8285 modules
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COMP6207 2028-29
Algorithmic Game Theory
This module:
- Introduces the students to the key issues of interaction of multiple self-interested parties (a.k.a. agents) and gives a broad survey of topics at the interface of theoretical computer science and game theory dealing with such interactions.
- Provides the theoretical background and practical tools to solve problems arising in settings with self-interested participants, to predict possible behaviour and outcomes, and finally, to design multi-agent systems that would incentivise desirable behaviour.
- Introduces the students to the specifics of computational game-theoretic techniques in different application areas, ranging from multi-agent systems, electronic marketplaces and networked computer systems to computational biology and social networks.
- Extends and advances the knowledge obtained in other AI modules (in particular, COMP6203 Intelligent Agents). -
ARTD1139 2025-26
Algorithmic Thinking & Methods
This module builds on the foundational skills and knowledge established in Creative Computing I to develop a more sustained application of coding to creative technological approaches to art and design. You will be introduced to more advanced programming principles and languages. The concept of the algorithm – the process or rule-based nature of computing – will be explored and applied to set of individual and team-based exercises that might include game-like rules and applications, augmented reality (AR) experiences, physical computing (e.g. Arduino) and further experiments with image manipulation, robotics and AI. -
ARTD1139 2026-27
Algorithmic Thinking & Methods
This module builds on the foundational skills and knowledge established in Creative Computing I to develop a more sustained application of coding to creative technological approaches to art and design. You will be introduced to more advanced programming principles and languages. The concept of the algorithm – the process or rule-based nature of computing – will be explored and applied to set of individual and team-based exercises that might include game-like rules and applications, augmented reality (AR) experiences, physical computing (e.g. Arduino) and further experiments with image manipulation, robotics and AI. -
COMP1324 2026-27
Algorithmics
This module teaches the basic data structures and algorithms which underpins modern software engineering. Without these algorithms most software would be hopelessly slow to the point of unusability. The course also teaches the principles behind the algorithms and data structures and the software engineering lessons which data structures and algorithms teach us. -
COMP1324 2025-26
Algorithmics
This module teaches the basic data structures and algorithms which underpins modern software engineering. Without these algorithms most software would be hopelessly slow to the point of unusability. The course also teaches the principles behind the algorithms and data structures and the software engineering lessons which data structures and algorithms teach us. -
MATH2014 2026-27
Algorithms
Algorithms are systematic methods for solving mathematical problems, such as sorting numbers in ascending order, finding the cheapest way to ship goods on the road network or finding the shortest path in a graph. They can be regarded as practical applications of mathematical proofs, and also as theoretical models of computational techniques. This module introduces some basic concepts related to algorithms, their implementation and their efficiency, using simple examples drawn from many areas of mathematics including Graph Theory and Operational Research (no previous knowledge of these topics is required, but having taken MATH1058 may help). The main aim of the module is designing algorithms for solving a wide range of problems, studying their computational complexity, and understanding whether a given problem may or may not admit an efficient algorithm for its solution. -
MATH2014 2027-28
Algorithms
Algorithms are systematic methods for solving mathematical problems, such as sorting numbers in ascending order, finding the cheapest way to ship goods on the road network or finding the shortest path in a graph. They can be regarded as practical applications of mathematical proofs, and also as theoretical models of computational techniques. This module introduces some basic concepts related to algorithms, their implementation and their efficiency, using simple examples drawn from many areas of mathematics including Graph Theory and Operational Research (no previous knowledge of these topics is required, but having taken MATH1058 may help). The main aim of the module is designing algorithms for solving a wide range of problems, studying their computational complexity, and understanding whether a given problem may or may not admit an efficient algorithm for its solution. -
MATH2014 2028-29
Algorithms
Algorithms are systematic methods for solving mathematical problems, such as sorting numbers in ascending order, finding the cheapest way to ship goods on the road network or finding the shortest path in a graph. They can be regarded as practical applications of mathematical proofs, and also as theoretical models of computational techniques. This module introduces some basic concepts related to algorithms, their implementation and their efficiency, using simple examples drawn from many areas of mathematics including Graph Theory and Operational Research (no previous knowledge of these topics is required, but having taken MATH1058 may help). The main aim of the module is designing algorithms for solving a wide range of problems, studying their computational complexity, and understanding whether a given problem may or may not admit an efficient algorithm for its solution. -
AICE1005 2025-26
Algorithms and Analysis
Algorithms and Analytics provides an introduction to core data structures and algorithms as well as the analytical tools to understand their performance. It covers the usage of algorithms for problem solving, their implementations in different programming languages and a theoretical understanding of their time and space complexity including NP-completeness. The algorithms covered include lists, sets, map, searching, sorting, graph algorithms, optimisation and random number generation, which are prevalent throughout software used in AI and Computer Engineering. -
AICE1005 2026-27
Algorithms and Analysis
Algorithms and Analytics provides an introduction to core data structures and algorithms as well as the analytical tools to understand their performance. It covers the usage of algorithms for problem solving, their implementations in different programming languages and a theoretical understanding of their time and space complexity including NP-completeness. The algorithms covered include lists, sets, map, searching, sorting, graph algorithms, optimisation and random number generation, which are prevalent throughout software used in AI and Computer Engineering.