Computer Science and Artificial Intelligence BSc (Hons)

30.00 credits

In this module, you will develop a strong foundation of how computers work in terms of hardware and software, and the formal logic behind it. You will have the opportunity to meet several different experts in the topics that form the basis of modern-day computer science.

To equip you to excel in your course, the subject experts will guide you in an exploration of digital logic, data processing, representation and storage, essentials of computer software and hardware including architectural concepts and relevant data structures and algorithms.

You will develop this knowledge further through the introduction of databases, web development, and the underlying technologies of modern-day communication, including Ethernet, Wi-Fi and the Internet.

30 credits

Without proper design, evaluation or control, Artificial Intelligence (AI) would dominate the world, hence this module introduces some of the fundamental mathematical concepts that underpin the design and analysis of AI software. You will be introduced to the key mathematical functions and concepts that are the foundation of computer science, of which AI is one of the many strands. You will become familiar with basic concepts and notation, learn topics including logic, set theory, number systems and special functions, as well as linear algebra and introductory probability, on which most AI systems are based.

The module is core to the BSc in Computer Science and Artificial Intelligence. It will provide the mathematical skills, techniques and understanding of the principles needed to support further learning on the programme. It will use AI applications to introduce core mathematical and statistical concepts that are essential attributes for computer scientists and machine learning analysts in the modern, data-driven world.

30 credits

The goal of the Professional Environments module is to prepare students for professional practice. It will firstly ensure they acquire suitable employability assets and secondly equip them with an understanding of the role of a professional in society and the role of professional bodies.

While the bulk of the taught programme focuses primarily on domain knowledge, the Professional Environments module focuses on developing key skills, personal qualities (e.g. commercial awareness, reliability and punctuality, understanding the centrality of customers and clients), and professional knowledge including the need to engage with continuing professional development. With such assets, students will generate a CV, an employment portfolio, and a professional online presence.

Being a professional also means understanding the key legal, ethical and societal issues pertinent to the domain, and understanding the need for continuing professional development (CPD) especially when technology develops at such a rapid pace. The module is designed to support different domain areas and to integrate experience from other professions. The subject areas being studied demand a global perspective which encourages the inclusion of our diverse of communities and national practices.

Reflecting the fact that team working is ubiquitous in the modern workplace, a significant proportion of the assessment work on the course is based around group work. There is considerable evidence that group work promotes a much deeper engagement with taught content and the Future Skills report shows how it is embedded in working practices. It also encourages the development of diverse learning communities with computer science, cybersecurity and digital media students working in close proximity. This module will therefore introduce students to best practice in group working covering how to approach group work, how to understand yourself, how to deal with different types of people, and methods of selecting and managing groups.

30 credits

We designed this module to establish a foundation for key Programming Concepts. We do not assume prior experience of programming, as we know you will all have widely different levels of existing knowledge. The module is designed to be accessible to a beginner while still being exciting for an experienced coder.

We are excited to be able to deliver this module using Kingston's own home-grown learning environment for programming, NoobLab. NoobLab gamifies your learning, making programming enjoyable and accessible for all existing ability levels – no other university offers this platform or unique approach to learning:

You will learn a variety of programming languages. In the first few weeks, we will use visual blocks that will allow you to construct programs and focus on thinking like a programmer rather than getting bogged down in grammar and syntax. Then, with these skills established, you will learn Python, Javascript and optionally Java, solving Code Kata style programming challenges on a weekly basis. This will equip you to build a graphical card game as your capstone project for the module.

30 credits

This module is a Level 5 core module for the BSc in Computer Science and Artificial Intelligence. It builds upon the skills students will have acquired in the Level 4 modules, primarily in mathematics, statistics and programming, and will provide them with a solid foundation in A.I. in preparation both for their Individual Project and other modules at Level 6, or for an appropriate Industrial Placement (if taken).

This module will introduce students to the principal paradigms of Artificial Intelligence, and their relation to other disciplines, such as Cognitive Science, and their applications to practical problems. These will include both traditional (logic and search based) and more modern (Machine Learning) approaches (including neural networks), and will also cover some real-world practical case studies.

It will cover the 'core' mathematical, statistical and machine learning concepts that are essential attributes for employable data scientists and machine learning engineers in the modern, data-driven world and include an introduction to the importance of ethical debate in both the development and application of AI, with contemporary case studies and issues relating to data privacy and data protection.

30 credits

This module is designed to encourage you to look outwards to industry and employability, and make you more confident when facing the job market upon graduation. You will develop excellent group working skills, broaden your understanding of industry and its requirements, and enhance your project management skills.

It is always exciting to watch the groups collaborating as they produce their entrepreneurial projects for Kingston University's 'Bright Ideas' scheme; students involved in this have won awards, producing fascinating artefacts for their remaining term and exploring new and different areas within their course field.

The module is an opportunity to work with many different students, working in subject areas that are innovative and unusual. Very often, a student may discover something they did not know that they could achieve. This triggers new learning and an added confidence that was not previously there. Those are the times that the learning is strongest, and our pride in the student, the greatest.

30 credits

This module seeks to establish the skills required to effectively use databases for storage and retrieval of information. You will learn how to design, build and query databases according using logical data models and structured query language (SQL).

30.00 credits

This module takes you on a journey from the underlying computer architecture through to modern computing approaches and methodologies. We developed this module to enhance your understanding of how modern computer systems are designed and used to meet the needs of today's computing environments.

We will cover topics such as operating system functionality, the principles and applications of parallel processing and the analysis of algorithm complexity. Furthermore, the module delves into containerisation and networking concepts, including physical network structures and associated addressing schemes. Finally,  you will evaluate the capabilities and limitations of Artificial Intelligence, exploring Neural Networks and Large Language Models (LLMs).

30 credits

This module takes what you did in Programming 1, where you started to think like a programmer, and focuses on one programming language to develop software applications that people can interact with.

You will continue to use Kingston's bespoke NoobLab in the first term – no other university offers this platform or unique approach to learning – to go into more depth in creating models of 'real world' objects, as well as data structures like arrays, lists and maps, and reading/writing files. In the second term you will build simple applications (graphical user interfaces).

You will use Java Swing as the basis for a graphic user interface, drawing on the Java Collections Framework as needed to build data structures for your applications. We will introduce industry-standard development environments such as NetBeans and Visual Studio Code, alongside GitLab for source and version control of your code.

30 credits

The goal of the module is to further develop skills in organisation, timekeeping, research literature, developing and critically analysing results as well as reporting work verbally and in a written format. The end result will be an artefact or artefacts which demonstrate creativity and technical competence as well as a technical report.

On successful completion of the module, students will be able to:

• Carry out a literature search to summarise and evaluate background work relevant to the chosen course, undertake an investigation of the planned topic and critically evaluate the outcomes.
• Plan tasks within time and other commitment constraints.
• Produce a well-structured written report demonstrating a sound understanding of the theory of the chosen project area including relevant references and use of language, diagrams, tables and graphs where necessary.
• Present or answer questions clearly and concisely in a structured interview about their work.
• Create an artefact relating to the chosen course.
• Identify and take account of relevant legal, social and ethical issues.

30 credits

This module will equip students with knowledge and experience in the concepts and methods in machine learning and artificial intelligence needed to evaluate their applicability to real-world problems. Students will apply machine learning and artificial intelligence algorithms and techniques in appropriately-scaled real-world applications. They will also gain a thorough awareness and understanding of the importance of ethical issues in A.I. and its applications, and can carry out an assessment of the ethical implications of particular developments and applications of A.I.

On successful completion of the module, students will be able to:

• Demonstrate understanding of and skills in applying advanced A.I. methodologies
• Discuss the issues in problem domains such as Computer Vision, Natural Language Processing and Anomaly Detection which make them unsuitable for solution using traditional methods alone, and how A.I. can address these.
• Identify, apply and implement appropriate A.I. approaches for solving problems from those domains studied
• Critically evaluate and discuss to what extent use of such approaches have been successful, including their legal, ethical, societal implications, and suggest alternative solutions when appropriate

30 credits

This module will consolidate and build on previously acquired knowledge of databases by analysing and evaluating important issues in the database area. In addition, advanced aspects of data warehousing and data mining will be studied, encompassing the principles and commercial application of the technologies.

15 credits

This module gives you a dedicated opportunity to develop your Future Skills Graduate Attributes. 

At the start of the module, you will be supported to self-assess your current skills profile. You will determine which attributes and skills you need to develop to support your career ambitions. In this process, you will be supported by a dedicated career coach, helping you explore a range of options that includes self-employment/freelancing, starting your own business, higher level study, and other professional graduate-level opportunities. Throughout the module, you will be given opportunities to engage with external mentors, to support reflection and to develop a professional network.

You will undertake a tailored series of activities and projects, aligned to your goals, from a menu of development options. This could include short courses, enrichment activities and experiential learning options such as micro-placements. You will also be able to reflect on activities outside the University that develop your graduate attributes, such as work or volunteering.

30 credits

This module will expand your skill set and your awareness as software industry professional, using industry-relevant tools, know-how, as well as theoretical areas. Our focus is on real-world experience, and preparing you to become a skilled graduate, regardless of the job roles you are considering or the skills you want to expand on within the computing domain.

This will empower you to become better at whichever role you are aiming at; developer, analyst, designer, project manager and so on. This is not a code-centric module; the skills in this module are more concerned with efficiently working within a software development team and managing the code produced rather than necessarily writing code yourself.

You will explore the latest practices for making more dependable, reusable and scalable software systems, and how to configure, maintain and support such systems. We will also discuss topics on software architecture, and how to select the right architecture based on the system requirements. We will also cover popular industry practices like refactoring, software measurements, DevOps, Microservices, and software testing approaches, and even a bit of Quantum computing.

The workshop activities promote collaborative learning. Within the first teaching block you will explore a specific topic or tool every two weeks. In the second teaching block, you will work as a team, taking up a role as a manager, developer, analyst, designer, security expert or tester and work on a software development case study.

Most of the topics and tools you come across in the module are linked to skills advertised as essential or desirable by software industry employers. They are also closely linked to interview questions or assessment centre activities. Overall, the main focus of this module is to equip you to become a skilled and knowledgeable IT professional capable of facing challenges, while maintaining a holistic, practical perspective on the issues at hand.

30 credits

This is an optional module intended for undergraduate students who are studying Computing-related subjects. Although it forms part of the User Experience guided pathway it can be taken as a standalone module and previous experience of UX is not assumed. This module will focus upon the skills, methods and tools required in careers such as UX Architect, UX Designer, Service Designer, Information Architect or Digital Product Designer. The curriculum is finely balanced between theory and practice. Students are directly immersed in organisational practices and skills used in industry and will make use of academic theory in this practical context.

Students will learn to develop investigative, analytical, technical, communication and advocacy skills to help them shape interactive technologies that augment people's abilities, enhance their creativity, connect them to others and protect their interests. They will also become aware of the impact of levels of digital literacy, availability of and access to technology, economic and business drivers, regulations, and regional/cultural norms. The module will also develop methods and skills required to understand current users, to investigate non-use, and to imagine future users.

30 credits

While this module provides a foundation for careers in mobile application development, mobile is becoming increasingly ubiquitous and the skills taught also have applications in UX, web development and software engineering in general. Although there are no prerequisites, it is assumed that students have acquired a general familiarity with programming and software development principles through their previous study.

The module is divided into two phases. In the first phase, students will be introduced to software development for the two major mobile platforms. This will cover development environments for these platforms, UI conventions, building and deploying simple applications. Students will then be introduced to cross platform development environments for mobile development.

In the second phase, standard frameworks for mobile web development will be introduced. The phase is organised around a practical project. Students will choose one of the platforms on which to build a mobile application of their choice. This project gives students the opportunity to specialise and explore their chosen platform in greater depth, acquiring the knowledge and proficiency to be able to design and build complex mobile apps. Students will be encouraged to publish their apps in one or both (in the case of a cross-platform app) of the two major app stores, thus providing an introduction to mobile application delivery and distribution.

30 credits

Programming is a central activity of software development, which encompasses a wide range of languages, environments and specialisms.

This module will offer students the opportunity to acquire a useful competence across this range. The first teaching block will cover aspects of language, algorithms, tools, test-driven methodologies, and a range of user interface technologies.

The second teaching block will apply these themes across a range of technologies and application environments, focusing on web and mobile in particular. Assessment will include computer-based in-class tests and e-portfolios of student achievement that allow them to curate and share their passion for programming.

30 credits

Data science analytics are widely applied in areas including medical, environmental and business analytics. This module builds on topics covered in earlier parts of the programme, including mathematical and statistical modelling, probability estimation and visualisation. Students will be introduced to the key statistical tests for frequentist data science, where specific theories are explored and tested via descriptive and inferential statistics.

The module also introduces further practical data analytical techniques, including time series and forecasting techniques, as well as Bayesian methodology and its applications to estimation and decision-making problems, including loss and risk functions. Students will apply their existing programming knowledge to acquire proficiency in using these techniques, develop and obtain real-world solutions from data.  Emphasis is placed on the practicability of methods and the illustration of their real-world applications.

This module will provide students with a data science skillset to include critical thinking, communication, teamwork and leadership skills that feed into data-driven decision-making. Delivery and Learning focuses on practical applications, allowing students to develop and consolidate modelling software skills and hone commercially and contextually relevant knowledge and competences.

30 credits

This module supports the creation of digital enterprises through the lifecycle of innovation and entrepreneurship, financing and development, business planning, customer development, marketing and retention.

There are three key parts:

1. Starting up: innovation and entrepreneurship, funding and funders, customers and prototyping
2. Digital strategy, management, finance and planning
3. Digital marketing, customer service and retention

Digital innovation is a major driving force in creating economic growth. This module illustrates how to work in an entrepreneurial fashion. At the heart of entrepreneurship is innovation, which can come in many forms. Sometimes this can be an incremental but generally gives significant improvement to the customer or alternatively as a new breakthrough or transformational innovation. Ideas are then considered from potential customers’ and funders’ perspectives to enable realistic aspirations to be made.

From this foundation, the module explains how to develop a digital business strategy, not only to satisfy the critical needs that organisations have, but also to explore the application and use of improved value chains using the concepts of corporate venturing (spin-out/intrapreneurship) and entrepreneurship (new venture creation).