MSc
Applied Computer Science (Conversion)
Degree Programme

PREPARATORY SEMESTER

• LANG 7100 Advanced English for Postgraduate studies

  This course is designed to enhance students’ academic language proficiency and communication skills. It prepares postgraduate students to engage confidently with academic texts and lectures with a technology and business focus while introducing them to key research practices and content relevant to their field of study. Students will develop a strong grasp of research methodologies, evidence-based writing, and critical analysis which are essential skills for success at the postgraduate study level. Through structured writing and speaking tasks aligned with higher education standards, and drawing on principles from established English for Specific Purposes (ESP) programs, the course uses discipline-specific materials to ensure practical, relevant, and meaningful learning.

• LIBA 7100 Academic Skills for Postgraduate Studies

  In this course, students will be introduced to a range of postgraduate study skills to facilitate successful completion of their postgraduate programme and allow them to begin the process of becoming collaborative and independent learners. The course focuses on developing critical thinking, AI literacy, research and communication. These skills will be introduced through investigations business and technology relating to the integration of AI. Beyond this, the course will create awareness of AI ethics and sustainability, using group work and report writing. Students will be introduced to, and use, a range of digital platforms as aids to effective communication through professional academic oral presentations and written reports using secondary sources. In that, the course allows students to adjust to expectations and conventions of postgraduate education in an English-speaking academic environment. In addition, students will be presented with reflective writing tools through a personal development portfolio that can aid in self-improvement, particularly in an academic setting

FALL SEMESTER

• COMP 7111 Programming Principles and Concepts

  The course introduces students from non-computing backgrounds to the fundamental principles of programming and computational thinking. It develops practical skills in writing, testing and debugging code, alongside problem-solving abilities. Also, fundamental data structures and basic algorithmic reasoning are also covered thus enabling students to consider efficiency and structural design in software development.

• COMP 7103 AI Ethics and Governance

  This course provides a critical and interdisciplinary introduction to AI ethics and governance. Students critically analyse AI systems, outputs, and impacts using interdisciplinary methods from ethics, law, sociology, critical theory, and will explore industry standards such as ACM or IEEE ethical frameworks. They will examine developing legislation including the EU AI Act, UK regulatory approaches, GDPR, and major international governance standards. The course develops students' ability to assess risks, analyse AI outputs for accuracy and bias, and consider the broader societal and cultural impacts of AI systems.

• COMP 7110 Computer Architecture and Networks

  This module develops an integrated understanding of computer systems architecture and networked infrastructure as foundational components of modern information systems. It introduces core architectural principles, operating system concepts and networking models, and examines how these layers interact to support secure, scalable and efficient computing environments

SPRING SEMESTER

• COMP 7107 Software Engineering

  This module develops an integrated understanding of software engineering principles and structured development practices appropriate to postgraduate conversion study. It introduces core concepts in software lifecycle management, requirements analysis, system design and quality assurance, alongside the use and selection of fundamental data structures to support robust software design. The module emphasises the disciplined application of engineering practices in the specification, development and evaluation of computer-based systems, including consideration of trade-offs relating to performance, maintainability, security and scalability.

• COMP 7109 Web Technologies with AI

  This course introduces students to the principles and practices of modern web technologies, with a particular focus on integrating artificial intelligence techniques into interactive web applications. Students explore front-end and back-end development concepts, server–client communication, data handling and the use of contemporary frameworks that support intelligent features. It also develops both conceptual understanding and hands-on skills, enabling students to design and implement dynamic web-based systems that incorporate AI components such as recommendation logic, classification models or natural language interfaces. Students also examine accessibility, usability, performance considerations of embedding AI within web experiences.

• COMP 7100 Research Methods for Computing

  This course introduces students to the principles, methodologies and analytical techniques used in computing research. It provides an understanding of how knowledge is generated, evaluated and communicated within the discipline, with emphasis on research design, data collection, data analysis and academic writing. Students learn to critically interpret research literature, formulate research questions, select appropriate methodological approaches, and reflect on ethical and professional considerations relevant to computing research. The course prepares students for projectbased work and professional inquiry by developing core skills required to conduct and evaluate research in academic and applied contexts.

Plus one elective from the following:

• BUSM 7103 Business Analytics: Data and Decisions

  This course provides a critical and interdisciplinary introduction to AI ethics and governance. Students critically analyse AI systems, outputs, and impacts using interdisciplinary methods from ethics, law, sociology, critical theory, and will explore industry standards such as ACM or IEEE ethical frameworks. They will examine developing legislation including the EU AI Act, UK regulatory approaches, GDPR, and major international governance standards. The course develops students' ability to assess risks, analyse AI outputs for accuracy and bias, and consider the broader societal and cultural impacts of AI systems.

• COMP 7108 AI for the Creative Sector

  This course explores the theoretical, practical and ethical dimensions of using artificial intelligence to enhance creative processes. Students examine how AI systems support creative work in art, design, media and film production, advertising, public relations, content generation and digital storytelling. With a non‑programming focus, the course introduces accessible tools including no‑code and low‑code AI systems, prompting strategies, multimodal models, and creative workflows. Emphasis is placed on practical application, critical evaluation, and responsible use of AI in creative industries.

FALL/SPRING/SUMMER SEMESTER

Either both of the following:

• COMP 7500 Professional Research Project

  This course provides students with the opportunity to undertake a substantial practical or research‑based project that demonstrates advanced application of various computing domains. Students may choose either a practical project, focused on the design and implementation of a system or solution, or a research project, focused on empirical, experimental or theoretical investigation. Working independently under supervision, students define a problem or research question, review relevant literature, select appropriate methods, and deliver a significant piece of work that evidences Level 7 technical, analytical and professional competence.

• COMP 7901 Internship Placement

  This course provides students with the opportunity to undertake a supervised internship within a computing, software, or technology-focused organisation. Students apply applied computing knowledge, software engineering skills and professional competencies to real‑world industry problems and workflows.

Or:

• COMP 7501 Extended Professional Research Project

  This course provides students with an extended supervised project in a computing, software engineering or technology-focused field. The extended professional research project enables students to participate in longer-term projects, systems development, operational processes, or research requiring advanced applied computing skills.