91抖阴

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 Top reasons to choose this course

• Developed with industry partners with your career in mind.
• Opportunity to take the SAS programming certification exam, highly sought after by employers.
• Option of a paid placement year to build your confidence and gain valuable work and networking experience; summer internships are also available.
• Specialist software used in industry including SAS, R, SQL and Python and platforms such as AWS.
• Practical project work including live coding sessions and analysis of live data sets provided by industrial partners.
• Collaborate on multidisciplinary projects with other schools such as 91抖阴 and Sussex Medical School (BSMS), the School of Applied Sciences and the School of Business and Law.
• Staff are active researchers, bringing opportunities to get involved in research projects.
• Based in one of the most important cities in the UK for digital technology businesses, offering networking and career opportunities.

Year 1 

In your first year you will be introduced to statistics, programming, visualisation, databases and core mathematics so you’ll gain all the mathematical and statistical background you’ll need for your studies.

Modules

• Managing Systems and Operations

  This module introduces you to digital technologies and operations management in business. You’ll explore contemporary issues, innovation and future trends in IS and operations management, examining how managers use digital technologies to measure and improve operations and systems performance. You’ll also develop an understanding of processes and how to improve them in both service-oriented and manufacturing-sector organisations. 

• Introduction to Data Analysis with SAS

  You will get an introduction to SAS programming and the basic statistical tools needed to use code to manipulate data and use the ‘point and click’ interface available in SAS Studio to perform data analysis. The module includes teaching materials developed in collaboration with industry-leading experts in statistics and analytics from the SAS Institute. You’ll gain the skills to manage and join multiple data sets, transform data, explore and visualise data.

• Computing Technologies

  This module will give you an understanding of the basic principles underlying the architecture and operation of a computer system, including the storage and retrieval of data. Content covers computer organisation and architecture; computer arithmetic, binary and hexadecimal number systems; system software; software tooling; data storage and management; relational database implementation; and an introduction to structured query language (SQL).

• Fundamentals of Programming

  This module introduces you to the key concepts of programming in the context of data analysis. You will use Excel to explore spreadsheets as a tool for organising and displaying data, and Python for programming, data analysis and manipulation.

• Mathematical Foundations

  You will learn the fundamental mathematical knowledge and skills required to successfully study for degree programmes in data and computing sciences. It will cover some of the basic concepts in algebra, geometry and calculus, and you will develop the ability to solve problems using the mathematical concepts introduced during the module.

• Introduction to Statistics

  This module introduces you to statistical and probability concepts and their real-world applications. Software packages such as SPSS and Microsoft Excel will be used to provide you with a grounding in industry appropriate statistical software. You will gain the skills required to apply statistics to real data sets together with the appropriate theory behind the applications.

Making sure that what you learn with us is relevant, up to date and what employers are looking for is our priority, so courses are reviewed and enhanced on an ongoing basis. When you have applied to us, you’ll be told about any new developments through .

Year 2 

In year 2 you will cover more advanced data analysis methodologies and strengthen your mathematical and programming skills. You will also develop your communication skills and your awareness of ethical issues related to managing data in a business environment.

Modules

• Linear Algebra and Further Calculus

  This module will introduce you to the fundamental concepts of linear algebra – such as vector spaces, subspaces, linear independence, linear transformations and further matrix algebra – and of multivariable calculus. Examples will enable you to develop an understanding of the general common principles that underlie many real-world applications.

• Database Management Systems

  This module explores the relational database model. You will gain practical experience in building database systems using this technology and explore the functions and features of database management systems and their role as part of an effective information system. 

• Programming for Data Science

  Programming for Data Science enables you to build on skills developed in year 1 and further explore concepts in programming, such as the object orientation approach, with a focus on how these can be applied to data science. You will use programming languages such as Python and R.

• Applied Machine Learning

  This module introduces the key concepts and ideas of machine learning in the context of practical data analysis, enabling you to use machine learning methods to extract value and insight from data. You will explore the common types of learning tasks, how to solve them and how to evaluate the quality of solutions. 

• Applied Statistical Modelling

  This module is covers a range of data analysis techniques including linear regression, logistic regression, poisson regression, multinomial logistic regression and ordinal logistic regression. The emphasis will be on the practical application of these methods using statistical software such as R, SAS and Python and real-world data sets. 

• Communicating Data

  The availability of  ‘big data’ has provided the means to collect vast amount of information which requires specialist skills to effectively disseminate to diverse audience. In this module, you will learn modern data visualisation tools and techniques to generate and communicate insights from data. You’ll also work on your report writing and presentation skills, focusing on best practice. 

Placement year

You have the option of a year’s paid placement after your second year. Going on a placement builds confidence, can help you decide what how you want to specialise in your final year and strengthens your CV.

Our students have been on placement with companies such as:

• Parexel (biopharmaceutical company)
• IBM
• Pensions Regulator
• The Home Office.

Final year

You choose five modules from a range of option modules. The Data Science Project is compulsory and provides opportunities to work with industry partners and contribute to our academic research. 

Modules

Core modules

• Data Science Project

  On this core module you will research a data science problem or topic in depth and present the results of your research to a small panel of lecturers. This is your opportunity to demonstrate your ability to explore new material, apply the skills, knowledge and techniques that you’ve learned during your studies and present your findings in a formal context. 

Options*

• Advanced Artificial Intelligence

  On this module you will examine current development in AI techniques and common issues that arise in real-world applications. You’ll develop an understanding of, and the skills needed to explore, advanced topics in AI such as logic, natural language processing (NLP) and speech and image recognition.

• Data Mining

  This module will help develop your understanding of data mining concepts and how they can be applied to solve real-world complex problems. You will explore areas including text mining, information extraction and information indexing, with specific algorithms and techniques for feature extraction.

• Time Series and Forecasting Models

  This module enables you to explore time series analysis used to model non-seasonal and seasonal data, and to analyse trends, patterns and seasonal variations over a time period. You'll be introduced to the concepts and methods used to predict future observations in different contexts such as to analyse financial data, stock prices, temperature readings, predict sales or marketing revenue. 

• Advanced Statistical Modelling

  On this module you will explore how to apply recent developments in statistical modelling, Bayesian approaches and complex statistical models to real-world problems using statistical software such as R, SAS and Python. An introduction to theory will help develop your understanding and you will examine real case studies so you can apply the theory and overcome the challenges of real data. 

• Natural Language Understanding

  This module enables you to develop the knowledge and skills relevant to natural language understanding (NLU) which is used in industry. You will explore NLU state-of-the-art techniques and apply artificial intelligence approaches to solve real-world problems and improve business performance. 

• Medical Statistics for Data Science

  This module focuses on the application of statistical concepts, models and techniques to analyse, compare and evaluate data from medical studies. You will explore the importance of statistics in medicine and develop an awareness of the problems associated with clinical medicine.

*Option modules are indicative and may change, depending on timetabling and staff availability.

Staff profile

, principal lecturer

Central to my approach as course leader is the emphasis on collaboration and interdisciplinary learning. I believe that data science is inherently interdisciplinary, drawing from fields such as statistics, machine learning, computer science, and domain-specific knowledge. Therefore, I strive to create opportunities for students to work collaboratively on projects that mirror real-world scenarios where they can leverage their diverse backgrounds and expertise to tackle complex challenges. Through teamwork, peer-to-peer learning and engagement with industry partners, students gain invaluable teamwork and communication skills that are essential for success in today's data-driven world.

In addition to teaching, my research focuses on developing innovative statistical methods, which I distribute as open-source software (R packages) and apply in interdisciplinary projects. As a Fellow of the Royal Statistical Society and Treasurer of the British and Irish Region of the International Biometric Society, I am heavily involved in professional development activities, participating in conferences, workshops and collaborations within the data science community. 

Course fees

This course offers a professional placement (sandwich) year in year 3. If you choose to take this placement you will pay a reduced fee during this year. For students starting their undergraduate degree in the 2025–26 academic year, the fee for the professional placement year is £1,500 for UK students and £1,850 for international students. This fee may be subject to small increases in line with inflation.

The fees listed here are for the first year of full-time study if you start your course in the academic year 2025–26.

You will pay fees for each year of your course. Some fees may increase each year.

UK undergraduate and some postgraduate fees are regulated by the UK government and increases will not be more than the maximum amount allowed. Course fees that are not regulated may increase each year by up to 5% or RPI (whichever is higher).

If you are studying part-time your fee will usually be calculated based on the number of modules that you take.

Find out more

• 91抖阴 Boost – cost of living help for our new undergrad students. Find out about how we can help with your study, accommodation or travel costs and more...
• Fees, bursaries, scholarships and government funding info for UK and international undergraduate students
• Student finance and budgeting while studying
• Read our student contract and (pdf) for more on 91抖阴 tuition fees.

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