BSc (Hons) Computer Science

Year 2 Core Modules

You must study and pass all five core modules​

Brief description

Build on your knowledge of programming taught in earlier modules (e.g. arrays, structures, simple collections). Gain an introduction to the standard data structures and algorithms that form the core of algorithmic thought in computer science and to the idea of reasoning about the behaviour and performance of a computer program.

Indicative content

• Reasoning about performance: The idea of an algorithm, time and space complexity, abstract data types.
• Basic data structures: Linked lists, stacks, queues, hash tables.
• Sorting and searching: Exhaustive and binary search, common sorting algorithms.
• Trees: Simple trees, tree search algorithms, tree representations (XML, JSON).
• Graphs: Simple and directed graphs, graph algorithms.

Brief description

The design and implementation of object-oriented software and relational databases. In both contexts,  review existing designs, develop your own to meet stated requirements, critically evaluate them and use them to create example implementations.

Indicative content

• Entity relationship (ER) modelling: Identifying entities; 1-1, 1-many and many-many relationships; design notation; ER in OO software and database design.
• Relational database design: Using primary and foreign keys to realise 1-1 and 1-many relationships; link tables for many-many relationships; designing to meet application data requirements; normalisation.
• SQL: SQL as a programming language; basic relational algebra; expressing unions and joins; selecting, extracting, editing and inserting data; writing SQL to meet functional requirements.
• OO software and SQL: Including SQL into OO software; integrating OO software and database designs; realising designs in code.
• Development methodologies: The role of a methodology; review different methodologies such as waterfall, RAD, agile, TDD; appraise the role of design within different methodologies.

Brief description

This module builds on Data Structures and Algorithms 1 by introducing students to parallel programming on shared memory and GPU architectures and the design techniques underpinning parallel applications, using a range of case studies drawn from typical real-world applications.

Indicative content

• Parallel programming: Why to parallelise, parallelism and concurrency, Amdahl's law, high-level approaches to parallelisation, parallel design.
• Low-level programming with threads: Starting and joining threads, sharing data safely, mutual exclusion, synchronisation objects, lock-free.
• High-level parallel programming: Task-based parallelism, message-passing parallelism, data-parallel problems, exploiting locality programming.
• Instruction-level parallelism: SIMD instructions, automatic vectorisation.
• GPGPU: GPU architectures, appropriate algorithms for GPUs, GPU profiling.
• Parallel Patterns: Design patterns for parallel and concurrent programming. Awareness of common sorting, numerical, image processing and searching and optimization algorithms and how they can benefit from parallelisation.

Brief description

Generic concepts for the optimisation of interactions between a user and computing systems and service, and how these interactions can be evaluated. Learn about research methods, quantitative and qualitative data analysis, and ethics in the data gathering process, as well as interface design. Explore aspects of usability and accessibility.

Indicative content

• Designing Experiments: Creating and building small experiments that relate to aspects of computing.
• Usability and Accessibility: Developing interfaces that are usable and accessible under consideration of platform.
• Professional and Ethical Issues: Consideration of issues that affect professionalism and ethical procedures in computing industries.
• Data Analysis and Evaluation: Quantitative and qualitative data analysis methods.

Brief description

Dynamic web applications, through client-side and server side internet development on a full-stack platform.

Indicative content

• Web standards: Application of HTML5 and CSS to develop responsive designs.
• Client-side technologies: Implementation of JavaScript, libraries, and frameworks to create effective user interfaces within an appropriate development practice and methodology.
• Design techniques: Appropriate techniques for dynamic web applications.
• Data persistence: The use of relevant data persistence and consideration of appropriate use.
• Server-side scripting technologies: Using server-side technologies to provide functionality. Consideration of the processes involved, and the benefits/drawbacks of processing on the server.
• Security and legal issues: Consider legal and security issues including privacy, transparency, data protection, GDPR, authorisation and validation.
• Practical aspects of security: Appropriate use of network protocols, secure programming, and testing strategies.

Year 2 Microcredentials - Term 2

If you are a Direct Entrant (new student) to this year of study and have not previously taken module ABE101, then you MUST take ABE201 as part of your Microcredential selection. If you have previously taken ABE101 then you are NOT permitted to take ABE201.

Instructions: Please choose a total of TWENTY credits of microcredential (ABE) modules.

Brief description

Throughout the microcredential you will become familiar with university systems (including the virtual learning environment), consider what attributes make a successful student and develop key successful student habits.

Indicative content

• Navigating Abertay Systems: Be introduced to and understand how to engage with Abertay systems and tools such as MyLearningSpace, MS Teams, OASIS, MyAbertay etc.
• Expectations of University and You: Explore your own and the universities expectations of you and of the university; Consider the code of conduct; independent learning; blended learning; how university is structured; health and safety; and the Abertay attributes.
• Understanding and Searching Information: How scholarly information is generated and disseminated, key characteristics of different information types. Planning, using, and refining appropriate search strategies; online search tools; using a range of web and database search functionality. 
• Successful Student Behaviours: Develop strategies to key successful student behaviours including Defeating Procrastination, Time Management, Notetaking and preparing for classes, Growth Mindset, Accessing student support and opportunities.
• Referencing: Understand what is meant by academic integrity, plagiarism, and the need for appropriate referencing; creating reference lists and in-text citations; use of referencing tools to manage information.
• Sounding Academic: Explore what lecturers mean by “academic style” and “the right language”; Understand what is meant by and how to learn the rules of academic writing characteristics. Consider how this differs between college and university; Learn how to paraphrase. Explore how assessments, marking and feedback works at university.
• Evaluating Information: Using appropriate quality criteria to critically evaluate information from any source to determine authority and bias.

Brief description

This microcredential provides you with the space and time to develop your skills in designing, planning, delivering, and showcasing an artefact responding to the societal issue. The microcredential is flexible and you will have a choice of what and how you create your response.

Indicative content

• The Big Issue: You will be introduced to the big society issue that will be the focus of your artefact response. Learning materials available will help you consider your response to the challenge.
• Developing Ideas: You will think creatively as to how you will respond to the big issue. You will consider your intended artefact aims, outcomes and target audience. 
• Responding to the Challenge: Resources and guidance will be available as you respond to the challenge and create your artefact.
• Preparing for the Showcase: Guidance will be available on how best to showcase your artefact for the assessment. You will develop your presentation skills to support you in showcasing the artefact. 
• Showcase Event: You will attend a showcase event and present your artefact.

Brief description

You will discuss a range of anti-racist approaches and how they apply within the context of professional communications. You will examine case studies and scenarios to identify the nature of bias in society explore ways to be anti-racist especially in professional communications.

Indicative content

• Racial Bias in Society: Using case studies and scenarios to discuss various forms of racism in society, you will explore the need for anti-racist practice in professional communications. 
• Classification of Anti-Racist Practice: This section compares different anti-racists approaches applied across several contexts. You will discuss the challenges and benefits of each approach. You will identify barriers to implementation of anti-racist practice.
• Discuss Anti-Racist Approaches for Successful Professional Communications: You will be introduced to various communications frameworks (e.g. the humanity-centric framework) and will explore scenarios for the application of these frameworks in a range of professional contexts.
• Embedding Anti-Racism in Digital and Social Media Communications: How can you discuss matters of race and anti-racism on digital and social media while maintaining a professional persona. We will examine cases for best practices and explore ways to avoid bigoted language in digital communications. 

Brief description

In this module you will study two ways of analysing language: (i) a basic introduction to conversation analysis and discourse analysis as applied to ordinary talk/texting, and (ii) and introduction text mining, based on identifying patterns and developing insights from text-based data available on the Internet (e.g., social media data, online texts, online reviews etc).

Indicative content

• Conversation Analysis and Talk and Text as Action: A brief overview of the CA focus on language as action; an examination of how people talk in terms of questions, answers, invitations, excuses, justifications etc.; an examination of texting, emojis, misunderstandings.
• Text Mining: Introduction to text mining and its uses in a social sciences and business context; Online data sources; The text mining process: data collection, pre-processing and analysis; effectively communicating and visualising insights from textual data.

Brief description

By the end of this microcredential, you will be able to evaluate and select machine learning algorithms and AWS services to be appropriately applied to different business problems.

Indicative content

• Introduction to Machine Learning: What is ML? ML process, business problem solved with ML, ML tools, Amazon SageMaker, ML challenges, supervised learning (regression, classification), unsupervised learning (clustering, dimensionality reduction), reinforcement learning, etc.
• Implementing a ML pipeline using Amazon Sage Maker: Formulating ML problems, collecting and securing data, extracting, transferring and loading data, evaluating your data, finding corelation, feature engineering, data cleaning, dealing with outliers, training, deployment, performance evaluation, hyperparameters and model tuning.
• Forecasting: Time series analysis, Amazon Forecast, Implementing a forecast model, Stock Predictions.
• Computer Vision: Facial Recognition, Image and Video Analysis, Dataset Preparation.
• Natural Language Processing: Amazon Comprehend, Polly, Translate, and Lex, Creating a chatbot, Alexa, etc.

Brief description

This online module will support you to get familiar with sustainability and introduce you to tools that can help you to understand and reduce your climate impact. By increasing your sustainability self-awareness, you will be able to make a positive difference in your own life, and in the organisations and communities around you.

Indicative content

• What is sustainability and how is it linked to Climate Change?: We define sustainability, enhancing understanding of the links between society, economy, and environment. Climate change is explained and linked to sustainability. We provide clear accessible information about the reliable science of climate change. We describe the need efforts towards limiting human-induced global warming (limiting cumulative CO2 and other greenhouse gas emissions). 
• Global Sustainability: We introduce the United Nations Sustainability Goals (SDGs). The 2030 Agenda for Sustainable Development, adopted by all United Nations Member States in 2015, provides a shared blueprint for peace and prosperity for people and the planet, now and into the future. At its heart are the 17 Sustainable Development Goals (SDGs), which are an urgent call for action by all countries - developed and developing - in a global partnership. They recognize that ending poverty and other deprivations must go hand-in-hand with strategies that improve health and education, reduce inequality, and spur economic growth – all while tackling climate change and working to preserve our oceans and forests. 
• Personal Sustainability: The WWF environmental footprint tool is a great way to start your personal sustainability journey. The planet is in crisis - from climate change to the pollution in our oceans and devastation of our forests. It's up to all of us to fix it. Take your first step with our environmental footprint calculator. 
• Community Sustainability and Climate Resilience: Community climate resilience comes in many forms. In this topic we introduce ideas which can provide multiple benefits of people, planet, and prosperity. We showcase inspiring examples whereby working with natural processes (Biophilic design, blue and green infrastructure) we can connect people with nature to improve their well-being and quality of life, whilst simultaneously tackling climate change and storing carbon.
• Global Solutions: What is the world doing about it? What impact do Global Climate and Biodiversity agreements (COP26 etc) really have? What’s happening here? Where are the challenges and the good news stories? We showcase positive initiatives focussed on progress.

Brief description

By the end of the module, you will know more about key aspects of nutrition and health and be better equipped to identify and tackle the barriers that prevent you from eating well.

Indicative content

• Healthy eating on a budget: This topic will show you that healthy eating doesn’t have to be expensive! You will be given basic nutritional knowledge, as well as skills and practical tips to be able to eat a healthy diet on a budget. You will then be able to develop your own menu and share it with your peers, so you learn from us as well as from each other.
• Prebiotics, probiotics and health: You will learn about the importance of our microbiota on health, and how what we eat can modulate it. You will be provided with cooking tips and will be able to develop your own fermented foods for better gut health.
• Fat or sugar, which is worse?: You may have heard that fats are bad for our health, or perhaps you have heard it is all about the sugars? You will learn about the role of both sugars and fats in our diet; what makes them good or bad for health and the science behind it. You will be given the tools to assess your own sugar and fat intake as well as tips to implement the changes you need to eat better. 
• The British diet vs Mediterranean diet: What is a Mediterranean diet and what are its real benefits? Is it just a diet or a pattern? Can we get the same benefits as those living in Mediterranean countries? In this topic, you will explore how feasible it is for us to adopt the Mediterranean diet and lifestyle, considering the seasonality of ingredients as well as sustainability. 
• What drives our food choices?: How healthy do you think your diet is? Do you find it easy to eat well? With this topic you will become more aware of our obesogenic environment, of how the food industry talks to us, and how the media report nutritional claims. You will learn to look more closely and more critically at your environment, so you can make healthier decisions.

Brief description

This microcredential will help you to refine your current writing skills through the analysis and discussion of a range of texts and exercises, enabling you to then apply these techniques to assignments for your other modules.

Indicative content

• Speaking the language: How to develop your academic and professional vocabulary: understanding the genre; understanding your reader’s expectations.
• Meeting expectations: Why different assignments have different requirements: decoding instructions; selecting appropriate writing techniques.
• Tightening up the nuts and bolts: How to improve your writing accuracy: reviewing key grammar and punctuation issues; improving your editing and proofreading.
• Standing on the shoulders of giants: How to borrow from the greats: reviewing the principles of citing sources; using writing techniques to incorporate research into writing.

Brief description

This module will help you develop a better understanding of the difference between media reporting and scientific evaluation. It will equip you with the skills to look beyond sensational stories related to human behaviour and dig deeper into a topic area to validate the evidence.

Indicative content

• Paranormal Beliefs and Experiences: Is Extrasensory Perception Real? Is there really evidence that we can predict the future?
• Myths about the Brain: Can repressed memories be recovered in therapy? How easily are false memories created? What are the implications for the justice system? 
• Myths about our Mind and Body: Is the key to success in everyday life simply a case of posing like a powerful superhero? 
• Myths about Language: Does being bilingual make you smarter and keep your brain younger? Are bilingual people less likely to get dementia as a result of this lifelong brain training?

Brief description

Through this microcredential you will gain an insight into what the world of work may look like in the (near) future. This includes developing a knowledge of how the economy and labour market evolves and why individual skills-sets and employability are so important and intrinsically linked to this process.

Indicative content

• The future of work: What will the future of work look like? What is used to predict how the world or work will change? Can the future of the economy and of work be accurately predicted? 
• Key factors that influence change: Identifying some of the key factors that influence how the world of work and our economy evolves and changes.
• The key role of skills and personal employability: The emergence and decline of skills: skills are fundamental to the economy (and graduate employers). What skills will be most in demand and/or be most valuable to our economy in future and why? Understand the importance of skills to the economy (and to graduate employers) at both the macro and micro level. Know what specific new skills are emerging and becoming more valuable and sought after, (as others are in decline) for our modern economy and graduate labour market. 
• Labour market information - what is it for?: Labour market Information is hugely important to our understanding of our economy at any given time: and also, in looking at the present and past to help predict future growth, opportunities, shortages and skills gaps. Recognise the importance of key Labour Market Information (LMI). Have the ability to source and use key Labour Market Information (LMI). Understand how to use accurate Labour Market Information as a tool to help their own personal development and future career planning. 
• What now?: Some help and steer – suggestions to you may wish to use your new knowledge and insight to help with your own career aspirations, planning and personal/professional development while at university.

Brief description

Some businesses have the sole focus of making money whereas others exist to also make a difference. Social enterprises are becoming more popular, and recognisable, and are making an impact across the world. From supporting the homeless, to giving waste products a second life, social enterprises are fighting for various causes. 

Indicative content

• What is a social enterprise and how does it function?: What the definition of a social enterprise is with examples from different sectors.
• How do social enterprises identify problems to tackle?: How social enterprises decide on what they will tackle and how they will do it. 
• How do you gather evidence that there is a problem requiring a solution?: Way in which you can gather evidence and data to validate the idea for a social enterprise. Determining needs and wants within a category. 
• How to identify skills and knowledge gaps: Understanding the skillsets within a founding team to fulfil the tasks required to start a social enterprise. 
• How to understand the problem you are trying to solve: Knowing the problem, you are trying to solve and how this effects the target customers the social enterprise is aimed at. Looking at the issues in a customer-focussed way. 
• How to develop a social impact plan: What is involved in a social impact plan and how to put one together. 

Brief description

This module will introduce you to the study of AI and Society. Artificial Intelligence (AI) is a set of technologies and concepts and can be understood as using computers and software to denote problem-solving capacities and knowledge acquisition (intelligence) which otherwise we believe only belongs to natural beings such as humans.

Indicative content

• Introduction to the core concepts: A brief introduction to the concepts of “artificial”, “intelligence” and “society”. 
• Introduction to the problem of AI and Society: A discussion of where the problem of the impact of AI on Society comes from, presentation of some of the original debates and examples.
• Contemporary debates: A discussion of the contemporary debates about the impact of AI on Society, with examples.

Brief description

What is Artificial Intelligence (AI) and how has it shaped our past and present? These are questions we will explore on a guided tour of AI from the past to the present and the future. You will develop a better understanding of what AI is and isn’t.

Indicative content

• Historical AI: Tracing the historical development of “traditional” AI systems including aircraft autopilots, expert systems, and accounting/financial software.
• Current AI: Covering the contemporary generation of AI technologies in areas such as speech recognition (e.g., Alexa, Siri) and recommendation systems (e.g., Amazon, YouTube). Examples will be drawn from Health, Sport, Games, Engineering, Business, Law and Computing. 
• Future AI: Exploring the limitations of today’s AI when it comes to general intelligence and contextual adaptation. Examples will be drawn from Health, Sport, Games, Engineering, Business, Law and Computing.
• My AI: How AI will impact your future, and how you can use AI to help you achieve your career goals.  Reflection on how AI may inform your subject area going forward.

Brief description

This microcredential is aimed at you, if you have an interest in technology but are not experts. The microcredential will develop your digital safety and how to stay safe online.

Indicative content

• Threat Landscape: Cyberattacks and online threats. System vulnerabilities. Social Engineering. Rights and computer laws.
• Authentication: Password security. Biometrics. MFA and Password managers. Good practices for authentication.
• Secure Communication: Web browser security. Certificates and trust. Effective encryption. Secure communication methods.
• Personal Information Privacy: Information leakage. Personal information privacy and open-source intelligence. Device encryption and security. Security mindfulness.
• Malware: Types of malware. Identifying malicious software. Malware propagation techniques. Malware removal and preventative measures.

Brief description

This microcredential will help you to develop and build your own confidence in applying numeracy skills in real world situations.

Indicative content

• What is my GPA and how likely am I to get a First? (BASIC NUMERACY): Calculation and manipulation of data using Percentages, Indices (Powers), Roots, Probability, and simple equations. 
• The power of prediction (GRAPHS): Straight line graphs, Gradients, Equations of a straight line, Intercepts. Drawing graphs - Linear equations, Distances between points. Simultaneous linear equations.  
• Love a good puzzle (ALGEBRA): Changing subject of formulae. Factorisation - common factors, Difference of two squares, Trinomials. Solving simultaneous equations by Substitution and Elimination.
• Advanced power of prediction (FUNCTIONS): Introduction to functions – Linear and Quadratic and solving quadratic equations. Factorising Quadratic equations.
• Love a good triangle (TRIGONOMETRY): Trignometric functions - Sine, cosine and tangent. Trignometric formulae.

Brief description

In this microcredential, you will learn more about how digital media production professionals in the UK and China are working together to reduce barriers and identify new opportunities for collaboration and growth.

Indicative content

• History and future of videogames in China: Focussing on the videogame sector as a case study of Chinese digital creative industries, how has the videogames market and industry developed in China, how is the Chinese videogames economy currently constituted, and what does the future hold?
• Consumer trends and audience preferences: What is popular with audiences in China? What can we note about preferences in terms of narrative content, aesthetics, play styles etc. when compared with other markets?
• Policy and regulation: What unique regulations or limitations are imposed on digital media within China, and what similarities are there with other national and transnational regulations? How is creative content development and publishing shaped by policy in China? What social and ethical challenges are presented by regulation, in China as well as in the UK?
• Transnational working and co-production: How is digital creative content conceived, developed, and released by professionals working across borders? What are the challenges for small and independent creative studios, compared with multi-nationals with studios based in and outside China?
• Publishing in China: How do digital media content like videogames make it to market in China? What processes and requirements must creative businesses be aware of, and how do developers find, connect to, and work with Chinese publishers? How to consumers in China access content, including on grey markets?
• Challenges and success: Hear from UK and Chinese professionals on the China market, co-operation, the hurdles they cleared, and how they found success.

Brief description

Increasingly, the role of creativity in supporting and maintaining wellbeing is being researched and celebrated. This module will introduce you to the current theory in this area, as well as a range of creative resources shown to be helpful for both self-care and the support of others.

Indicative content

• Why does creativity matter?: An introduction to why creativity matters when it comes to mental health.
• Your brain on words: The place of stories in their various forms as a resource for wellbeing.
• Engaging the senses: The potential of tools such as music and art for self-care.

Year 3 Core Modules

You must study and pass all six core modules

Brief description

Understand web application development by learning to create a database back-end and related server-side scripts. Learrn key concepts in web application development such as security and the need to develop a professional approach.

Indicative content:

• Dynamic Site Basics: Write sites in HTML5 supported by CSS with a framework (eg. Bootstrap). Design and implement a database to store data in relational form; use PHP to extract data and deliver to the web page. Use of Javascript.
• Database Management Systems - Server-Side Scripting: Examine issues such as concurrency and distributed database, OO, SQL and NoSQL. Using techniques to develop a structured approach to scripting. Use of prepared statements to enforce secure scripting. Understanding of the MVC architecture and separation of Model, View Controller. Use of API and Web Services to deliver content from the database.
• Web Application Architectures - Security: Explore the 3−tier architecture and techniques of ensuring the separation of these tiers. Management of sites to allow interface changes without affecting the processing or database. Running through the module is the idea of secure coding. Main threats to the security of dynamic web applications and their data. Implement countermeasures to security threats within the context of differing types of application. 
• Databases: Appropriate use of the Relational database model to store data for dynamic web sites. Alternative models including NoSQL database model.
• JSON: JavaScript Object Model - Use of JSON as a data description language. Using JSON to deliver data between applications and servers. XML as an alternative.
• State Management within HTTP: Use of Cookies in web development. Sessions and session management. Client Management and Application Management within PHP. Examination of different models from other technologies.
• Client-Side Scripting: Review of Javascript as a client side language. Use of frameworks such as JQuery and AngularJS. Extension to Javascript server side development.
• AJAX – RIA: Use of AJAX to develop web pages. Single page Web Applications using AJAX (RIA). Especially building Mobile Web Apps.
• Internet of Things: Basic architecture of node / sensor domain, database and application domain. Creation of big data; upload to servers. Interrogation of servers to get information on the mobile device.
• Mobile Internet Sites: Creation of mobile internet sites. Inclusion of special features that make the mobile more appropriate especially location.

Brief description

Working within a team, learn project management concepts to create a project proposal in a professional manner. Present your work in a client pitch to a stakeholder. The project briefs are drawn from industry and/or research based problems. Expect to: engage fully in your team role, communicate effectively with project stakeholders, contribute to the planning of the project, develop artefacts or prototypes, write associated documentation, and create and present the client pitch.

Indicative content:

• Research: Background, competitors, prior art, project benefits.
• Project: Project management concepts, Agile, Scrum.
• Activities: Activities, deliverables and products.
• Managing: Managing time and resources.
• Identifying: Identifying and managing risks.
• Quality considerations: Professional standards and quality assurance.
• Develop: Develop artefacts, prototypes.
• Interacting: Interacting with clients and team members.

Brief description

Understand software development practices which can be used to to develop applications for a range of mobile devices. Develop and evaluate the techniques used to implement mobile applications.

Indicative content:

• Background to Smart and Mobile Development: Challenges in developing for smart including mobile devices. Development strategies, emulators and development environments. Use of the application abstraction to allow easier development.
• User Interfaces: Development of interfaces for user-interaction including UI controls (buttons, forms) and underlying hardware controls (key presses, touch screen). Basic control of a mobile device using the high user interface. Use of commands and forms to gain data from the client. Use of low level features to display data to the user. Use of key presses to control real-time application.
• Storage: Consideration of storage requirements for mobile devices. Saving and retrieving local and remote storage. Overview of database design. Use of remote databases, and how to use server side databases in an internet application. Use of internet based scripting to generate server side text for the client.
• Location awareness: Utilising the network location capabilities of mobile devices to develop feature rich applications.
• Telephony and SMS: Understanding the telephony and SMS stack on the mobile device and the use of APIs required for their access and control.
• Communication Networks: Using short and long distance networks for communication and understanding of the limitations and benefits of each.
• Security: Consider the security implications of mobile and smart platforms, how these can be exploited and development considerations to improve resilience.
• Performance: Methods for testing the functionality and performance of applications on mobile devices.
• Mobile Web Application Development: Explore and evaluate a range of mobile solution options from response design, jQuery mobile, and Javascript based applications.

Brief description

This module develops students’ understanding of how Machine Learning (ML) fits in Artificial Intelligence (AI) contexts. It observes how ML solutions became a vital component in the development of intelligent systems and how they can be utilised in certain types of problems within a wide spectrum of disciplines. The module introduces some of the many ML systems and relevant data concepts. Students are encouraged to select one technique to use in a given domain-specific application.

Indicative content:​

• Learning Pipeline Conceptual view of the fundamentals and terminology of ML, and the ability of a machine to learn from its environment. The structure and components of the traditional machine learning pipeline: data, model, and evaluation.
• Challenges of Applied ML The difficulties that arise with data-driven problems and the challenges accompanying an ML solution. Practical issues around data availability and representation, as well as characteristics of the applied model. The causes of overfitting and underfitting and possible remedies.
• Big Data The challenge of the 21st century is ‘too much data and not enough analysis’. Explore the challenges and opportunities afforded by this phenomenon. How data availability can positively or negatively control/affect businesses.
• Learning Paradigms The main approaches to learning and how a system can be supervised, unsupervised, or reinforced to produce a solution. The practicality of each paradigm and the constraints of its applicability.
• ML Techniques Linear Regression, Reinforcement Learning, Artificial Neural Networks, Clustering Algorithms, Feature Identification with Singular Value Decomposition, Support Vector Machine, Random Forests, Decision Trees, Convolution Neural Network.
• Data for ML The importance of data cleaning and pre-processing in ML context. Data representation. The curse of dimensionality. Feature selection and the impact of weak descriptors. Examples of datasets from different domains. Dimensionality reduction and Principal Component Analysis.
• Applications of ML Real-world data-driven problems. Applications and uses of ML solutions. Analysis and discussion of case studies in different contexts.
• Evaluation Metrics Analysis tools to assess the performance of a model. Understanding different metrics, what they describe the model, and their suitability in practice. Fitness function, Cost functions, False positive Rate, Receiver Operating Characteristics, Confusion Matrix. The Precision-Recall trade-off.
• Model Enhancement Addressing poor performance and situations where data availability may not be enough. Methods to improve performance, assist convergence, and speed up parameter optimisation. Regularisation, Gradient Descent, Cross-validation. Statement on Teaching, Learning and Assessment.

Brief description

Complete a team based development project or other technical investigation project, which was planned and initially developed in the module: Professional Project Planning and Prototyping.

Indicative content:

• Orientation: Consolidation of project teams and target problem.
• Project principles: Required development methodologies during product production.
• Documentation: The importance and content of a requirements specification and related documentation.
• Design: The role of design and redesign during project development.
• Implementation: Implementation issues and approaches.
• Quality and Standards: Testing and evaluation methods and execution.
• Communication: Oral and written communication and demonstration of software product.
• Project planning and team working: Planning the project, organising a team, supporting colleagues, devising weekly plans, keeping progress records.
• Self−evaluation: Personal contribution to team progress, logbook.

Brief description

Gain understanding and experience in design/programming within a software engineering context.

Indicative content:​

• Software engineering (SE): What is SE? Application to development process; application to programming practices.
• SE Development methodologies: Agile development; Waterfall Model; Continuous delivery.
• Source control: Strategies; tools; version control systems (git).
• Code development practices: Design concepts: Coupling and Cohesion; Continuous integration/continuous delivery (CI/CD); Test-driven development (TDD).
• Unified Modelling Language (UML): Use case diagrams; Sequence diagrams; Class diagrams; State-machine diagrams; Activity diagrams.
• Patterns: Pattern catalogues; reviewing a pattern; strategy pattern; observer pattern and variants; pattern implementation.
• Secure OO coding practices: Identifying coding vulnerabilities; types of exploits; protection through good programming practice.
• Protecting against the user: Full input verification & validation; handling passwords and encryption.

Year 4 Core Modules

You must study and pass all five core modules

Brief description

Develop an understanding of enterprise systems engineering by learning to design and implement solutions. Critically appraise enterprise internet solutions involving scalability, customisation and security.

Indicative content

• Architecting Scalable Enterprise Applications: Examine concepts that are required to architect and maintain scalable enterprise applications.
• API Security: Implementing and securing Application Programming Interfaces (API)
• Ensuring High Availability for your Enterprise Applications: Examine the core concepts of High Availability and how it can be deployed to ensure that enterprise applications are protected from failures.
• Load Balancing Enterprise Applications: Concepts that are required to deploy load balancing for enterprise applications.
• Working with Big Data: The core concepts of Big Data and how it is being used and deployed in enterprise environments.
• Securing Enterprise Applications: The concepts required to secure enterprise applications and how to protect the data that is being used by the applications.
• Distributed Databases in an Enterprise Environment. 
• Provisioning Enterprise Servers.

Brief description

Explore system programming and development and gain an understanding of the security implications of such systems.

Indicative content

• System Programming: C programming, compiler, linker and loader. Static and runtime analysis of binary files. System development kits, kernel headers and cross complier environments.
• Hardware: ASIC, MCU, CPU, SOC, assembly, component security, pcb security, sniffing wire traffic, radio traffic, Types of communication (I2C, SPI, UART, RS232) and security challenges.
• Operating systems: I/O Manager, Memory Manager, Scheduler, .s file, init file, boot loader, boot process, ROM, RAM, execution rings.
• Kernels: Types of kernel, real time, unix, Windows, mac, linux, user space vs kernel space, shell, native applications, dll, registry/proc. Security landscape in user and kernel space.
• Auditing and Debugging: User and kernel space debugging, Remote kernel debug setup, Analysis of precompiled binaries.
• Loadable modules: Linker, stack and memory layout, Interrupts, IRQ table and priorities. Introduction to device drivers, Types of driver, lifecycle, portability. Security risks associated with loadable modules.
• Cloud Platforms: Setup and use of cloud platforms such as AWS. Cloud platform utilisation fundamentals and business considerations.
• Web Technologies: TCP/IP protocol with understanding of application protocols such as HTTP, FTP, SSH etc. Understand web server and common gateway interface (CGI).

Brief description

Undertake the practical and development work for a major, in-depth individual project in an aspect of your programme. Devise the idea for the project and proof of concept to support the specification of a well-researched project proposal document.in Term 1. Carry out and complete the main development work for the project in Term 2.

Indicative content

• Investigation, Research and Selection: Initial investigation of project topic, Background research of project topic and Selection of project topic.
• Evaluation: Methods of evaluating a project.
• Legal, Social, Professional and Ethical Issues: Consideration of legal, social, ethical and professional issues.
• Proposal: Production of a project proposal.
• Project Ffeasibility and Proof of Concept: Demonstrate feasibility of project.
• Self-directed problem solving, Originality and Creativity.
• Self-Motivation, Initiative and Insight.
• Software Design Skills.
• Recording, Reporting and Communication Skills.
• Employability and professional development.

Brief description

Present as a dissertation a major, in-depth individual project in an aspect of your programme. Normally you will devise the project, drawing from current industry and/or research based problem areas. Present your work in a structured and coherent manner which allows for critical and insightful review and evaluation of the project and artefact produced. Write the dissertation in academic style appropriate to your domain of study.

Indicative content

• Introduction: Introduce the topic of the project and the problem area with and appropriate research question.
• Investigate: Investigate previous work in the chosen project area and show how the work of the project relates to it.
• Justify: Demonstrate a sound justification for the approach and methodology adopted.
• Document: Document the output of the project with some originality.
• Evaluate: Critically evaluate the output, using third party evaluation where appropriate, and recognise the strengths and limitations of the work.
• Communicate: Communicate your work professionally in the required academic format/style. Demonstrate an ability for independent learning and linkage to future work and career aspirations.

Brief description

This module provides students with an opportunity to explore advanced topics in the computing domain that are used to enhance modern business practices, for example computer vision, natural language processing, data visualisation and infrastructure.

Indicative content

• Visual Content Recognition: Introduction to computer vision applications and challenges. Improving businesses with Vision-aware Solutions. Convolution Neural Networks and Recognition. Popular Tools. Selected research paper(s) to read and discuss.
• Visual Content Creation: Features for Image Data. Examples of Image Datasets. Generative models and content creation. Model Deception and DeepFake. Ethics and Dataset Bias. Selected research paper(s) to read and discuss.
• Machine Learning for Text Analytics: Introduction to NLP applications and challenges. Improving businesses with Language-aware Data Products. Computational Linguistics. Popular Tools. Supervised and Unsupervised Models for Text Analytics. Selected research paper(s) to read and discuss.
• Deep Learning for NLP: Features for Textual Data. Text Corpora and Lexical Resources. Convolution Neural Networks for Ngram Detection. Recurrent Neural Networks for Modelling Sequence. Selected research paper(s) to read and discuss.
• Data Collection and Storage: Methods to collect data in various formats. Pre-processing of data to ensure integrity and formatting consistency. Storage mechanisms and infrastructures suited to the data format and velocity.
• Data Processing Pipelines: Creation of software-based processes to handle the entire lifecycle of data in an automated fashion. Will cover on-premises and modern cloud techniques.
• Approaches to Data Visualisation: Exploration of ways in which data can be presented in a visual manner. Software frameworks and libraries for data visualisation.
• Business Intelligence: Tools and process which will allow data to be formed into information and visual presentations which provide value and inform strategic decisions in a business. Communicating complex data to non-technical stakeholders. Providing interactive dashboards to communicate important information.