BSc (Hons) Computer Science Bachelor's degree at the Arts, London

Introduction to patterns in nature (fractals, physical phenomena, genetics, simple life forms, cells and living creatures) and their equivalents in computing (computational biology, L-Systems, digital art, simulation) as well as basic concepts of software architecture.

Hands-on, project-focused unit building on basic 2D programming experience and interaction design to explore advanced possibilities for people to work and live with computers. Design interactive human/computer experiences using generated graphics, images, and sound. Introduction to creative ideation, planning, and basic project management skills.

Assessment: Report reflecting on development process and conceptually framing ideas and inspirations

Introduction to the discipline of computer science and data science and their effects on the wider world. Literacy in computer programming languages such as JavaScript and Python and learning to apply basic mathematics for applications from basic data processing to real-time multimedia programming.

Introduction to the concept of human computer interaction (HCI) including key theories and approaches for understanding how we work with computers. Learning accessible and inclusive approaches to designing and prototyping interactive systems through HCI case studies, best practices, and small group project.

Using approaches borrowed from speculative design and design fiction to develop understanding of the basic architecture of the Internet and the web and how to develop websites. Group project to create speculative (fictional) websites, apply fundamental approaches to web application development, investigate what different types of people expect from websites, design interfaces and interactions in HTML/CSS/JavaScript.

Assessment: Presentation and critical thinking through in-class critique and participation

Expansion of knowledge, skills, and competencies in programming and computer architecture by looking at how the world is made computable by processes of digitisation and the application of digital logic. Learning how computing hardware uses binary representations and binary operations. Applying matrix mathematics to make sense of and manipulate images and other large data sets.

Introduction to essential concepts of data collection, networked systems, large-scale abstraction, and cybersecurity essentials such as risk and trust through the lens of ethical and legal requirements. Identification, analysis, and assessment of risks to individuals, marginalised groups, society, democratic governance, and the environment.

Building on knowledge and skills in web programming to explore how reality is digitised, abstracted, and automated using computational processes. Learning industry-standard 'full stack' approaches that utilise both SQL and NoSQL databases, application development frameworks like React, networks, and servers to collect and visualise data. Group work to create data-driven applications like social web forums and chat clients.

Introduction to a range of mathematical techniques and standard algorithms used in computing for topics such as searching, sorting, data structures, and analysis. Implementation and analysis of their efficiency, performance, and complexity using formal and informal types of notation. Critical thinking about how abstract, automated decision-making of algorithms might have unintended or negative effects on real-world data.

Development of understanding of what type of organisations exist that students may want to work for, with, or to start on their own. Exploration of a range of different organisations in different industries through case studies and guest lectures, including companies, start-ups, non-profits, government divisions, NGOs and small collectives.

Exploration of the basics of computer graphics and audio through the lens of human perception: what can we perceive, and how is it represented mathematically, and in computing hardware and software as light, sound, and other sensory forms. Efficient working with complex media like graphics and sound in a real-time environment using key multimedia libraries like WebGL and game engines.

Deepening understanding of the variety of forms that interfaces and interactions between people and technology may take. Exploration of the impact that interface and interaction design can have on people's lives and activities and learning practical and ethical methods for designing and evaluating technology interfaces and interactions.

Immersion in current topics of interest in computer science from across the world, challenging understanding of the discipline and serving as a source of inspiration for future endeavours, including final year degree project.

Group work to collaboratively design and develop a prototype software project feature, which may be a whole or part of an entire software application. Projects address specific problems and challenges across a range of use cases, scaffolded by and reinforcing learning from HCI, project management, and programming.

Introduction to interactive concepts in machine learning and AI. Examination of more complex intelligent systems design, including neural networks, reinforcement learning and other critical techniques, and application to different contexts such as audio and video generation and data analysis.

Building on understanding of networks and website architecture from Year 2. Series of hands-on exercises covering key conceptual topics in cybersecurity such as intrusion detection, cryptography, trust, and privacy legislation. Advancement of understanding of basic computing infrastructure and interaction with terminal consoles, client-server systems, and networks.

Further development of professional approaches to human-computer interface development, both physical and virtual.

Consideration and reflection on critical approaches to technology development, including legal, regulatory and research-led ethics. Application of these techniques to final year projects, exploring how knowledge of computing ethics has been applied.

Final project incorporating a range of methods and approaches drawn from skills acquired throughout the course including mathematical and algorithmic thinking, HCI methods, software engineering, signal processing, interaction, machine learning and AI, security and trust, and other essential topics in the discipline.