This course is for students interested in the art and science of computer programming. It is concerned with advanced data structures and their algorithms. It involves a study of classical and recently discovered methods for solving a diverse range of computational problems. Analysis of important performance characteristics (such as efficiency, scalability, applicability, adaptability, and design) will also be addressed. A survey of problem spaces and techniques for addressing specific examples using useful/interesting algorithms and data structures is offered. Examples typically include: string algorithms, data compression, pattern searching, external methods, dynamic programming, geometric algorithms, heuristic methods, and so forth. The aim is to equip students to address future novel problems, and prepare them for industry and/or research careers. A key objective is to give students a deeper understanding of the connection between computing theory and practice. This course should be considered essential for computer scientists and software engineers.

This internship enables the development of practical knowledge and hands-on experience through a supervised internship in the IT industry.

This internship enables the development of practical knowledge and hands-on experience through a supervised internship in the IT industry.

This course is for students interested in the art and science of computer programming. It is concerned with advanced data structures and their algorithms. It involves a study of classical and recently discovered methods for solving a diverse range of computational problems. Analysis of important performance characteristics (such as efficiency, scalability, applicability, adaptability, and design) will also be addressed. A survey of problem spaces and techniques for addressing specific examples using useful/interesting algorithms and data structures is offered. Examples typically include: string algorithms, data compression, pattern searching, external methods, dynamic programming, geometric algorithms, heuristic methods, and so forth. The aim is to equip students to address future novel problems, and prepare them for industry and/or research careers. A key objective is to give students a deeper understanding of the connection between computing theory and practice. This course should be considered essential for computer scientists and software engineers.

This internship enables the development of practical knowledge and hands-on experience through a supervised internship in the IT industry.

This course is for students interested in the art and science of computer programming. It is concerned with advanced data structures and their algorithms. It involves a study of classical and recently discovered methods for solving a diverse range of computational problems. Analysis of important performance characteristics (such as efficiency, scalability, applicability, adaptability, and design) will also be addressed. A survey of problem spaces and techniques for addressing specific examples using useful/interesting algorithms and data structures is offered. Examples typically include: string algorithms, data compression, pattern searching, external methods, dynamic programming, geometric algorithms, heuristic methods, and so forth. The aim is to equip students to address future novel problems, and prepare them for industry and/or research careers. A key objective is to give students a deeper understanding of the connection between computing theory and practice. This course should be considered essential for computer scientists and software engineers.

This internship enables the development of practical knowledge and hands-on experience through a supervised internship in the IT industry.

An introduction to bioinformatics, open to students majoring in computer science or biology. It includes an overview of molecular biology, genomics, script language programming, algorithms for biological data, an introduction to machine learning and data mining, and relevant statistical methods.

This paper covers object-oriented software development in Java focusing on abstract data types and dynamic data structures, while introducing design methodologies in software construction, software process, and software testing.

This course is for students interested in the art and science of computer programming. It is concerned with advanced data structures and their algorithms. It involves a study of classical and recently discovered methods for solving a diverse range of computational problems. Analysis of important performance characteristics (such as efficiency, scalability, applicability, adaptability, and design) will also be addressed. A survey of problem spaces and techniques for addressing specific examples using useful/interesting algorithms and data structures is offered. Examples typically include: string algorithms, data compression, pattern searching, external methods, dynamic programming, geometric algorithms, heuristic methods, and so forth. The aim is to equip students to address future novel problems, and prepare them for industry and/or research careers. A key objective is to give students a deeper understanding of the connection between computing theory and practice. This course should be considered essential for computer scientists and software engineers.

This paper provides the "capstone" project required to complete an accredited engineering degree. The paper builds on the knowledge and skills students have gained in the first three years of their professional engineering degree and reinforces the multidisciplinary aspect of engineering. Students will learn how to carry out a Research &Development project as an individual or as part of a team, and also gain an appreciation of the depth and breadth of knowledge and skills required for completing a project that addresses real-world problems.

An introduction to bioinformatics, open to students majoring in computer science or biology. It includes an overview of molecular biology, genomics, script language programming, algorithms for biological data, an introduction to machine learning and data mining, and relevant statistical methods.

This paper provides an overview of the operation of computer systems. The central theme is the way in which the hardware and software co-operate to allow the execution of programs written in a high-level language.

This paper provides an overview of the operation of computer systems. The central theme is the way in which the hardware and software co-operate to allow the execution of programs written in a high-level language.

This course is for students interested in the art and science of computer programming. It is concerned with advanced data structures and their algorithms. It involves a study of classical and recently discovered methods for solving a diverse range of computational problems. Analysis of important performance characteristics (such as efficiency, scalability, applicability, adaptability, and design) will also be addressed. A survey of problem spaces and techniques for addressing specific examples using useful/interesting algorithms and data structures is offered. Examples typically include: string algorithms, data compression, pattern searching, external methods, dynamic programming, geometric algorithms, heuristic methods, and so forth. The aim is to equip students to address future novel problems, and prepare them for industry and/or research careers. A key objective is to give students a deeper understanding of the connection between computing theory and practice. This course should be considered essential for computer scientists and software engineers.

An introduction to bioinformatics, open to students majoring in computer science or biology. It includes an overview of molecular biology, genomics, script language programming, algorithms for biological data, an introduction to machine learning and data mining, and relevant statistical methods.

This paper covers object-oriented software development in Java focusing on abstract data types and dynamic data structures, while introducing design methodologies in software construction, software process, and software testing.

This course gives a survey of advanced algorithms and analysis of their performance, along with heuristic methods that include basic Artificial Intelligence techniques.

This paper covers object-oriented software development in Java focusing on abstract data types and dynamic data structures, while introducing design methodologies in software construction, software process, and software testing.

This internship enables the development of practical knowledge and hands-on experience through a supervised internship in the IT industry.

This internship enables the development of practical knowledge and hands-on experience through a supervised internship in the IT industry.

This paper covers object-oriented software development in Java focusing on abstract data types and dynamic data structures, while introducing design methodologies in software construction, software process, and software testing. A group project reinforces broader software engineering practices.

This paper provides the capstone project required to complete an accredited engineering degree. The paper builds on the knowledge and skills students have gained in the first three years of their professional engineering degree and reinforces the multidisciplinary aspect of engineering. Students will learn how to carry out a Research & Development project as an individual or as part of a team, and also gain an appreciation of the depth and breadth of knowledge and skills required for completing a project that addresses real-world problems.

University of Waikato

University of Waikato