMPSCI 225, MATHS 254, 255
Restriction: COMPSCI 762
210

COMPSCI 361

: Machine Learning
2024 Semester One (1243)
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. Understand the foundations of machine learning, and introduce practical skills to solve different problems.
Subject: Computer Science
Prerequisite: COMPSCI 220, and 15 points from DATASCI 100, STATS 101, 108, and 15 points from COMPSCI 225, MATHS 254, 255
Restriction: COMPSCI 762
211

COMPSCI 361

: Machine Learning
2023 Semester One (1233)
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. Understand the foundations of machine learning, and introduce practical skills to solve different problems.
Subject: Computer Science
Prerequisite: COMPSCI 220, and 15 points from DATASCI 100, STATS 101, 108, and 15 points from COMPSCI 225, MATHS 254, 255
Restriction: COMPSCI 762
212

COMPSCI 361

: Machine Learning
2022 Semester One (1223)
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. Understand the foundations of machine learning, and introduce practical skills to solve different problems.
Subject: Computer Science
Prerequisite: COMPSCI 220, and 15 points from DATASCI 100, STATS 101, 108, and 15 points from COMPSCI 225, MATHS 254, 255
Restriction: COMPSCI 762
213

COMPSCI 361

: Machine Learning
2021 Semester One (1213)
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. Understand the foundations of machine learning, and introduce practical skills to solve different problems.
Subject: Computer Science
Prerequisite: COMPSCI 220, and 15 points from DATASCI 100, STATS 101, 108, and 15 points from COMPSCI 225, MATHS 254, 255
Restriction: COMPSCI 762
214

COMPSCI 361

: Machine Learning
2020 Semester One (1203)
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. Understand the foundations of machine learning, and introduce practical skills to solve different problems.
Subject: Computer Science
Prerequisite: COMPSCI 220, and 15 points from DATASCI 100, STATS 101, 108, and 15 points from COMPSCI 225, MATHS 254, 255
Restriction: COMPSCI 762
215

COMPSCI 367

: Artificial Intelligence
2025 Semester Two (1255)
Covers algorithms and representational schemes used in artificial intelligence. AI search techniques (e.g., heuristic search, constraint satisfaction, etc.) for solving both optimal and satisficing tasks. Tasks such as game playing (adversarial search), planning, and natural language processing. Discusses and examines the history and future of AI and the ethics surrounding the use of AI in society.
Subject: Computer Science
Prerequisite: COMPSCI 220 and COMPSCI 225 or MATHS 254, or SOFTENG 282 and 284
Restriction: COMPSCI 761
216

COMPSCI 367

: Artificial Intelligence
2024 Semester Two (1245)
Covers algorithms and representational schemes used in artificial intelligence. AI search techniques (e.g., heuristic search, constraint satisfaction, etc.) for solving both optimal and satisficing tasks. Tasks such as game playing (adversarial search), planning, and natural language processing. Discusses and examines the history and future of AI and the ethics surrounding the use of AI in society.
Subject: Computer Science
Prerequisite: COMPSCI 220 and COMPSCI 225 or MATHS 254, or SOFTENG 282 and 284
Restriction: COMPSCI 761
217

COMPSCI 367

: Artificial Intelligence
2023 Semester Two (1235)
Covers algorithms and representational schemes used in artificial intelligence. AI search techniques (e.g., heuristic search, constraint satisfaction, etc.) for solving both optimal and satisficing tasks. Tasks such as game playing (adversarial search), planning, and natural language processing. Discusses and examines the history and future of AI and the ethics surrounding the use of AI in society.
Subject: Computer Science
Prerequisite: COMPSCI 220, and COMPSCI 225 or MATHS 254
Restriction: COMPSCI 761
218

COMPSCI 367

: Artificial Intelligence
2022 Semester Two (1225)
Covers algorithms and representational schemes used in artificial intelligence. AI search techniques (e.g., heuristic search, constraint satisfaction, etc.) for solving both optimal and satisficing tasks. Tasks such as game playing (adversarial search), planning, and natural language processing. Discusses and examines the history and future of AI and the ethics surrounding the use of AI in society.
Subject: Computer Science
Prerequisite: COMPSCI 220 and 15 points from COMPSCI 225, MATHS 254, 255
Restriction: COMPSCI 761
219

COMPSCI 367

: Artificial Intelligence
2021 Semester Two (1215)
Covers algorithms and representational schemes used in artificial intelligence. AI search techniques (e.g., heuristic search, constraint satisfaction, etc.) for solving both optimal and satisficing tasks. Tasks such as game playing (adversarial search), planning, and natural language processing. Discusses and examines the history and future of AI and the ethics surrounding the use of AI in society.
Subject: Computer Science
Prerequisite: COMPSCI 220 and 15 points from COMPSCI 225, MATHS 254, 255
Restriction: COMPSCI 761
220

COMPSCI 367

: Artificial Intelligence
2020 Semester Two (1205)
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.
Subject: Computer Science
Prerequisite: COMPSCI 220 and 15 points from COMPSCI 225, MATHS 254, 255
Restriction: COMPSCI 761
221

COMPSCI 369

: Computational Methods in Interdisciplinary Science
2025 Semester One (1253)
Many sciences use computational methods that involve the development and application of computer algorithms and software to answer scientific questions. This course looks at how to tackle these interdisciplinary problems through methods like probabilistic computer modelling, computer-based statistical inference, and computer simulations. The material is largely motivated by the life sciences but also uses examples from other sciences. It focuses on modelling and analysing real-world data with an emphasis on analysing DNA sequence data. No background in physical or life sciences is assumed.
Subject: Computer Science
Prerequisite: COMPSCI 220, and COMPSCI 225 or MATHS 254
222

COMPSCI 369

: Computational Methods in Interdisciplinary Science
2024 Semester One (1243)
Many sciences use computational methods that involve the development and application of computer algorithms and software to answer scientific questions. This course looks at how to tackle these interdisciplinary problems through methods like probabilistic computer modelling, computer-based statistical inference, and computer simulations. The material is largely motivated by the life sciences but also uses examples from other sciences. It focuses on modelling and analysing real-world data with an emphasis on analysing DNA sequence data. No background in physical or life sciences is assumed.
Subject: Computer Science
Prerequisite: COMPSCI 220, and COMPSCI 225 or MATHS 254
223

COMPSCI 369

: Computational Methods in Interdisciplinary Science
2023 Semester One (1233)
Many sciences use computational methods that involve the development and application of computer algorithms and software to answer scientific questions. This course looks at how to tackle these interdisciplinary problems through methods like probabilistic computer modelling, computer-based statistical inference, and computer simulations. The material is largely motivated by the life sciences but also uses examples from other sciences. It focuses on modelling and analysing real-world data with an emphasis on analysing DNA sequence data. No background in physical or life sciences is assumed.
Subject: Computer Science
Prerequisite: COMPSCI 220, and COMPSCI 225 or MATHS 254
224

COMPSCI 369

: Computational Methods in Interdisciplinary Science
2022 Semester One (1223)
Many sciences use computational methods that involve the development and application of computer algorithms and software to answer scientific questions. This course looks at how to tackle these interdisciplinary problems through methods like probabilistic computer modelling, computer-based statistical inference, and computer simulations. The material is largely motivated by the life sciences but also uses examples from other sciences. It focuses on modelling and analysing real-world data with an emphasis on analysing DNA sequence data. No background in physical or life sciences is assumed.
Subject: Computer Science
Prerequisite: COMPSCI 220 and 15 points from COMPSCI 225, MATHS 254, 255
225

COMPSCI 373

: Computer Graphics and Image Processing
2025 Semester One (1253)
Basic geometric processes including transformations; viewing and projection; back projection and ray tracing. Graphics modelling concepts: primitives, surfaces, and scene graphs, lighting and shading, texture mapping, and curve and surface design. Graphics and image processing fundamentals: image definition and representation, perception and colour models, grey level and colour enhancement, neighbourhood operations and filtering. Use of the OpenGL graphics pipeline.
Subject: Computer Science
Prerequisite: COMPSCI 210, 230, or COMPSYS 201 and SOFTENG 281
Restriction: COMPSCI 771