School of Computer Science BCS accreditation 2021 - 2026

Artificial Intelligence MEng (Hons) - COMP26120 Algorithms and Data Structures

2.1.1 Knowledge and understanding of facts, concepts, principles & theories

This course considers essential facts, concepts, principles and theories related to Algorithms and Data Structures, topics which are at the core of Computer Science. This includes theoretical tools include algorithmic complexity analysis and fundamental algorithmic design principles.

Assesement : Examination, Individual coursework, Lab work

2.1.2 Use of such knowledge in modelling and design

There is a focus on the trade-offs associated with the performance of various data structures and algorithmic paradigms. This is explored using theoretically using computational complexity and practically via experimentation.

Assesement : Individual coursework, Lab work

2.1.3 Problem solving strategies

Material is placed within the context of real-world scenarios to demonstrate application to real-word problems. The course involves lab work that involves analysing a problem to develop an appropriate solution. Exam questions often involve an element of analysing a scenario to identify the most appropriate algorithmic solution.

Assesement : Examination, Lab work

2.1.4 Analyse if/how a system meets current and future requirements

Emphasis is placed on being able to argue and/or demonstrate the correctness and complexity of an algorithmic solution.

Assesement : Examination, Lab work

2.1.5 Deploy theory in design, implementation and evaluation of systems

Theoretical properties related to algorithms and data structures are explored through the implementation and evaluation of algorithmic solutions to computational problems during lab exercises.

Assesement : Lab work

2.1.9 Knowledge of information security issues

Examples from computer security are often used as examples to demonstrate key concepts. One topic involves the basic theory required to understand asymmetric key encryption, accompanied by a lab to explore the process in practice.

Assesement : Lab work

2.2.1 Specify, design or construct computer-based systems

The course is a practical course in which students build a variety of systems, from specification, through design to implementation.

Assesement : Lab work

2.2.2 Evaluate systems in terms of quality and trade-offs

Analysing and understanding performance trade-offs is a core component of lab work.

Assesement : Lab work

2.2.4 Deploy tools effectively

Throughout the course, students are using tools to build systems which are of practical use.

Assesement : Lab work

2.3.2 Development of general transferable skills

Students need to be able to communicate and engage with staff about systems they have built. Marking in laboratory session is via dialogue with students and students need to be able to explain their design, implementation and the correctness and performance of the systems.

Assesement : Lab work

3.1.3 Knowledge of systems architecture

The performance of algorithms and data structures is placed within the broader context of systems architecture e.g. caching effects.

Assesement : Not Assessed

3.1.4 Knowledge and understanding of mathematical and/or statistical principles

The course relies on considerable mathematical foundations, for performance analysis and correctness arguments.

Assesement : Examination, Individual coursework

3.2.2 Defining problems, managing design process and evaluating outcomes

The course provides mechanisms to evaluate fitness for purpose through theoretical and practical tools for performance analysis.

Assesement : Lab work

4.1.1 Knowledge and understanding of scientific and engineering principles

Scientific and engineering principles are deployed throughout the course unit.

Assesement : Lab work

4.1.2 Knowledge and understanding of mathematical principles

Mathematical principles are core to the course and are applied directly to the design of solutions.

Assesement : Examination, Individual coursework, Lab work

4.1.3 Knowledge and understanding of computational modelling

Modelling via data structures and algorithms is the central concern of the course.

Assesement : Examination, Individual coursework, Lab work

4.2.1 Specify, deploy, verify and maintain computer-based systems

The course is based on the use of theoretical and practical processes for the design and implementation of computer-based systems.

Assesement : Lab work

4.2.2 Defining problems, managing design process and evaluating outcomes

The course provides mechanisms to evaluate fitness for purpose through theoretical and practical tools for performance analysis.

Assesement : Lab work