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Showing 25 course outlines from 19204 matches

3726

COMPSCI 742

: Advanced Internet: Global Data Communications
2024 Semester Two (1245)
The course covers wide area networks, global routing, network and protocol performance, buffering and queuing, advanced network measurement, network application performance, content networks, and advanced networking concepts. Recommended preparation: COMPSCI 314 or 315
Subject: Computer Science
No pre-requisites or restrictions
3727

COMPSCI 742

: Advanced Internet: Global Data Communications
2023 Semester Two (1235)
The course covers wide area networks, global routing, network and protocol performance, buffering and queuing, advanced network measurement, network application performance, content networks, and advanced networking concepts.
Subject: Computer Science
Prerequisite: COMPSCI 314 or 315
3728

COMPSCI 742

: Advanced Internet: Global Data Communications
2022 Semester Two (1225)
The protocols and performance of local area networks. The special requirements of very high speed networks (100 Mb/s and higher). Asynchronous transfer mode (ATM) and its relation to other protocols. The TCP/IP suite. Recommended preparation: COMPSCI 314, 315.
Subject: Computer Science
Prerequisite: Approval of the Academic Head or nominee
3729

COMPSCI 742

: Advanced Internet: Global Data Communications
2021 Semester Two (1215)
The protocols and performance of local area networks. The special requirements of very high speed networks (100 Mb/s and higher). Asynchronous transfer mode (ATM) and its relation to other protocols. The TCP/IP suite. Recommended preparation: COMPSCI 314, 315.
Subject: Computer Science
Prerequisite: Approval of the Academic Head or nominee
3730

COMPSCI 742

: Advanced Internet: Global Data Communications
2020 Semester Two (1205)
The protocols and performance of local area networks. The special requirements of very high speed networks (100 Mb/s and higher). Asynchronous transfer mode (ATM) and its relation to other protocols. The TCP/IP suite. Recommended preparation: COMPSCI 314, 315.
Subject: Computer Science
Prerequisite: Approval of the Academic Head or nominee
3731

COMPSCI 747

: Computing Education
2025 Semester One (1253)
An overview of topics related to the use of technology in education and how people learn computer science concepts. Topics include research methodologies used in computer science education, how novices learn to program, and how technology can engage students in active learning, facilitate collaboration and enhance traditional educational practice. Recommended preparation: 30 points at Stage III in Computer Science or COMPSCI 718
Subject: Computer Science
No pre-requisites or restrictions
3732

COMPSCI 747

: Computing Education
2024 Semester One (1243)
An overview of topics related to the use of technology in education and how people learn computer science concepts. Topics include research methodologies used in computer science education, how novices learn to program, and how technology can engage students in active learning, facilitate collaboration and enhance traditional educational practice. Recommended preparation: 30 points at Stage III in Computer Science or COMPSCI 718
Subject: Computer Science
No pre-requisites or restrictions
3733

COMPSCI 747

: Computing Education
2023 Semester One (1233)
An overview of topics related to the use of technology in education and how people learn computer science concepts. Topics include research methodologies used in computer science education, how novices learn to program, and how technology can engage students in active learning, facilitate collaboration and enhance traditional educational practice. Recommended preparation: 30 points at Stage III in Computer Science
Subject: Computer Science
Prerequisite: Approval of the Academic Head or nominee
3734

COMPSCI 747

: Computing Education
2022 Semester One (1223)
An overview of topics related to the use of technology in education and how people learn computer science concepts. Topics include research methodologies used in computer science education, how novices learn to program, and how technology can engage students in active learning, facilitate collaboration and enhance traditional educational practice. Recommended preparation: 30 points at Stage III in Computer Science
Subject: Computer Science
Prerequisite: Approval of the Academic Head or nominee
3735

COMPSCI 747

: Computing Education
2021 Semester One (1213)
An overview of topics related to the use of technology in education and how people learn computer science concepts. Topics include research methodologies used in computer science education, how novices learn to program, and how technology can engage students in active learning, facilitate collaboration and enhance traditional educational practice. Recommended preparation: 30 points at Stage III in Computer Science
Subject: Computer Science
Prerequisite: Approval of the Academic Head or nominee
3736

COMPSCI 750

: Computational Complexity
2025 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
Subject: Computer Science
No pre-requisites or restrictions
3737

COMPSCI 750

: Computational Complexity
2024 Semester Two (1245)
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
Subject: Computer Science
No pre-requisites or restrictions
3738

COMPSCI 750

: Computational Complexity
2023 Semester Two (1235)
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.
Subject: Computer Science
Prerequisite: Approval of the Academic Head or nominee
3739

COMPSCI 750

: Computational Complexity
2022 Semester Two (1225)
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.
Subject: Computer Science
Prerequisite: Approval of the Academic Head or nominee
3740

COMPSCI 750

: Computational Complexity
2021 Semester Two (1215)
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.
Subject: Computer Science
Prerequisite: Approval of the Academic Head or nominee
3741

COMPSCI 750

: Computational Complexity
2020 Semester Two (1205)
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.
Subject: Computer Science
Prerequisite: Approval of the Academic Head or nominee
3742

COMPSCI 751

: Advanced Topics in 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. Research frontiers in database systems. Recommended preparation: COMPSCI 220, 225 or COMPSCI 718
Subject: Computer Science
Restriction: COMPSCI 351, SOFTENG 351
3743

COMPSCI 751

: Advanced Topics in 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. Research frontiers in database systems. Recommended preparation: COMPSCI 220, 225 or COMPSCI 718
Subject: Computer Science
Restriction: COMPSCI 351, SOFTENG 351
3744

COMPSCI 751

: Advanced Topics in 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. Research frontiers in database systems. Recommended preparation: COMPSCI 220, 225.
Subject: Computer Science
Prerequisite: Approval of the Academic Head or nominee
Restriction: COMPSCI 351, SOFTENG 351
3745

COMPSCI 751

: Advanced Topics in 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. Research frontiers in database systems. Recommended preparation: COMPSCI 220, 225.
Subject: Computer Science
Prerequisite: Approval of the Academic Head or nominee
Restriction: COMPSCI 351, SOFTENG 351
3746

COMPSCI 751

: Advanced Topics in 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. Research frontiers in database systems. Recommended preparation: COMPSCI 220, 225.
Subject: Computer Science
Prerequisite: Approval of the Academic Head or nominee
Restriction: COMPSCI 351, SOFTENG 351
3747

COMPSCI 752

: Big Data Management
2025 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
Subject: Computer Science
No pre-requisites or restrictions
3748

COMPSCI 752

: Big Data Management
2024 Semester One (1243)
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
Subject: Computer Science
No pre-requisites or restrictions
3749

COMPSCI 752

: Big Data Management
2023 Semester One (1233)
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 351.
Subject: Computer Science
No pre-requisites or restrictions
3750

COMPSCI 752

: Big Data Management
2022 Semester One (1223)
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 351.
Subject: Computer Science
Prerequisite: Approval of the Academic Head or nominee