Search Course Outline
Showing 25 course outlines from 529 matches
276
COMPSCI 711
: Parallel and Distributed Computing2023 Semester One (1233)
Computer architectures and languages for exploring parallelism, conceptual models of parallelism, principles for programming in a parallel environment, different models to achieve interprocess communication, concurrency control, distributed algorithms and fault tolerance.
Prerequisite: COMPSCI 320 or 335
277
COMPSCI 711
: Parallel and Distributed Computing2022 Semester One (1223)
Computer architectures and languages for exploring parallelism, conceptual models of parallelism, principles for programming in a parallel environment, different models to achieve interprocess communication, concurrency control, distributed algorithms and fault tolerance. Recommended preparation: COMPSCI 335.
Prerequisite: Approval of the Academic Head or nominee
278
COMPSCI 711
: Parallel and Distributed Computing2021 Semester Two (1215)
Computer architectures and languages for exploring parallelism, conceptual models of parallelism, principles for programming in a parallel environment, different models to achieve interprocess communication, concurrency control, distributed algorithms and fault tolerance. Recommended preparation: COMPSCI 335.
Prerequisite: Approval of the Academic Head or nominee
279
COMPSCI 711
: Parallel and Distributed Computing2020 Semester Two (1205)
Computer architectures and languages for exploring parallelism, conceptual models of parallelism, principles for programming in a parallel environment, different models to achieve interprocess communication, concurrency control, distributed algorithms and fault tolerance. Recommended preparation: COMPSCI 335.
Prerequisite: Approval of the Academic Head or nominee
280
COMPSCI 712
: AI Agency, Ethics and Society2025 Semester One (1253)
Introduces students to a range of philosophical and normative topics relating to artificial intelligence. Examines key ideas of intelligence, privacy, consent, and discusses other ethical issues that arise in the development and use of AI. The importance of Māori rights and interests in AI and data are explored. Possible approaches to addressing these various concerns are considered.
No pre-requisites or restrictions
281
COMPSCI 712
: AI Agency, Ethics and Society2024 Semester One (1243)
Introduces students to a range of philosophical and normative topics relating to artificial intelligence. Examines key ideas of intelligence, privacy, consent, and discusses other ethical issues that arise in the development and use of AI. The importance of Māori rights and interests in AI and data are explored. Possible approaches to addressing these various concerns are considered.
No pre-requisites or restrictions
282
COMPSCI 713
: AI Fundamentals2025 Semester One (1253)
Examines the core concepts and techniques in AI, including breakthroughs in symbolic AI, machine learning, and neural networks. Real-world applications are presented, with a focus on AI research in Aotearoa/NZ and ethical considerations. The course is designed to be accessible to students with limited programming experience.
No pre-requisites or restrictions
283
COMPSCI 713
: AI Fundamentals2024 Semester One (1243)
Examines the core concepts and techniques in AI, including breakthroughs in symbolic AI, machine learning, and neural networks. Real-world applications are presented, with a focus on AI research in Aotearoa/NZ and ethical considerations. The course is designed to be accessible to students with limited programming experience.
No pre-requisites or restrictions
284
COMPSCI 714
: AI Architecture and Design2025 Semester One (1253)
Equips students with the ability to develop AI applications by introducing well-established AI frameworks and using web-based interactive computing platforms. Students will acquire the skills to implement simple AI techniques using these frameworks and evaluate their performance. Introduces basic practical technologies to investigate artificial intelligence techniques.
No pre-requisites or restrictions
285
COMPSCI 714
: AI Architecture and Design2024 Semester One (1243)
Equips students with the ability to develop AI applications by introducing well-established AI frameworks and using web-based interactive computing platforms. Students will acquire the skills to implement simple AI techniques using these frameworks and evaluate their performance. Introduces basic practical technologies to investigate artificial intelligence techniques.
No pre-requisites or restrictions
286
COMPSCI 715
: Advanced Computer Graphics2025 Semester Two (1255)
An advanced look at current research issues in computer graphics. Typical topics include: ray-tracing acceleration methods; radiosity; subdivision surfaces; physically-based modelling; animation; image-based lighting and rendering; non-photorealistic rendering; advanced texturing. Recommended preparation: COMPSCI 373
Prerequisite: Approval of the Academic Head or nominee
287
COMPSCI 715
: Advanced Computer Graphics2024 Semester Two (1245)
An advanced look at current research issues in computer graphics. Typical topics include: ray-tracing acceleration methods; radiosity; subdivision surfaces; physically-based modelling; animation; image-based lighting and rendering; non-photorealistic rendering; advanced texturing. Recommended preparation: COMPSCI 373
Prerequisite: Approval of the Academic Head or nominee
288
COMPSCI 715
: Advanced Computer Graphics2023 Semester Two (1235)
An advanced look at current research issues in computer graphics. Typical topics include: ray-tracing acceleration methods; radiosity; subdivision surfaces; physically-based modelling; animation; image-based lighting and rendering; non-photorealistic rendering; advanced texturing. The precise content may vary from year to year. Consult the department for details. Recommended preparation: COMPSCI 373 or equivalent, and 15 points at Stage II in Mathematics.
Prerequisite: Approval of the Academic Head or nominee
289
COMPSCI 715
: Advanced Computer Graphics2022 Semester Two (1225)
An advanced look at current research issues in computer graphics. Typical topics include: ray-tracing acceleration methods; radiosity; subdivision surfaces; physically-based modelling; animation; image-based lighting and rendering; non-photorealistic rendering; advanced texturing. The precise content may vary from year to year. Consult the department for details. Recommended preparation: COMPSCI 373 or equivalent, and 15 points at Stage II in Mathematics.
Prerequisite: Approval of the Academic Head or nominee
290
COMPSCI 715
: Advanced Computer Graphics2021 Semester Two (1215)
An advanced look at current research issues in computer graphics. Typical topics include: ray-tracing acceleration methods; radiosity; subdivision surfaces; physically-based modelling; animation; image-based lighting and rendering; non-photorealistic rendering; advanced texturing. The precise content may vary from year to year. Consult the department for details. Recommended preparation: COMPSCI 373 or equivalent, and 15 points at Stage II in Mathematics.
Prerequisite: Approval of the Academic Head or nominee
291
COMPSCI 715
: Advanced Computer Graphics2020 Semester Two (1205)
An advanced look at current research issues in computer graphics. Typical topics include: ray-tracing acceleration methods; radiosity; subdivision surfaces; physically-based modelling; animation; image-based lighting and rendering; non-photorealistic rendering; advanced texturing. The precise content may vary from year to year. Consult the department for details. Recommended preparation: COMPSCI 373 or equivalent, and 15 points at Stage II in Mathematics.
Prerequisite: Approval of the Academic Head or nominee
292
COMPSCI 717
: Fundamentals of Algorithmics2025 Semester Two (1255)
Fundamental techniques are covered for the design of algorithms such as greedy algorithms, divide-and-conquer, and dynamic programming. Data structures are explored that help implement algorithms. Essential tools are taught for analysing algorithms, for example worst- and average-case analyses of space and time. Recommended preparation: COMPSCI 120, 130
Restriction: COMPSCI 220, 320, SOFTENG 250, 284
293
COMPSCI 717
: Fundamentals of Algorithmics2025 Semester One (1253)
Fundamental techniques are covered for the design of algorithms such as greedy algorithms, divide-and-conquer, and dynamic programming. Data structures are explored that help implement algorithms. Essential tools are taught for analysing algorithms, for example worst- and average-case analyses of space and time. Recommended preparation: COMPSCI 120, 130
Restriction: COMPSCI 220, 320, SOFTENG 250, 284
294
COMPSCI 717
: Fundamentals of Algorithmics2024 Semester One (1243)
Fundamental techniques are covered for the design of algorithms such as greedy algorithms, divide-and-conquer, and dynamic programming. Data structures are explored that help implement algorithms. Essential tools are taught for analysing algorithms, for example worst- and average-case analyses of space and time. Recommended preparation: COMPSCI 120, 130
Restriction: COMPSCI 220, 320, SOFTENG 250, 284
295
COMPSCI 717
: Fundamentals of Algorithmics2023 Semester One (1233)
Fundamental techniques are covered for the design of algorithms such as greedy algorithms, divide-and-conquer, and dynamic programming. Data structures are explored that help implement algorithms. Essential tools are taught for analysing algorithms, for example worst- and average-case analyses of space and time. Recommended preparation: 15 points from COMPSCI 120 or equivalent and 15 points from COMPSCI 130 or equivalent
Prerequisite: Approval of Academic Head or nominee
Restriction: COMPSCI 220, 320, SOFTENG 250
Restriction: COMPSCI 220, 320, SOFTENG 250
296
COMPSCI 717
: Fundamentals of Algorithmics2022 Semester One (1223)
Fundamental techniques are covered for the design of algorithms such as greedy algorithms, divide-and-conquer, and dynamic programming. Data structures are explored that help implement algorithms. Essential tools are taught for analysing algorithms, for example worst- and average-case analyses of space and time. Recommended preparation: 15 points from COMPSCI 120 or equivalent and 15 points from COMPSCI 130 or equivalent
Prerequisite: Approval of Academic Head or nominee
Restriction: COMPSCI 220, 320, SOFTENG 250
Restriction: COMPSCI 220, 320, SOFTENG 250
297
COMPSCI 717
: Fundamentals of Algorithmics2021 Semester One (1213)
Fundamental techniques are covered for the design of algorithms such as greedy algorithms, divide-and-conquer, and dynamic programming. Data structures are explored that help implement algorithms. Essential tools are taught for analysing algorithms, for example worst- and average-case analyses of space and time. Recommended preparation: 15 points from COMPSCI 120 or equivalent and 15 points from COMPSCI 130 or equivalent
Prerequisite: Approval of Academic Head or nominee
Restriction: COMPSCI 220, 320, SOFTENG 250
Restriction: COMPSCI 220, 320, SOFTENG 250
298
COMPSCI 717
: Fundamentals of Algorithmics2020 Semester One (1203)
Fundamental techniques are covered for the design of algorithms such as greedy algorithms, divide-and-conquer, and dynamic programming. Data structures are explored that help implement algorithms. Essential tools are taught for analysing algorithms, for example worst- and average-case analyses of space and time. Recommended preparation: 15 points from COMPSCI 120 or equivalent and 15 points from COMPSCI 130 or equivalent
Prerequisite: Approval of Academic Head or nominee
Restriction: COMPSCI 220, 320, SOFTENG 250
Restriction: COMPSCI 220, 320, SOFTENG 250
299
COMPSCI 718
: Programming for Industry2025 Late Year Term (1257)
An examination of object-oriented programming and design. Key principles of object-oriented programming: typing, encapsulation, inheritance, polymorphism and composition. Fundamental object-oriented modelling and design techniques. Students will develop application software of reasonable complexity that draws on object-oriented language features, and contemporary APIs, frameworks and tools.
No pre-requisites or restrictions
300
COMPSCI 718
: Programming for Industry2025 Semester Two (1255)
An examination of object-oriented programming and design. Key principles of object-oriented programming: typing, encapsulation, inheritance, polymorphism and composition. Fundamental object-oriented modelling and design techniques. Students will develop application software of reasonable complexity that draws on object-oriented language features, and contemporary APIs, frameworks and tools.
No pre-requisites or restrictions