Data Science BSc

2024-25 entry
Information School

On this degree you'll develop ethical data-driven solutions which have a positive impact on organisations and society. Taught by active researchers and developed with industry experts, you'll learn the technical and analytical competencies necessary to become a responsible data scientist.

Key details

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    Course description

    Two students looking at a computer
    Two students looking at a computer

    Taught by active researchers and developed with industry experts, prepare for a career where you can use data-driven solutions to make a positive impact on society.

    Most data science courses are based in computer science or engineering departments - our degree is based in social sciences. That’s because we think it’s important to teach you not just the programming and analysis tools, but also how to use data-driven solutions responsibly and to the benefit of society.

    Data science underpins all kinds of decision-making, so you could be studying data from a sports team to improve performance, using real-world data as part of the solution to climate change, or analysing business expenditure.

    With opportunities to study abroad, work-based placements and developing your personal portfolio, you’ll be in a strong position for the future.

    Why study this course?

    • Become a critical data professional - learn how to work with and analyse data, and use your findings to make ethical, sustainable decisions – engaging different audiences and stakeholders, using visualisation and statistical methods.
    • Uniquely employable - developed with industry experts and taught by active researchers, this course gives you the skills to manage the complexities of data in organisations and to integrate the work of data scientists with those in more managerial or policy-making roles.
    • Sustainability, equality, diversity and ethical practice - with a strong focus on sociological theory, you will explore the underpinning concepts of responsible data science and the ethical application of technical approaches. By studying with us, you'll develop solid foundations in ethics, sustainability, critical thinking, and how to influence outcomes of data to positively impact society.
    Find out about our Data Science BSc

    Modules

    A selection of modules are available each year - some examples are below. There may be changes before you start your course. From May of the year of entry, formal programme regulations will be available in our Programme Regulations Finder.

    Choose a year to see modules for a level of study:

    Title: Data Science BSc
    UCAS code: I2L9
    Years: 2023
    Year one

    In year one, you'll develop fundamental capabilities and understandings in data science, including data visualisation and data modelling. With a strong focus on sociological theory, you will explore the underpinning concepts of responsible data science and the ethical application of technical approaches. You will also be introduced to computer programming and computational thinking.

    Practical Programming for Data Science 1

    This module introduces students to skills in computer programming and computational thinking needed for practical data science (e.g. decomposition, pattern recognition, abstraction and algorithms). Students will learn about the major programming paradigms used by data scientists (e.g. functional, object-oriented and event-driven) and explore the issues arising from the choices programmers make (e.g. potentially biasing assumptions about data or computation). The module will focus on programming with Python, one of the most widely used languages in data science. The module will also teach students how to use packages and productivity tools to support practical programming and extend base Python functionality. Students will also learn how to effectively use online resources for reference and training. Students will engage in problem-based learning throughout and practise key principles of effective group work in practical data science.

    20 credits
    Data Modelling and Storage

    This module uses an inquiry-based approach to introduce students to the various technologies used to model and store data. Primarily, it focuses on the competencies needed to design and implement a well-formed, relational database, populating, manipulating and querying it using Structured Query Language (SQL) executed from within a computer program. SQL is also introduced as an industry standard method to 'wrangle' data. That is, to transform and map data from one form to one to another, to meet some data science goal. The entire data modelling and implementation process is undertaken with reference to other Level 1 modules and framed around responsible data science. This includes the importance of acknowledging data origins and the contexts of application when considering data modelling techniques, ensuring legal compliance, and the awareness of the Sustainable Development Goals (SDGs).

    10 credits
    Communicating Data

    The vast amounts of information in a variety of types provide both opportunities and challenges to organisations daily. A primary aspect of data science is to make this information accessible to different groups of audiences, in different forms and mechanisms. Visualising data is an essential skill in communicating data effectively and is therefore a key process in decision making within organisations and in information dissemination to the public.

    This module will focus on theories and methods for visualising and presenting data and insights to different audiences. The module will discuss the building blocks of data visualisation, such as visual elements, and cover how to create and critique different visualisations to display data. The module will also cover design considerations and good practices in data visualisation and presentation.

    20 credits
    Data Driven Organisations

    Many organisations are making use of data, analytics, and new technologies (e.g., Artificial Intelligence, cloud computing, Internet of Things, and Big Data) to drive digital transformation and become more 'data-driven'. Data science (and increasingly AI methods) can be applied in many ways within organisations and used for activities including business intelligence, data mining, predictive modelling and automation. A key use of data and analytics is to improve the outcomes (speed, accuracy, and relevance) for all types of decisions, from operational to strategic. The use of data science and more advanced techniques allows organisations to respond rapidly to changing requirements and contexts. In particular, the combination of predictive and prescriptive methods allows organisations to tackle complex problems, such as forecasting and simulating outcomes, that may assist with more informed and evidence-based decision making. This module will help students to understand the organisational and business contexts in which data and data science can be used to support digital transformation. This includes the people, cultures, processes, and technologies that are needed to become an effective data-driven organisation. As well as considering the opportunities and benefits of using data and analytics, this module will also consider some of the common barriers faced by organisations in adopting such approaches. Students will also learn about the importance of data leadership to drive concrete actions and the need for a clear data strategy to guide and drive organisations to use and manage data effectively and achieve their specific business goals.The content in this module will be organised around three main themes: Organisations, the business context and the desire (and increasingly need) to be data-driven Building the capabilities of a data-driven organisation (i.e., what a data-driven organisation looks like)The adoption of data and analytics, and developing maturity (i.e., how to create and grow as a data-driven organisation). 

    10 credits
    Statistics for Insight

    This module equips students with a comprehensive overview of the fundamental aspects of quantitative research methods and statistics. Students undertaking the module will gain experience in dealing with data and ways to analyse and report them. Using data from a range of applications and sources, students will learn practical statistical techniques and fundamental principles, as well as using IBM SPSS software to analyse data to make inferences and predictions.

    In the initial part of the module students will learn research question development, study design, data cycle, sampling and confounding, types of data, graphical and tabular representation of data and results, summarising numeric and categorical data. Students will then move on to learn about data distributions, hypothesis testing, confidence intervals and probability theory to build the knowledge-base required to undertake inferential statistics to make deductions about populations.

    Inferential statistics techniques covered include parametric (e.g. t-tests, ANOVA, correlations) and non-parametric tests (e.g. Mann-Whitney, Kruskal-Wallis), bootstrapping and regression analysis. The module will also actively link with the learning undertaken in other Level 1 modules on the programme. Students will put into practice their newly acquired knowledge of statistical tools.

    20 credits
    Data Science Foundations and Contexts

    This foundational module underpins our approach to teaching future data scientists. It develops students' essential skills and awareness of the ethics and practicalities of real-world data science contexts. These contexts will include big business, academic research, cause-related charities as well as policy and public sectors.

    This module addresses two key questions: firstly, 'What makes data science a science?', through material on the origins and traditions of data uses; and secondly, 'How does thinking about data science as a social and information science help us imagine and realise more ethical and sustainable futures?'

    Core content includes:

    - the importance of useful data science, with critical understanding of how data science is used - in different contexts - for good and bad;

    - foundational professional skills and literacies (data, information, ethical and academic);

    - how data work in different contexts: in the workplace, personal data and different geographies, domains and industries;

    - how contextual data can improve understanding as well as ways that data are acquired, deployed, monitored and evaluated;

    - different origins and traditions of data science including its history, perspectives and disciplines;

    - the impact of data science and ethical innovations including critical data science, fairness, accountability, transparency, ethics and social justice (FATES), ethical data and Artificial Intelligence (AI), data and AI futures, data politics and activism, and using data for good causes;

    - cross-cutting themes such as sustainability (and the Sustainable Development Goals [SDGs]), decolonisation, and intersectionality;

    - the benefits, challenges and threats of AI and data-driven approaches to decision-making, as well as human computer interaction across multi-cultural contexts;

    - the core legislation, standards and codes of conduct related to data.

    40 credits

    The content of our courses is reviewed annually to make sure it's up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research; funding changes; professional accreditation requirements; student or employer feedback; outcomes of reviews; and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption.

    Learning and assessment

    Learning

    You'll learn through a mix of laboratories and practical classes, group work, interactive lectures and seminars, inquiry-based and self-directed learning. A diverse range of learning and assessment activities will support you to develop the Sheffield Graduate Attributes. You'll learn a broad set of skills, including teamwork and project-based tasks so that you will be ready for graduate career opportunities.

    On each module, you will be taught by subject specialists who are also active researchers in their field. This research-led approach means that our curriculum is current and relevant, and it is further supported by visiting lecturers and other industry-based experts.

    Our staff backgrounds and research reflect influences from computing, health, critical data studies and different social sciences disciplines, as well as experience from professional practice in data roles.

    Assessment

    Your lecturers are here to support your development, meaning that you’ll be given extensive feedback on your work. We use a range of assessment methods including, exams, online tests, group/individual presentations and coursework.

    Programme specification

    This tells you the aims and learning outcomes of this course and how these will be achieved and assessed.

    Find programme specification for this course

    Entry requirements

    With Access Sheffield, you could qualify for additional consideration or an alternative offer - find out if you're eligible.

    Standard offer

    The A Level entry requirements for this course are:
    AAB

    A Levels + a fourth Level 3 qualification
    ABB + A in a relevant EPQ
    International Baccalaureate
    34
    BTEC Extended Diploma
    DDD in Engineering, Applied Science, IT or Computing
    BTEC Diploma
    DD in Engineering, Applied Science, IT or Computing + A at A Level
    Scottish Highers
    AAAAB
    Welsh Baccalaureate + 2 A Levels
    B + AA
    Access to HE Diploma
    Award of Access to HE Diploma in a relevant subject, with 45 credits at Level 3, including 36 at Distinction and 9 at Merit
    Other requirements
    • GCSE Maths grade 6/B

    Access Sheffield offer

    The A Level entry requirements for this course are:
    ABB

    A Levels + a fourth Level 3 qualification
    ABB + A in a relevant EPQ
    International Baccalaureate
    33
    BTEC Extended Diploma
    DDD in Engineering, Applied Science, IT or Computing
    BTEC Diploma
    DD in Engineering, Applied Science, IT or Computing + B at A Level
    Scottish Highers
    AAABB
    Welsh Baccalaureate + 2 A Levels
    B + AB
    Access to HE Diploma
    Award of Access to HE Diploma in a relevant subject, with 45 credits at Level 3, including 30 at Distinction and 15 at Merit
    Other requirements
    • GCSE Maths grade 6/B

    English language requirements

    You must demonstrate that your English is good enough for you to successfully complete your course. For this course we require: GCSE English Language at grade 4/C; IELTS grade of 6.5 with a minimum of 6.0 in each component; or an alternative acceptable English language qualification

    If you have any questions about entry requirements, please contact the department.

    Graduate careers

    As an evolving discipline, data science skills and knowledge are in strong demand with employers across a number of sectors.

    We've worked closely with employers and industry partners to develop our curriculum to provide you with the relevant skills and experience to develop your future career. Our course is designed to equip students with the capabilities to manage the complexities of data in organisations and to integrate the work of data scientists with those in more managerial or policy-making roles.  

    All students have the opportunity to take either a placement year or a year abroad in between Levels 2 and 3.  Students can also opt for a work experience module in Level 3 to spend time developing real-world skills with a local partner organisation or business.

    Our annual Data Science Industry Day gives you an opportunity to meet employers and to link your learning at university with real-life contexts and challenges.

    Some examples of the areas you may choose to explore include:

    • Sustainability and global development
    • NGOs, charities and third sector organisations
    • Media and social media
    • Finance and business
    • Retail and ecommerce
    • Public sector, transport and health
    • Sports analysis
    • Academia and research

    Information School

    The University of Sheffield Information School is ranked number one in the world for library and information management in the QS World University Rankings by subject (2023, 2022 and 2021).

    By studying with us, you'll develop solid foundations in ethics, sustainability, critical thinking, and how to influence outcomes of data science to positively impact society.

    We offer an outstanding academic education through the principles of research-led teaching, so you're always challenged and up to date.

    The school has been at the forefront of developments in the information and data field for more than fifty years. The subject is characterised by its distinctive, interdisciplinary focus on the interactions between people, information and digital technologies.

    Our students are from around the world creating a multicultural, vibrant and invigorating environment where you can thrive in your learning. As part of our mission to provide world-quality university education in information, we aim to inspire and help you pursue your highest ambitions for your academic and professional careers.

    Our staff are experts in their field and work with organisations in the UK and worldwide, bringing fresh perspectives to your studies. They'll give you the advice and support you need to excel in your subject. We also work closely with partners and experts from industry, ensuring that your learning is always linked to your future career.

    You'll have access to a high-quality, specialised learning environment including cutting-edge computing suites and our iLab usability testing facilities.

    Information School

    Why choose Sheffield?

    The University of Sheffield

      Number one in the Russell Group
    National Student Survey 2023 (based on aggregate responses)

      92 per cent of our research is rated as world-leading or internationally excellent
    Research Excellence Framework 2021

      Top 50 in the most international universities rankings
    Times Higher Education World University Rankings 2023

      Number one Students' Union in the UK
    Whatuni Student Choice Awards 2023, 2022, 2020, 2019, 2018, 2017

      Number one for teaching quality, Students' Union and clubs/societies
    StudentCrowd 2023 University Awards

      A top 20 university targeted by employers
    The Graduate Market in 2023, High Fliers report


    Information School

    Number 1 in the world for library and information management

    QS World University Rankings by subject 2023

    Fees and funding

    Fees

    Additional costs

    The annual fee for your course includes a number of items in addition to your tuition. If an item or activity is classed as a compulsory element for your course, it will normally be included in your tuition fee. There are also other costs which you may need to consider.

    Examples of what’s included and excluded

    Funding your study

    Depending on your circumstances, you may qualify for a bursary, scholarship or loan to help fund your study and enhance your learning experience.

    Use our Student Funding Calculator to work out what you’re eligible for.

    Placements and study abroad

      Placement

    You may have the opportunity to add an optional placement year as part of your course, converting the three year course to a four-year Degree with Placement Year. 

    A placement year will help you to:

    • gain an insight into possible careers
    • develop a range of transferable skills
    • build a professional network
    • get a feel for what you do and don’t like doing
    • add valuable work experience to your CV
    • gain experience of applying for jobs and interview practice
    • apply elements of academic learning in the workplace

    Study abroad

    Spending time abroad during your degree is a great way to explore different cultures, gain a new perspective and experience a life-changing opportunity that you will never forget. 

    You can apply to extend this course with a year abroad, usually between the second and third year. We have over 250 University partners worldwide. Popular destinations include Europe, the USA, Canada, Australia, Singapore and Hong Kong. 

    Find out more on the Global Opportunities website.

    Visit

    University open days

    We host five open days each year, usually in June, July, September, October and November. You can talk to staff and students, tour the campus and see inside the accommodation.

    Open days: book your place

    Subject tasters

    If you’re considering your post-16 options, our interactive subject tasters are for you. There are a wide range of subjects to choose from and you can attend sessions online or on campus.

    Upcoming taster sessions

    Campus tours

    Our weekly guided tours show you what Sheffield has to offer - both on campus and beyond. You can extend your visit with tours of our city, accommodation or sport facilities.

    Campus tour: book your place

    Apply

    Make sure you've done everything you need to do before you apply.

    How to apply When you're ready to apply, see the UCAS website:
    www.ucas.com

    Not ready to apply yet? You can also register your interest in this course.

    The awarding body for this course is the University of Sheffield.

    Recognition of professional qualifications: from 1 January 2021, in order to have any UK professional qualifications recognised for work in an EU country across a number of regulated and other professions you need to apply to the host country for recognition. Read information from the UK government and the EU Regulated Professions Database.

    Any supervisors and research areas listed are indicative and may change before the start of the course.

    Our student protection plan

    Terms and Conditions upon Acceptance of an Offer

    2024-2025

    Make sure you've done everything you need to do before you apply.

    How to apply When you're ready to apply, see the UCAS website:
    www.ucas.com

    Not ready to apply yet? You can also register your interest in this course.

    On this degree you'll develop ethical data-driven solutions which have a positive impact on organisations and society. Taught by active researchers and developed with industry experts, you'll learn the technical and analytical competencies necessary to become a responsible data scientist.