Clearing offers from 48 UCAS tariff points. Subject-specific requirements still apply. See the entry requirements section for details.
Artificial Intelligence (AI) is transforming everything from healthcare and finance to gaming and robotics. On this degree, you'll learn how to design systems that can learn, adapt, and make decisions - and graduate ready to step into one of the fastest-growing career areas in the world.
At Lincoln, this course is designed to take you from curious beginner to confident AI practitioner. You'll build real systems, work with industry-relevant tools, and develop the practical and problem-solving skills employers are actively looking for.
Artificial Intelligence (AI) is transforming everything from healthcare and finance to gaming and robotics. On this degree, you'll learn how to design systems that can learn, adapt, and make decisions - and graduate ready to step into one of the fastest-growing career areas in the world.
At Lincoln, this course is designed to take you from curious beginner to confident AI practitioner. You'll build real systems, work with industry-relevant tools, and develop the practical and problem-solving skills employers are actively looking for.
This course is designed to help you understand not just how AI works - but how to apply it in real situations.
You'll develop skills in:
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.
By the time you graduate, you'll be able to:
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. You will be provided with the knowledge of how core computer components function and how they come together to form a single system. The module will introduce data representation and digital logic, followed by a study of the Central Processing Unit, memory, interconnections and I/O devices. Standard, sequential (i.e. von Neumann) architecture will be compared to modern hardware platforms that are based on multi-core processors, parallel units and embedded systems.
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 offers a hands‑on introduction to the core concepts of machine learning, showing you how intelligent systems learn from data to make predictions and uncover hidden patterns. Through practical work with both supervised and unsupervised methods, you will build the skills needed to tackle real‑world data science challenges and apply machine learning techniques across a wide range of domains.
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.
This module provides an opportunity for students in the School of Engineering and Physical Sciences to spend a year abroad at one of the University’s partner institutions. During the year abroad, students share classes with students at their chosen destination and study on a suite of locally delivered modules. This module will extend the length of your programme by one year and is taken between level 5 (year 2) and level 6 (year 3).
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 and medical imaging. Image processing is the study of algorithms that take images as an input and return information about these images. 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 raw images and interpret the result.
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.
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.
This module is intended to introduce students with the fast growing area of consumer electronics design.
Apart from interface and size issues, portable consumer electronics present some of the toughest design and engineering challenges in all of technology. This module breaks the complex design process down into its component parts, detailing every crucial issue from interface design to chip packaging, focusing upon the key design parameters of convenience, utility and size.
Realistic physics simulation is a key component for many modern technologies including computer games, video animation, medical imaging, robotics, etc. This wide range of applications benefiting from real-time physics simulation is a result of recent advances in developing new efficient simulation techniques and the common availability of powerful hardware.
The main application area considered in this module is computer games, but the taught content has much wider relevance and can be applied to other areas of Computer Science.
The field of software development is continuously evolving, driven in part by the increasing usage of generative AI and the requirement to protect applications from sophisticated cyber-attacks. This module aims to introduce students to modern development practices. Students will gain hands-on experience in tools and practices used for secure application development, deployment and monitoring.
† 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. You will be provided with the knowledge of how core computer components function and how they come together to form a single system. The module will introduce data representation and digital logic, followed by a study of the Central Processing Unit, memory, interconnections and I/O devices. Standard, sequential (i.e. von Neumann) architecture will be compared to modern hardware platforms that are based on multi-core processors, parallel units and embedded systems.
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 offers a hands‑on introduction to the core concepts of machine learning, showing you how intelligent systems learn from data to make predictions and uncover hidden patterns. Through practical work with both supervised and unsupervised methods, you will build the skills needed to tackle real‑world data science challenges and apply machine learning techniques across a wide range of domains.
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.
This module provides an opportunity for students in the School of Engineering and Physical Sciences to spend a year abroad at one of the University’s partner institutions. During the year abroad, students share classes with students at their chosen destination and study on a suite of locally delivered modules. This module will extend the length of your programme by one year and is taken between level 5 (year 2) and level 6 (year 3).
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 and medical imaging. Image processing is the study of algorithms that take images as an input and return information about these images. 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 raw images and interpret the result.
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.
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.
This module is intended to introduce students with the fast growing area of consumer electronics design.
Apart from interface and size issues, portable consumer electronics present some of the toughest design and engineering challenges in all of technology. This module breaks the complex design process down into its component parts, detailing every crucial issue from interface design to chip packaging, focusing upon the key design parameters of convenience, utility and size.
Realistic physics simulation is a key component for many modern technologies including computer games, video animation, medical imaging, robotics, etc. This wide range of applications benefiting from real-time physics simulation is a result of recent advances in developing new efficient simulation techniques and the common availability of powerful hardware.
The main application area considered in this module is computer games, but the taught content has much wider relevance and can be applied to other areas of Computer Science.
The field of software development is continuously evolving, driven in part by the increasing usage of generative AI and the requirement to protect applications from sophisticated cyber-attacks. This module aims to introduce students to modern development practices. Students will gain hands-on experience in tools and practices used for secure application development, deployment and monitoring.
† 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.
Starting university - and studying a technical subject — can feel like a big step. That’s why support is built into every stage of your journey.
You’ll have access to:
This means you’re not expected to figure everything out on your own, there's support in place to help you succeed.
Gain hands-on experience in a real workplace and apply your learned skills in a professional setting.
AI is one of the most in-demand skill areas globally, and this degree is designed to help you access those opportunities.
Graduates can pursue roles such as:
You may also progress to:
The combination of technical skills and problem-solving ability means you won’t be limited to a single career path; you'll graduate with flexible, future-proof skills.
104 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: BCC to BBC
BTEC Extended Diploma: Distinction, Merit, Merit.
T Level: Merit Overall
Access to Higher Education Diploma: 104 to 112 UCAS points to be achieved from 45 Level 3 credits.
International Baccalaureate: 29 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 visithttps://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.
104 to 112 UCAS Tariff points from a minimum of 2 A Levels or equivalent Level 3 qualifications.
If you are eligible for a contextual offer, a one grade or 8 UCAS Tariff point reduction to the standard entry requirements will be applied.
A Level: BBC
BTEC Extended Diploma: DMM
T Level: Merit
Access to Higher Education Diploma: 45 Level 3 credits with a minimum of 112 UCAS Tariff points.
International Baccalaureate: 29 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 will 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 visithttps://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.
This course could be a good fit if you:
Not sure if you’re ready? You don’t need to be an expert, just motivated to learn.
University Study is a major investment, so it’s important to understand the costs and support available. A full breakdown of the fees associated with this programme can be found below. Eligible students may be able to access scholarships and bursaries to help with study costs.
University Study is a major investment, so it’s important to understand the costs and support available. A full breakdown of the fees associated with this programme can be found below. Eligible students may be able to access scholarships and bursaries to help with study costs.
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.
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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.