Computer Science (Artificial Intelligence) with Placement

Python is rapidly becoming the most important programming language in the world. It is used for everything from Artificial Intelligence (AI) applications and web technologies to financial modelling. Python has grown to be the prescribed language for AI and machine learning applications. Assuming no programming experience, this module prepares you for the exciting world of AI and programming by giving you the fundamental programming knowledge you need in the context of the Python programming language. Following successful completion of the module you are ready for advanced programming concepts.

Artificial Intelligence is an exciting and rapidly advancing technology.  The computer language of choice is almost exclusively Python.  Python is a powerful language with an unmatched ecosystem of software packages. This module equips the successful student with the tools they need for a life-long career in AI programming and data-driven problem solving. The student will learn the advanced language features required for solving the challenging AI problems. Material includes tools for data manipulation and preparation, AI programming software packages and visualisation tools. All instruction employs the industry standard programming tools universally used for experimentation and result dissemination. 

This module covers the fundamental components (hardware and software) of a typical computer system, and how they collaborate to execute programs. You will receive a comprehensive overview from the lowest level of abstractions in hardware to the highest level of abstractions of modern programming languages. You will explore the design of instruction set architectures, memory hierarchy, and data paths. Computer architecture focuses on the high-level design principles and trade-offs that govern the organization of these components, such as pipelining, caching, and parallelism.  Examples of topics that may be covered include logic circuits, machine language, processors, memory management, processes, concurrency, file systems, and operating systems. Throughout, special attention is paid to abstraction, performance, and other quality requirements. Understanding computer systems is essential for computer scientists, IT professionals, architects, and programmers to design, build, and optimise efficient and reliable computing systems for various applications and domains.

Machine learning is not only central to modern artificial intelligence, but across sciences and everyday life. You will learn how computers can program themselves automatically, learning from data or from active exploration of the world. You will develop ability to make sound, rational and effective judgements and decisions about the use of the core machine learning algorithms for different types of practical problems. Selected algorithms will be investigated in great depth, to give you deep understanding of the inner workings of machine learning.

Embark on a transformative journey into Natural Language Processing (NLP). By delving into the realm of NLP, you will gain a deeper understanding of the intricacies of language-based AI and learn valuable skills that are highly sought after in the tech industry. You’ll learn about how cutting-edge technology is being used in human language understanding and manipulation. Through hands-on practical explorations, you'll discover how to wield powerful NLP tools and libraries to craft artificial intelligence code capable of deciphering human-like text. You’ll find out about the power of language models, from traditional linguistics-influenced methods to state-of-the-art architectures. You’ll become adept at deploying these models critically and successfully, with the opportunity to explore a particular topic in more depth through practical project work.

Deep learning is an approach to machine learning developed over the past several decades that draws heavily on our knowledge of the human brain, statistics and applied mathematics. In recent years, deep learning has grown tremendously in popularity and usefulness, largely due to more powerful computers, larger datasets and techniques to train deeper networks. You will investigate modern deep neural networks starting from the fundamentals of Artificial Neural Networks (ANNs). You will start by learning what is an artificial neuron and architectures like multilayer perceptron, expanding on algorithms for training ANNs such as gradient descent and backpropagation. You will examine applications of deep learning with particular attention to coding aspects during lectures and practical activities. You will learn to use the most popular techniques to evaluate the performance of a model on real data. For this, you will be introduced to different types of deep neural networks, from convolutional networks to recursive neural networks, and autoencoders to address different problems with a particular focus on computer vision topics.

This module will guide you through the different stages of working on an exciting computer science project. World-leading experts in the field will support you along the way by providing supervision and monitoring of your weekly activities. With computer systems becoming more crucial in everyday life, you’ll have the opportunity to conceptualise, design, develop, and test your own large system capable of solving the identified challenges. Alternatively, you will explore and critically evaluate state of the art literature, identify relevant research methodologies to advance topics in computer science, carry out independent investigations, and make an impact in the research community. You’ll be empowered to explore different skills learned throughout your degree programme and apply them in the specific domain identified for your master’s project. Finally, you will reflect on your project journey throughout the writing of a well-organised dissertation demonstrating your individual reflection and achieved learning.

Software is everywhere, and its development should be tailored according to its requirements. This module will cover principles of software engineering following agile principles for guiding its development. You will investigate software modelling as means to understand and manage software complexity. As an integral part of software development, you will learn principles of planning, cost and time estimation, quality, and risk evaluation. You will also learn why software should be developed considering social, professional, and ethical principles, including security and privacy principles. You will work with your peers to develop or evolve a software system. You will apply the principles of agile methodology in your project, manage your team effectively, organise your code using version control, and resolve problems via issue tracking. You will identify risks for software projects and follow the principles for developing software with the highest professional standards.

Web-based information systems form the heart of e-commerce. In today's digital landscape, they are also increasingly the way businesses handle all their information needs. Building such systems requires an understanding of up-to-date tools and technologies such as web page creation, client-side programming, server-side programming and databases; it also calls for an understanding of how to design systems that genuinely meet user and business needs. This module will empower you with the essential skills and knowledge needed to thrive in the dynamic domain of e-business systems and in today's digital economy. You will learn the foundations for client-side and server-side programming as well as database design and implementation, critical knowledge on e-business systems and their properties. As technology continues to evolve, we will keep you ahead of the curve by exploring novel and emerging technologies in the e-commerce landscape.

Did you know that currently a majority of cyber security incidents involve one or more human elements (be it social engineering attacks, human errors, or misuse)? Today, it is clearer than ever that creating secure systems requires an appreciation of the underlying technology, but it also requires us to develop a solid grasp of people’s psychology – the ‘why’ people do, the ‘what’ they do, and the ‘how’ we can help them to adopt better security behaviours and practices. You’ll learn about human factors, usable security, security awareness, education and culture, all within the context of today’s organisations and social environments. With the knowledge gained, you’ll be able to think of technology systems more critically and in a socio-technical way which appreciates the various nuances of cyber security.

We will give you the statistical and computing skills you need to succeed in the rest of the course. Even if you have limited mathematical skills or no computer programming knowledge we will guide you to a level where you can apply advanced data science methods effectively. This module includes subjects such as introductory probability where you’ll learn how likely you are to win at a game of cards; introductory statistics such as testing a hypothesis in a clinical trial; and programming skills in a language such as R, including data visualisation. We will then move on to more advanced topics such as linear regression, which allows you to make predictions using multiple variables, and skills that will increase your employability, such as report writing, production of slides using appropriate software, and presentation skills. You will also find out about the important ethical implications of working as a data scientist.

The Year in Industry Placement provides you with a structured opportunity to combine work experience or entrepreneurial activity with academic study. The Year in Industry allows you to develop and reflect on managerial and/or professional practice in real and often complex situations, and to integrate this with the study of the relevant subject(s) of your main degree programme.

Where relevant, students develop, reinforce and apply professional and/or technical expertise in an employment or entrepreneurial context. The Industry Placement requires you to document your experiences in relation to both your university studies as well as to a wide range of employability skills. To be able to undertake this module it is necessary for you to secure a placement. The placement should be appropriate to your degree and experience. The length of the placement should normally be at least 44 weeks. It must be completed between the end of Summer Term and the start of the late Summer Term the following year. The particular combination of your degree course and choice of modules together with the great variety of increasingly diverse Year in Industry situations make the 'curriculum' of the Year in Industry essentially unique.

The Year in Industry provides you with a structured opportunity to combine work experience or entrepreneurial activity with academic study. The Year in Industry Report runs in tandem with the Year in Industry experience and offers you the opportunity to reflect and document your accomplishments during your industrial practice.

The Year in Industry allows you to develop and reflect on managerial and/or professional practice in real and often complex situations, and to integrate this with the study of the relevant subject(s) of your main degree programme.

Where relevant, you will develop, reinforce and apply professional and/or technical expertise in an employment or entrepreneurial context.

The Industry Report requires you to reflect on and evidence your experiences in relation to both your university studies as well as to a wide range of employability skills.

To be able to undertake this module it is necessary for you to secure a placement.

The placement should be appropriate to your degree and experience. The length of the placement should normally be at least 44 weeks. It must be completed between the end of Summer Term and the start the late Summer Term the following year.

The particular combination of the your degree course and choice of modules together with the great variety of increasingly diverse Year in Industry situations make the “curriculum” of the Year in Industry essentially unique.