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Students will develop an understanding of ethical, professional and legal issues relating to Computer Science. Students will participate in critical reading, writing and develop their referencing techniques.
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This module provides the first exposure to programming, problem-solving and software designing. The constructs of functional programming and debugging are introduced for designing, developing and deploying correct, efficient, maintainable and scalable programmes.
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This module provides opportunity to be proficient with tools and techniques for creating content accessible via mobile, table or desktop devices reliant on web technologies such as HTML, CSS and scripting. The students also learn the structure of data within relational databases, data modelling and relational algebra. The practical experience is enriched by implementation using SQL within web applications.
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This module extends the programming proficiency by introducing object oriented programming and data structures for developing applications. The concepts of abstraction, encapsulation, inheritance, polymorphism, linear and non-linear data structures, algorithms and analyses of time and space complexities are discussed within the context of real-world problems and their solutions.
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This module covers the fundamental concepts of linear algebra, calculus, discrete mathematics, statistics and probability that are required by a Computer Science student. It lays the foundations for students to successfully complete the remainder of their studies as well as for a computing career.
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This module introduces students to fundamentals of computer architecture, operating systems and networking. The emphasis is on the hardware aspects of a system and how the hardware is used during execution o software. Networking fundamentals cover architecture, functions, addressing, media and operations.
Computer Science BSc (Hons)
Honours Degree, Undergraduate, September 2025
Key Details
- G400 Course Code
- 3 Years
- TBC Typical UCAS Tariff
Nurturing passionately curious minds to lead the future world of IT and make a significant contribution to problem solving practices is hallmark of the BSc (Hons) Computer Science course. Computer Science is undoubtedly the most popular program worldwide and impacts everything from scientific research, healthcare, education, banking, finance, transport, manufacturing, agriculture, automation and communication etc. to household objects like microwave ovens, fridges, or door locks. The unique blend of theoretical and practical underpinnings of programming, artificial intelligence, data science, deep learning, cyber security, desktop and mobile applications development, robotics and game development aim to provide students unfettered learning opportunities tailored to their particular strengths. With the support of creative technologies, state-of-the-art infrastructure and highly experienced academics staff, our vision is to cultivate ethos of curiosity, pragmatism, teamwork and versatility amongst graduates and to give them the distinct competitive edge with necessary skills to address technological challenges of 21st century.
- This course enables students to develop competence in key themes such as artificial intelligence, data science and cyber security, alongside wisdom in their application domains, sufficient for them to progress to postgraduate study or employability.
- A rigorous, coherent and engaging curriculum that draws on the teaching strengths and research expertise in the subject area, aims to provide students unfettered learning opportunities tailored to address emerging technologies and specialisms.
- Learning opportunities encourage and support the spirit of intellectual curiosity and enquiry, an ability to apply computational thinking to solve problems and the capacity for creative computing.
- Relevant professional bodies (e.g. British Computing Society) inform the learning experiences provided to acquire and develop the practical skills essential within Computer Science.
- Students develop an appreciation of legal, professional, economic, environmental, moral and ethical issues involved with Computer Science and their impact upon society.
The first year covers basics of Computer Science. More specifically, you will analyse small-scale problems and design their solutions by applying algorithmic and mathematical techniques. The programming, web applications development, data structures, computer architecture and networking fundamentals modules would develop necessary skills for computer scientists and also familiarise them to professional ethos and awareness of security implications.
In second year, the core modules ensure developing a deeper understanding of user interface design, robotics and cyber security and machine learning. Additionally, the specialist modules within artificial intelligence, data science or cyber security domains specialisms support tailoring study paths to individual strengths and ambitions. The optional modules like exploratory data analyses, visualization, knowledge representation and reasoning, pattern recognition and applied statistics, creative computing, robotics and computer vision will ensure acquiring pertinent technical skills, theoretical foundations and professional responsibility while developing medium-scale, real-world projects within the modules.
As you progress into the third year, higher level and core Computer Science modules, such as Internet of Things and Deep Learning, will underpin the specialist modules like natural language processing, data modelling, game design and development, cloud-based development, distributed databases and big data analytics. Each of these modules has an elegant blend of theory and practice and offers a stimulating and challenging learning experience that allows developing an informed and practical understanding. The ability to research, think and analyse critically, design robust software applications and also to reflect and develop both personally and professionally will be entailed in the final year project with the aim of considering the role and career which Computer Science graduates wish to undertake.
3 hours of contact time per 20 credit module, a total of 9 contact hours per week.
Modules are assessed through portfolios, video papers, digital artefacts, case studies and blogs alongside more traditional assessment types such as technical reports, academic essays, presentations, projects or online exams.
As a graduate who has developed a passion for Computer Science, you will be well prepared for post-graduate study, professional training and/or graduate employment in the commercial sector.
You may choose to pursue a career as a programmer, machine learning developer, data scientist, business analyst, network manager, cyber security manager, cloud and web application developer, database developer or games designer.
The course also provides progression to the PGCE Secondary Computing course at Newman as part of a seamless transition if you meet the Department of Education Initial Teacher Training entry requirements.
Birmingham Newman University is located in Britain’s second city – Birmingham. With one of the youngest city populations in Europe, it is a vibrant and dynamic place to study.
Studying at Newman University, you have the advantage of being near to the city, but living in, or commuting to peaceful and comfortable surroundings on campus.
Dining out
Birmingham has lots of wonderful places to dine out with a range of different cuisines. Places where you can dine out include; Brindley Place, Mailbox and Hagley Road (just 10 minutes’ from Newman).
Entertainment
Whether you like to go to; the theatre, gigs or clubs, or enjoy: sports, shopping visiting art galleries or exhibitions – Birmingham will not disappoint and you will be spoilt for choice!
Location
Getting around Birmingham is easy via train, bus or by car. Birmingham has excellent transport links to the rest of Britain, making it easy for those weekend getaways!
Why not explore the city for yourself by visiting one of our Open Days?
Want to find out more about Birmingham? Then take a look at some Birmingham City Secrets.
Course Fees
The full-time course fee for September 2025 is £9,250 per year.
The University will review tuition fees and increase fees in line with any inflationary uplift as determined by the UK Government, if permitted by law or government policy, in subsequent years of your course. It is anticipated that such increases would be linked to RPI (the Retail Price Index excluding mortgage interest payments).
Additional Costs
Find out more about the other additional costs associated with our undergraduate degrees.
Modules
Please be aware that, as with any course, there may be changes to the modules delivered, for information view our Changes to Programmes of Module Changes page.
Timetables: find out when information is available to students
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This module aims to teach students the concepts, skills and knowledge required to develop mobile applications. Students will appraise the tools, processes and techniques used to plan, design and deploy mobile applications. This module provides the students with the opportunity to evaluate the technical and management dimensions of mobile applications development.
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This module enables students to investigate the scope and challenges of Human Computer Interaction (HCI) and interaction design. They will develop an understanding of HCI concepts and apply HCI methodologies to augmented reality and tangible user interfaces. Students will investigate current user-centred design research and participate in the process of designing a high-fidelity prototype that meets user requirements.
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This module covers the fundamental concepts required to understand and to work with security. These security concepts include: historical background, security and security threats, practical measures (such as identification, authentication, audit trails), security models, cryptography, network security). The practical part of the module provides students with the opportunity to explore computer system security via hands-on activities. Current issues relating to cyber security are discussed leading to investigation of possible solutions.
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Machine Learning, is a subset of Artificial Intelligence, is concerned with creating learning models that allow a computer to exhibit behaviour that would normally require a human to do. Typical applications include: computer vision, speech recognition, and intelligent robots. The learning models come in various forms, such as parametric and non-parametric and probability distributions. In this module, students will learn about the most effective machine learning techniques and gain practice in implementing them successfully. Additionally, students will learn about the theoretical underpinnings of machine learning.
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This module teaches students the concepts and processes of obtaining detailed insights hidden in data. As an integral component of Data Science, this module entails exploration and visualization of graphs, plots, distributions, probability densities, correlations, clustering and time series data. Students will learn how to inspect data from different perspectives, discover relationships and trends, infer patterns, locate outliers and summarize and describe findings for undertaking further analyses and modelling.
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In this module students will learn one of the fundamental areas of artificial intelligence – representing knowledge about the world. The module will introduce existing frameworks, representation using first-order logic, propositional calculus, ontologies, planning and reasoning for decision making applications within artificial intelligence.
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The module presents the student with the opportunity to articulate creative ideas through computing. The module provides the foundational aspects of programming for creativity, principles of form, structure, transformation and generative processes for image, sound and video. Students will explore the methods and conceptual tools used in the creative industries. They will also implement creative concepts that are not easily realised with commercial software packages.
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This module aims to provide students the necessary theoretical and practical skills to understand, design and develop statistical machine learning models for pattern recognition problems such as object detection, recognition, segmentation and texture analysis. Students will be able to apply various techniques for real-world applications such as person identification, audio processing, speech recognition, image analyses and motion estimation.
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In this module, students will address the general problem of sensor-based mobile robot navigation and explore the implementation of intelligent image processing and machine learning in mobile robots. Throughout the module, students will be introduced to various 2-D and 3-D vision problems, characteristic problems in robotics, derive mathematical models for those problems and develop algorithms that apply these models to solve robotic problems.
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The final project and critical evaluation will be structured to assess the knowledge and understanding by means appropriate to individual students, though all approaches will lead to the production of a significant piece of work that involves the demonstration of advanced practice in computer science. All approaches will be accompanied by a critical self- evaluation of the outcomes achieved. Students would integrate concepts and skills learned throughout the degree course to substantial open-ended problems. The module will increase students understanding of applied, investigational or theoretical approaches to real word problems.
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This module will cover the context and the history of the IoT, the hardware, communications protocols and security systems it relies on, and the cloud-side analytics that makes sense of the data produced. It will provide practical hands-on experience of common IoT devices (sensors, actuators, microcontrollers), and examine a range of commercial platforms. Students will be provided with a Wi-Fi microcomputer and will program live IoT applications using that device with the opportunity to produce their own IoT device with a range of functions and capabilities.
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Deep learning is a group of exciting new technologies for neural networks. Deep learning allows a neural network to learn hierarchies of information in a way that is like the function of the human brain. This module will introduce the student to classic neural network structures, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Neural Networks (GRU), General Adversarial Networks (GAN), and reinforcement learning. Application of these architectures to computer vision, time series, security, natural language processing (NLP), and data generation will be covered.
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This module will provide students opportunity to understand and apply computational techniques to analyse and synthesize natural language and speech. An interdisciplinary bridging of information retrieval and machine learning will provide necessary skills to develop applications capable of comprehending, manipulating and generating natural languages similar to Large Language Models.
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This module aims to teach students the concepts, skills and knowledge required to develop, design and prototype games. This module provides an introduction to games design and the games industry and outlines the key elements of game development. The module will provide contextual knowledge of the games industry (past and present; the UK and international), different genres, technology and tools, and roles, good practice, and current challenges of games design and development. The wider influence of games within contemporary culture and education will also be considered, specifically the application of ludic design principles in other creative sectors (e.g. ‘gamification’).
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This module entails the confluence of data gathering and wrangling with machine learning techniques for improving quality and usability of predictive analytics. Students learn methods for creating conceptual representations of data objects, longitudinal and cross-sectional data gathering, preprocessing, feature engineering, dimensionality reduction, principal components analysis, discriminant analysis, associative models, auto-regression and moving averages, clustering and reinforcement learning.
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This module aims to introduce students to the paradigm of cloud computing, where technology-related functions are provided as a service to users in order to perform resource-intensive tasks such as data analysis and machine learning. They will learn formal methods and techniques for designing and implementing advanced cloud-based applications. Students will have an appreciation for Artificial Intelligence and Semantic Web research related to cloud computing. They will investigate big data computing using cloud-based technologies and apply the skills and knowledge gained to design, develop and deploy an interactive data-driven cloud-based application to solve programming problems.
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The aim of this module is to enhance the knowledge of database systems for handling huge volumes of data on distributed systems which address deficiencies of centralised systems. Additionally, storage, processing and retrieval of semi-structured or unstructured data within schemaless databases, like MongoDB, are presented along with intrinsic challenges of validation, integrity constraints and inconsistencies. An introduction of NoSQL with practical applications enables students to explore application domains such as social media, e-commerce and real-time analytics.
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This module aims to make students understand and apply concepts of Big Data, distributed computing, MapReduce framework and resource management in computing clusters. An appreciation of programming paradigm, tools, techniques and algorithms supporting Big Data will provide necessary practical experience required in this emerging field.
Additional Information
Free Windows Surface Pro for All BSc Computer Science First Year Students
To support with the cost of living, all BSc Computer Science students will receive a free Windows Surface Pro upon enrolment at the start of your first year, which you can keep. This device will come pre-installed with all the necessary software and apps to support your studies, ensuring you have the tools needed for success.
General Academic Regulations: Terms and Conditions for students attending our courses