Data Science (BSc)

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. 

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.
• 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.

Modules

• We're revising the curriculum of this course for this year of entry and are in the process of confirming the modules. The information on this page gives you an idea of the areas we expect the course to cover. There may be changes before you start. 

Year 1

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
• Data Modelling and Storage
• Data Driven Organisations
• Communicating Data
• Statistics for Insight
• Data Science Foundations and Contexts

Year 2

In year two, you'll build on these foundations and apply these to the data lifecycle and team-based projects. You’ll enhance your programming skills to develop software that processes and analyses data in complex data structures.

• Data Ethics and Leadership
• Practical Programming for Data Science 2
• AI and Machine Learning for Advanced Analytics
• Databases and Beyond
• Using Data for Responsible Decision Making
• Responsible Data Science Lab 1

Final Year

In your final year (year three or four, depending on whether you choose to do a placement year), you'll have the opportunity to specialise and to prepare yourself for employment through your portfolio and your independent study.

• Responsible Data Science Lab 2
• Data Science Portfolio
• Building AI Applications
• Researching Social Media

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

• 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.

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