The world is full of data, from global banks to Formula 1 teams, supermarkets and the United Nations. Data scientists ask and answer questions like what happened, why it happened, what will happen, and what can be done with the results.
Data scientists use principles and practices from the fields of mathematics, statistics, artificial intelligence, and computer engineering, to analyse and generate meaning from data. At Kent, you're taught how to apply cutting-edge machine learning and deep learning methods, and how to make sense of the text data that is all around us.
Taught by experts in the field, you'll use real-world data to learn the technical, practical and transferrable skills needed to be a successful data scientist. This conversion course is designed for those with limited previous knowledge of data science, statistics and computing: you don't need a background in the subject as we start with the foundations of data science theory.
Artificial intelligence and machine learning innovations have made data processing faster and more efficient. Industry demand has created job positions in organisations around the world within the field of data science. Due to the skillset and expertise required, this looks likely to continue over the coming decades. Add a Year in Industry to further enhance your employability.
A 2:2, 2:1 or First Class degree.
All applicants are considered on an individual basis and additional qualifications, professional qualifications and relevant experience may also be taken into account when considering applications.
Please see our International Student website for entry requirements by country and other relevant information. Due to visa restrictions, students who require a student visa to study cannot study part-time unless undertaking a distance or blended-learning programme with no on-campus provision.
This course requires a Good level of English language, equivalent to B2 on CEFR.
Details on how to meet this requirement can be found on our English Language requirements webpage.
Examples:
IELTS 6.0 with a minimum of 5.5 in each component
PTE Academic 63 with a minimum of 59 in each sub-test
A degree from a UK university
A degree from a Majority English Speaking Country
Please note that if you are required to meet an English language condition, we offer a number of pre-sessional courses in English for Academic Purposes through Kent International Pathways.
We’ve created the most progressive approach to higher education, developing and modernising our curriculum. For 2025 our courses will be designed with you at their heart to deliver a top-class student experience and career outcomes.
The following modules are what students will typically study, but this may change year to year in response to new developments and innovations.
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.
Dive into the exhilarating world of machine learning, where cutting-edge artificial intelligence meets real-world applications. With our comprehensive program, you'll discover how computers can autonomously learn and evolve, harnessing data and active exploration to perfect their algorithms. By mastering these revolutionary techniques, you'll gain the skills to make insightful, effective decisions tailored to a wide array of practical challenges. Our in-depth exploration of key algorithms ensures you not only understand but excel in the intricacies of machine learning, positioning you at the forefront of innovation. Embrace the future - let machine learning elevate your expertise and ambition to new heights.
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.
This module offers a comprehensive exploration of foundational Bayesian algorithms within the realm of probabilistic machine learning, equipping you with cutting-edge techniques applicable across diverse domains including natural language processing, image recognition, and fraud detection. You’ll delve into fundamental Bayesian Inference concepts, including prior and posterior distributions, Bayesian estimation, Bayes factor, model selection, and forecasting. You’ll gain knowledge of various posterior sampling algorithms and see how to apply them through real-world instances in linear regression and classification. You’ll also learn about the latest trends in the field including variational Bayes and online learning. Through a combination of lectures and practical computer-based sessions, you’ll gain hands-on experience and theoretical insights and gain a deep understanding of probabilistic machine learning methodologies.
You will build on the knowledge from Foundations of Data Science, gaining advanced skills that you will use in your career as a data scientist. Our emphasis is on both data modelling skills and the ability to apply this knowledge to messy, real-world data. We will teach you technical skills that are in demand from employers, including different types of sophisticated statistical models and how to apply them using computer languages that are used by many organisations. You will apply these methods in the role of a consultant, working with a stakeholder, such as a client, who has given you a realistic data problem. This will involve working on the problem from the initial meeting, through understanding and analysing the data, to presenting the results back to the client.
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.
The data science project is an opportunity to bring together everything you have learned on the course. You will carry out an extended piece of research on an important topic, including the opportunity to propose your own project, exploring the subject in depth using the data science methods that you have studied in the earlier modules. We will guide you through planning the project, providing you with initial comments, and then you will prepare and give a presentation describing your initial findings. The feedback we give you will help you to carry out your subsequent analyses in an effective way. Throughout the project you will be guided by a member of academic staff who will supervise your analyses based on their particular expertise. You will describe your work in an extended written report, which will be evidence of your abilities in data science that you can show to potential employers.
Assessments includes extensive analyses of complex real-world data. There will be unseen written examinations but most of the credit is based on coursework, including an independent project and report supported by an academic supervisor. Assessments will involve working with messy data where analyses need to be presented to 'clients', group work on coding projects, and development of data visualisation tools that could be used by a particular organisation. There will be exposure to assessments that are relatively low stakes, such as project plans and presentations. The technology to be used to undertake assessment will be standard: any computer with a modern specification will be appropriate.
For course aims and learning outcomes please see the course specification.
Kent’s Computing Service central facility runs Windows. Within the School, postgraduate students can use a range of UNIX servers and workstations. Packages available include R, MATLAB, SPSS, STAN and Python.
Staff publish regularly and widely in journals, conference proceedings and books. Among others, they have recently contributed to: Annals of Statistics; Biometrics; Biometrika; Journal of Royal Society, Series B; Statistics and Computing. Details of recently published books can be found within our staff research interests.
You will be a trained data scientist, equipped to work in many fields. Organisations with data will require your skills: you might work for a national government, an insurance company, as an archaeologist or for a football club or cricket franchise. Alternatively, perhaps you see yourself as a future entrepreneur, using what you’ve learnt about data to develop your own business. To help you decide, you’ll be able to attend talks from professionals who work with data and to attend networking events with employers.
The 2025/26 annual tuition fees for this course are:
For details of when and how to pay fees and charges, please see our Student Finance Guide.
Tuition fees may be increased in the second and subsequent years of your course. Detailed information on possible future increases in tuition fees is contained in the Tuition Fees Increase Policy. If you are uncertain about your fee status please contact information@kent.ac.uk.
The University will assess your fee status as part of the application process. If you are uncertain about your fee status you may wish to seek advice from UKCISA before applying.
For details of when and how to pay fees and charges, please see our Student Finance Guide.
Tuition fees may be increased in the second and subsequent years of your course. Detailed information on possible future increases in tuition fees is contained in the Tuition Fees Increase Policy. If you are uncertain about your fee status please contact information@kent.ac.uk.
You'll need regular access to a desktop computer/laptop with an internet connection to use the University of Kent’s online resources and systems. We've listed some guidelines for the technology and software you'll need for your studies.
Find out more about student accommodation and living costs, as well as general additional costs that you may pay when studying at Kent.
Search our scholarships finder for possible funding opportunities. You may find it helpful to look at both:
We have a range of subject-specific awards and scholarships for academic, sporting and musical achievement.
Next steps
Learn more about the application process or begin your application by clicking on a link below.
You will be able to choose your preferred year of entry once you have started your application. You can also save and return to your application at any time.
Apply - Full-time at Canterbury
Apply - Full-time at Canterbury
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Kent ranked top 40 in The Times Good University Guide 2025.
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Kent has risen 11 places in THE’s REF 2021 ranking, confirming us as a leading research university.
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