Artificial intelligence (AI) is a dynamic and multifaceted branch of computer science concerned with building intelligent machines capable of making decisions and solving problems that typically require human intelligence. The demand for expertise in computer science and artificial intelligence is rapidly increasing across organisations globally. Such technical expertise is required by a wide range of industries, including health care, agriculture, transportation, and finance.
Our BSc (Hons) Computer Science with Artificial Intelligence programme aims to develop confident and informed graduates who will be able to contribute to the advancement of current and emerging technologies. The artificial intelligence theme focuses on developing knowledge and practice in highly pertinent areas such as natural language processing; deep learning and its applications, and the ethical considerations of artificial intelligence systems.
Artificial intelligence (AI) is a dynamic and multifaceted branch of computer science concerned with building intelligent machines capable of making decisions and solving problems that typically require human intelligence. The demand for expertise in computer science and artificial intelligence is rapidly increasing across organisations globally. Such technical expertise is required by a wide range of industries, including health care, agriculture, transportation, and finance.
Our BSc (Hons) Computer Science with Artificial Intelligence programme aims to develop confident and informed graduates who will be able to contribute to the advancement of current and emerging technologies. The artificial intelligence theme focuses on developing knowledge and practice in highly pertinent areas such as natural language processing; deep learning and its applications, and the ethical considerations of artificial intelligence systems.
Focus on cutting-edge topics
Access to a range of specialist equipment
Taught by world-leading AI researchers
Gain industry recognised qualifications at no extra cost
Optional placement year
Undertake individual projects on topics of interest
In the first year, you can delve into the fundamental areas of computer science, developing skills in problem solving, programming, software engineering, and data science.
The second year builds on this foundation, covering artificial intelligence, full stack development, networking, and natural language processing. Throughout the year, you can collaborate on a team software engineering project.
In the third year, you are able to explore machine learning, mobile application development, image processing, autonomous mobile robotics and deep learning. There will also be opportunities to undertake a substantial individual project on a topic of interest under the supervision of an expert in the field.
The programme's modular structure typically consists of 12 weeks per module, comprising of lectures and supported workshop sessions for hands-on practical experience. You are expected to engage actively with the material presented in lectures and workshops, supplementing their in-class experience with a minimum of two to three hours of self-directed study for every hour spent in formal instruction. Industry certification opportunities are available to further enhance your skills and employability.
In the first year, you can delve into the fundamental areas of computer science, developing skills in problem solving, programming, software engineering, and data science.
The second year builds on this foundation, covering artificial intelligence, full stack development, networking, and natural language processing. Throughout the year, you can collaborate on a team software engineering project.
In the third year, you are able to explore machine learning, mobile application development, image processing, autonomous mobile robotics and deep learning. There will also be opportunities to undertake a substantial individual project on a topic of interest under the supervision of an expert in the field.
The programme's modular structure typically consists of 12 weeks per module, comprising of lectures and supported workshop sessions for hands-on practical experience. You are expected to engage actively with the material presented in lectures and workshops, supplementing their in-class experience with a minimum of two to three hours of self-directed study for every hour spent in formal instruction. Industry certification opportunities are available to further enhance your skills and employability.
This module aims to equip students with an understanding of time and space efficiency, enabling them to select appropriate algorithms for the programming problems they are presented with. Students will be introduced to relevant theoretical concepts around algorithms and data structures in lectures, together with practical experience of implementing them in the workshops.
This module introduces the fundamentals of computer hardware, which underpins core aspects of computer science. This knowledge is essential not only for a deeper understanding of the processes governing computing but also for realising how hardware interacts with software.
By studying Computer Architecture, students can gain greater confidence in their study subject and future benefits when improving their programming skills. The module will study the individual components of a computer system, their function, main characteristics, performance and their mutual interaction.
Data science is a relatively new field of study that utilises algorithms, statistics, and visualisation methods to answer scientific questions using data. In this module, students learn how to load, transform, visualise, and extract knowledge from data using their skills as programmers. Students can also gain experience in using interactive programming environments (e.g. IPython/Jupyter) and open-source libraries (e.g., numpy, matplotlib, pandas) that are widely used by data scientists in industry. In the latter part of the module, students will work in groups to analyse a real-world dataset and present their findings to their peers.
This module introduces you to software constructs and the development of programs using a high-level programming language. You can learn about standard programming practices and develop software using the object-oriented programming paradigm. Attention is paid to the fundamentals that constitute a complete computer program including layout, structure, and functionality. There is also emphasis upon the use of debugging tools and unit testing.
This module aims to introduce the main components of the software design and development process that ensure software is fit for purpose and of sufficient quality. You can develop your practical understanding and appreciation of frameworks for software development processes using case studies and practical implementations.
In industry, computer scientists and software developers work in teams to create solutions to a variety of different problems. This module aims to introduce you to the art of problem solving, teamwork, and the industry employment process. The professional aspects of working in the computing industry are explored to help equip you with the necessary skillsets required for an industry setting.
This module aims to provide a comprehensive analysis of the general principles and practices of advanced programming with respect to software development. Notions and techniques of advanced programming are emphasised in the context of analysis, design, and implementation of software and algorithms. Great importance is placed upon the Object-Oriented paradigm and related concepts applied to algorithm and software development using the C++ programming language, however students will also be exposed to the principles and underlying theories pertaining to functional programming.
The module aims to provide a modern introduction to the concepts of symbolic artificial intelligence, set in the context of intelligent agents.
The module covers the concepts such as state space representations and search, heuristic and adversarial search methods, and optimization techniques. The module also covers knowledge representation, AI planning, and some nonstatistical, machine learning methods.
This module will explore the ‘full stack’ of web application technologies. You will have the opportunity to learn how to design and develop both the frontend and backend of modern web applications. The module aims to cover the three-tier architecture approach for developing web applications: i) presentation tier, ii) application tier, and iii) data tier. You can learn how to use the relevant technologies for each tier, encompassing web presentation, application programmable interfaces (APIs), and database technologies. The overall aim of the module is for you to learn the how to develop robust client-server applications using secure and scalable technologies.
In this module, students learn how computers can be used to analyse and process the natural language that we use in our everyday lives. Natural language is a data type like no other, and presents a unique set of challenges for which the field of Natural Language Processing (NLP) has sought to provide answers. Common applications of NLP include machine translation, text summarisation, question answering, chatbots, grammar checking, and many others.
This module considers basic computer communications and networking with an emphasis on the Internet Protocol.
The module examines the Internet Protocol as a model for intercommunication in modern network implementations. Additionally the module examines fundamental design features of a Network Protocol and the need to implement security in the modern Internet.
The module adopts a standards driven approach and determines methods used in modern network systems for the distribution of data. An emphasis on network infrastructure and protocols underpins the module together with basic security considerations important in modern network architectures. Aspects of security concepts are extended to consider mechanisms that counter various forms of threat that exist from different sources.
This purpose of this module is to provide students with the experience of working as part of a team within a simulated commercial setting. Students will go through the key phases of software development from ideation through to development, testing, delivery, and publishing. Through the module students will learn how to manage and deliver commercial software development projects. This will include ethical, social and professional issues, project management, communication, time management, and team working strategies.
This module develops on the skills learnt in the first year and places them in a simulated commercial setting. The artefact produced as part of the software development process should be suitable for inclusion within a professional portfolio.
The module aims to introduce the main concepts of Autonomous Mobile Robotics, providing an understanding of the range of processing components required to build physically embodied robotic systems, from basic control architectures to spatial navigation in real-world environments.
Students will have the opportunity to be introduced to relevant theoretical concepts around robotic sensing and control in the lectures, together with a practical “hands on” approach to robot programming in the workshops.
Inspired by the biological neurons that make up our brains, artificial neural networks (ANNs) are simple mathematical models that date back to the work of McCulloch and Pitts in the 1940s. Today, ANNs are the powerhouses of modern AI solutions and are regarded as one of the most important technical innovations of the past decade. In this module, we will follow the chronology of the deep learning revolution, starting with the basics of deep feed-forward networks and how to train them effectively. We will then work our way forwards in time and study convolutional neural network (CNN) architectures for images, recurrent neural networks (RNN) for time series data, and unsupervised models for representation learning. Towards the end of the module, students explore how deep nets learn and study the issues that can impact their real-world utility and the implications for society at large.
Digital image processing techniques are used in a wide variety of application areas such as computer vision, robotics, remote sensing, industrial inspection, medical imaging, etc. It is the study of any algorithms that take image as an input and returns useful information as output.
This module aims to provide a broad introduction to the field of image processing, culminating in a practical understanding of how to apply and combine techniques to various image-related applications. Students will have the opportunity to extract useful data from the raw image and interpret the image data — the techniques will be implemented using the mathematical programming language Matlab or OpenCV.
The module introduces the fundamentals of machine learning and principled application of machine learning techniques to extract information and insights from data. The module covers supervised and unsupervised learning methods. The primary aim is to provide students with knowledge and applied skills in machine learning tools and techniques which can be used to solve real-world data science problems.
This module aims to equip you with the skills to design and develop connected, data-driven mobile applications, leveraging smartphone sensor technologies such as location, camera and proximity sensors. Consuming RESTful web services will be an area of focus for the data driven components of mobile app development. You can utilise contemporary tools to build mobile applications by applying industry-standard techniques for both code-base development and user-centered design.
This module offers students the chance to demonstrate their ability to work independently on a significant, in-depth project requiring the coherent and critical application of computer science theory and skills.
Students must initially produce a project proposal and related materials to frame the work, specifying clear, specific, academically justified, and appropriately scoped aims and objectives, as well as feasible means for fulfilling those aims and objectives. Students then work independently to fulfil those project goals. Throughout this process students are expected to demonstrate the application of practical development and analytical skills, innovation and/or creativity, and the synthesis of information, ideas and practices to generate a coherent problem solution.
† Some courses may offer optional modules. The availability of optional modules may vary from year to year and will be subject to minimum student numbers being achieved. This means that the availability of specific optional modules cannot be guaranteed. Optional module selection may also be affected by staff availability.
This module aims to equip students with an understanding of time and space efficiency, enabling them to select appropriate algorithms for the programming problems they are presented with. Students will be introduced to relevant theoretical concepts around algorithms and data structures in lectures, together with practical experience of implementing them in the workshops.
This module introduces the fundamentals of computer hardware, which underpins core aspects of computer science. This knowledge is essential not only for a deeper understanding of the processes governing computing but also for realising how hardware interacts with software.
By studying Computer Architecture, students can gain greater confidence in their study subject and future benefits when improving their programming skills. The module will study the individual components of a computer system, their function, main characteristics, performance and their mutual interaction.
Data science is a relatively new field of study that utilises algorithms, statistics, and visualisation methods to answer scientific questions using data. In this module, students learn how to load, transform, visualise, and extract knowledge from data using their skills as programmers. Students can also gain experience in using interactive programming environments (e.g. IPython/Jupyter) and open-source libraries (e.g., numpy, matplotlib, pandas) that are widely used by data scientists in industry. In the latter part of the module, students will work in groups to analyse a real-world dataset and present their findings to their peers.
This module introduces students to software constructs and the development of programs using a high-level programming language. Students will learn about standard programming practices and develop software using the object-oriented programming paradigm. Attention is paid to the fundamentals that constitute a complete computer program including layout, structure, and functionality. There is also emphasis upon the use of debugging tools and unit testing.
This module will outline the main components of the software design and development process that ensure software is fit for purpose and of sufficient quality. Students will develop their practical understanding and appreciation of frameworks for software development processes using case studies and practical implementations.
In industry, computer scientists and software developers work in teams to create solutions to a variety of different problems. This module aims to introduce the art of problem solving, teamwork, and the industry employment process to help equip students with the skillsets required for an industry setting.
This module aims to provide a comprehensive analysis of the general principles and practices of advanced programming with respect to software development. Notions and techniques of advanced programming are emphasised in the context of analysis, design, and implementation of software and algorithms. Great importance is placed upon the Object-Oriented paradigm and related concepts applied to algorithm and software development using the C++ programming language, however students will also be exposed to the principles and underlying theories pertaining to functional programming.
The module aims to provide a modern introduction to the concepts of symbolic artificial intelligence, set in the context of intelligent agents.
The module covers the concepts such as state space representations and search, heuristic and adversarial search methods, and optimization techniques. The module also covers knowledge representation, AI planning, and some nonstatistical, machine learning methods.
This module will explore the ‘full stack’ of web application technologies. You will have the opportunity to learn how to design and develop both the frontend and backend of modern web applications. The module aims to cover the three-tier architecture approach for developing web applications: i) presentation tier, ii) application tier, and iii) data tier. You can learn how to use the relevant technologies for each tier, encompassing web presentation, application programmable interfaces (APIs), and database technologies. The overall aim of the module is for you to learn the how to develop robust client-server applications using secure and scalable technologies.
In this module, students learn how computers can be used to analyse and process the natural language that we use in our everyday lives. Natural language is a data type like no other, and presents a unique set of challenges for which the field of Natural Language Processing (NLP) has sought to provide answers. Common applications of NLP include machine translation, text summarisation, question answering, chatbots, grammar checking, and many others.
This module considers basic computer communications and networking with an emphasis on the Internet Protocol.
The module examines the Internet Protocol as a model for intercommunication in modern network implementations. Additionally the module examines fundamental design features of a Network Protocol and the need to implement security in the modern Internet.
The module adopts a standards driven approach and determines methods used in modern network systems for the distribution of data. An emphasis on network infrastructure and protocols underpins the module together with basic security considerations important in modern network architectures. Aspects of security concepts are extended to consider mechanisms that counter various forms of threat that exist from different sources.
This purpose of this module is to provide students with the experience of working as part of a team within a simulated commercial setting. Students will go through the key phases of software development from ideation through to development, testing, delivery, and publishing. Through the module students will learn how to manage and deliver commercial software development projects. This will include ethical, social and professional issues, project management, communication, time management, and team working strategies.
This module develops on the skills learnt in the first year and places them in a simulated commercial setting. The artefact produced as part of the software development process should be suitable for inclusion within a professional portfolio.
The module aims to introduce the main concepts of Autonomous Mobile Robotics, providing an understanding of the range of processing components required to build physically embodied robotic systems, from basic control architectures to spatial navigation in real-world environments.
Students will have the opportunity to be introduced to relevant theoretical concepts around robotic sensing and control in the lectures, together with a practical “hands on” approach to robot programming in the workshops.
Inspired by the biological neurons that make up our brains, artificial neural networks (ANNs) are simple mathematical models that date back to the work of McCulloch and Pitts in the 1940s. Today, ANNs are the powerhouses of modern AI solutions and are regarded as one of the most important technical innovations of the past decade. In this module, we will follow the chronology of the deep learning revolution, starting with the basics of deep feed-forward networks and how to train them effectively. We will then work our way forwards in time and study convolutional neural network (CNN) architectures for images, recurrent neural networks (RNN) for time series data, and unsupervised models for representation learning. Towards the end of the module, students explore how deep nets learn and study the issues that can impact their real-world utility and the implications for society at large.
Digital image processing techniques are used in a wide variety of application areas such as computer vision, robotics, remote sensing, industrial inspection, medical imaging, etc. It is the study of any algorithms that take image as an input and returns useful information as output.
This module aims to provide a broad introduction to the field of image processing, culminating in a practical understanding of how to apply and combine techniques to various image-related applications. Students will have the opportunity to extract useful data from the raw image and interpret the image data — the techniques will be implemented using the mathematical programming language Matlab or OpenCV.
The module introduces the fundamentals of machine learning and principled application of machine learning techniques to extract information and insights from data. The module covers supervised and unsupervised learning methods. The primary aim is to provide students with knowledge and applied skills in machine learning tools and techniques which can be used to solve real-world data science problems.
This module aims to equip you with the skills to design and develop connected, data-driven mobile applications, leveraging smartphone sensor technologies such as location, camera and proximity sensors. Consuming RESTful web services will be an area of focus for the data driven components of mobile app development. You can utilize contemporary tools to build mobile applications by applying industry-standard techniques for both code-base development and user-centered design.
This module offers students the chance to demonstrate their ability to work independently on a significant, in-depth project requiring the coherent and critical application of computer science theory and skills.
Students must initially produce a project proposal and related materials to frame the work, specifying clear, specific, academically justified, and appropriately scoped aims and objectives, as well as feasible means for fulfilling those aims and objectives. Students then work independently to fulfil those project goals. Throughout this process students are expected to demonstrate the application of practical development and analytical skills, innovation and/or creativity, and the synthesis of information, ideas and practices to generate a coherent problem solution.
† Some courses may offer optional modules. The availability of optional modules may vary from year to year and will be subject to minimum student numbers being achieved. This means that the availability of specific optional modules cannot be guaranteed. Optional module selection may also be affected by staff availability.
We want you to have all the information you need to make an informed decision on where and what you want to study. In addition to the information provided on this course page, our What You Need to Know page offers explanations on key topics including programme validation/revalidation, additional costs, and contact hours.
We want you to have all the information you need to make an informed decision on where and what you want to study. In addition to the information provided on this course page, our What You Need to Know page offers explanations on key topics including programme validation/revalidation, additional costs, and contact hours.
A diverse range of assessment methods are used on the programme and are designed to evaluate your mastery of theoretical computer science and practical proficiencies. Assessment strategies include in-class tests, individual and group projects, and time-constrained assessments. The assessments reflect the applied nature of computer science, as such, a significant proportion of overall assessment is weighted towards coursework, emphasizing the hands-on experience required by the computing industry.
A diverse range of assessment methods are used on the programme and are designed to evaluate your mastery of theoretical computer science and practical proficiencies. Assessment strategies include in-class tests, individual and group projects, and time-constrained assessments. The assessments reflect the applied nature of computer science, as such, a significant proportion of overall assessment is weighted towards coursework, emphasizing the hands-on experience required by the computing industry.
There is a range of equipment for loan, including Raspberry Pi devices, smartphones, robots, and virtual reality equipment such as HTC Vive and Oculus Quest.
Students on this course are taught by academics whose research has been internationally recognised. Researchers in the School include Marc Hanheide, Professor of Intelligent Robotics and Interactive Systems, and Nigel Allinson MBE, Distinguished Professor of Image Engineering, who has been supported with a £3.3 million grant from the UK’s Engineering and Physical Sciences Research Council for advances in medical imaging.
The School is also a Microsoft Imagine Academy member and Cisco Academy member, which gives students the opportunity to gain industry recognised qualifications such as Microsoft Technology Associate and Cisco certification at no additional cost.
Students may also have the opportunity to participate in various extracurricular activities such as hackathons, game jams, and summer research projects.
This programme is optionally available in a sandwich mode variant. If you choose the sandwich placement option, you can take a year out in industry between the second and third year. This provides the opportunity to gain industrial experience. You will be supported throughout your placement, which can be overseas. A Placement Year Fee is payable to the University of Lincoln during this year for students joining in 2025/26 and beyond. You are expected to cover their own travel, accommodation, and living costs. There are also opportunities to take shorter work placements, for example over the summer period, and to be involved in academic’s research projects.
104 UCAS Tariff points from a minimum of 2 A Levels or equivalent qualifications.
BTEC Extended Diploma: Distinction, Merit, Merit.
T Level: Merit
Access to Higher Education Diploma: 45 Level 3 credits with a minimum of 104 UCAS Tariff points.
International Baccalaureate: 28 points overall.
GCSE's: Minimum of three at grade 4 or above, which must include English. Equivalent Level 2 qualifications may be considered.
The University accepts a wide range of qualifications as the basis for entry and do accept a combination of qualifications which may include A Levels, BTECs, EPQ etc.
We may also consider applicants with extensive and relevant work experience and will give special individual consideration to those who do not meet the standard entry qualifications.
Non UK Qualifications:
If you have studied outside of the UK, and are unsure whether your qualification meets the above requirements, please visit our country pages for information on equivalent qualifications.
https://www.lincoln.ac.uk/studywithus/internationalstudents/entryrequirementsandyourcountry/
International students will be required to demonstrate English language proficiency equivalent to IELTS 6.0 overall, with a minimum of 5.5 in each element. For information regarding other English language qualifications we accept, please visit the English Requirements page.
If you do not meet the above IELTS requirements, you may be able to take part in one of our Pre-sessional English and Academic Study Skills courses.
The University of Lincoln's International College also offers university preparation courses for international students who do not meet the direct entry requirements. Upon successful completion, students can progress to Bachelor's study at the University of Lincoln. Please visit https://www.lincoln.ac.uk/internationalcollege/ for more information.
For applicants who do not meet our standard entry requirements, our Science Foundation Year can provide an alternative route of entry onto our full degree programmes:
https://www.lincoln.ac.uk/course/sfysfyub/
If you would like further information about entry requirements, or would like to discuss whether the qualifications you are currently studying are acceptable, please contact the Admissions team on 01522 886097, or email admissions@lincoln.ac.uk.
96 to 112 UCAS Tariff points.
This must be achieved from a minimum of 2 A Levels or equivalent Level 3 qualifications. For example:
A Level: CCC to BBC
BTEC Extended Diploma: Distinction Merit Merit
T Level: Merit Overall
Access to Higher Education Diploma: 96 to 112 UCAS points to be achieved from 45 Level 3 credits.
International Baccalaureate: 28 points overall.
GCSE's: Minimum of three at grade 4 or above, which must include English and Maths . Equivalent Level 2 qualifications may be considered.
The University accepts a wide range of qualifications as the basis for entry and do accept a combination of qualifications which may include A Levels, BTECs, Extended Project Qualification (EPQ).
We may also consider applicants with extensive and relevant work experience and will give special individual consideration to those who do not meet the standard entry qualifications.
___________________________________________________
Non UK Qualifications:
If you have studied outside of the UK, and are unsure whether your qualification meets the above requirements, please visit our country pages
https://www.lincoln.ac.uk/studywithus/internationalstudents/entryrequirementsandyourcountry/ for information on equivalent qualifications.
EU and Overseas students will be required to demonstrate English language proficiency equivalent to IELTS 6.0 overall, with a minimum of 5.5 in each element. For information regarding other English language qualifications we accept, please visit the English Requirements page
If you do not meet the above IELTS requirements, you may be able to take part in one of our Pre-sessional English and Academic Study Skills courses.
___________________________________________________
For applicants who do not meet our standard entry requirements, our Science Foundation Year can provide an alternative route of entry onto our full degree programmes:
https://www.lincoln.ac.uk/course/sfysfyub/
If you would like further information about entry requirements, or would like to discuss whether the qualifications you are currently studying are acceptable, please contact the Admissions team on 01522 886097, or email admissions@lincoln.ac.uk
Going to university is a life-changing step and it's important to understand the costs involved and the funding options available before you start. A full breakdown of the fees associated with this programme can be found on our course fees pages.
For eligible undergraduate students going to university for the first time, scholarships and bursaries are available to help cover costs. To help support students from outside of the UK, we are also delighted to offer a number of international scholarships which range from £1,000 up to the value of 50 per cent of tuition fees. For full details and information about eligibility, visit our scholarships and bursaries pages.
Going to university is a life-changing step and it's important to understand the costs involved and the funding options available before you start. A full breakdown of the fees associated with this programme can be found on our course fees pages.
For eligible undergraduate students going to university for the first time, scholarships and bursaries are available to help cover costs. To help support students from outside of the UK, we are also delighted to offer a number of international scholarships which range from £1,000 up to the value of 50 per cent of tuition fees. For full details and information about eligibility, visit our scholarships and bursaries pages.
The best way to find out what it is really like to live and learn at Lincoln is to visit us in person. We offer a range of opportunities across the year to help you to get a real feel for what it might be like to study here.
