Data Science BSc (Hons)

Why study this course? 

• This Data Science BSc course offers a comprehensive introduction to the most important areas of the discipline, including data programming, statistical modelling, business intelligence, machine learning and data visualisation.
• Developed with input from industry experts, this course covers all the necessary skills and competencies required to delve deeper into this fascinating field. By the end of the BSc degree, you’ll be ready to apply for rewarding roles in the data science and big data industries, as well as the many sectors and organisations that increasingly require data scientists.
• Designed by academics from both Mathematics and Applied Computing backgrounds, this course is made up of fine-tuned modules which are prepared with your future in mind. The course will foster your learning development using a range of tools and big data platforms, allowing you to continue to specialise in data engineering, analytics, big data visualisation, statistical modelling and machine learning.

During your studies you’ll be encouraged to:

• Apply maths, statistics and science practice
• Recognise and exploit business opportunities using data science innovation
• Find a solution to domain-specific problems using data science capability
• Utilise a range of coding practices
• Build scalable data products for strategic or operational business and Contribute through the product life cycle
• Use tools such as Spark, Kafka, Hadoop, Oracle, SQL Server, Linux, Apache Airflow, RStudio, Python - Jupyter, Tableau, and D3 technology

Your learning will see you attend a variety of scheduled sessions such as lectures, tutorials, and workshops. This will be further developed by your revision of module materials and learning exercises outside of scheduled teaching hours. Throughout your learning experience you’ll find the teaching team on hand to support you.

What’s more, we have a wealth of appropriate blended learning technologies, such as the University’s virtual learning environment WebLearn, our library’s e-books and our online databases. These will further facilitate and support your learning, in particular to:

• Deliver content
• Encourage your active learning
• Provide formative and summative assessments with prompt feedback
• Enhance your course engagement

The specialist nature of this course will allow you to explore and experience advanced techniques in data science and data analytics. You’ll acquire practical skills, often first-hand from an external organisation, which will prepare you for your future as a data scientist.

You can get a taste for life at our School of Computing and Digital Media by taking a look at our showcase of recent student work.

Course modules

The modules listed below are for the academic year 2024/25 and represent the course modules at this time. Modules and module details (including, but not limited to, location and time) are subject to change over time.

Year 1 modules

• Data Analysis
• Financial Mathematics
• Fundamentals of Computing
• Introduction to Information Systems
• Logic and Mathematical Techniques
• Programming

Year 2 modules

• Data Analytics
• Data Engineering
• Databases
• Professional and Ethical Issues
• Programming with Data
• Smart Data Discovery
• Statistical Methods and Modelling Markets

Year 3 modules

• Artificial Intelligence and Machine Learning
• Big Data and Visualisation
• Career Development Learning
• Data and Web Development
• Project
• Cryptography and Number Theory
• Project Analysis and Practice

Data Analysis (core, 15 credits)

• This module introduces methods of analysing data using appropriate statistical software. Descriptive statistics and statistical techniques that are useful to present, analyse and make inferences about data are also introduced. A selection of suitable software (e.g. Excel, SPSS, R) will enable students to analyse data in order to make informed decisions.
• You’ll be provided with opportunities to develop an understanding of good academic practice, as well as the skills necessary to demonstrate this. In particular, you’ll be encouraged to complete weekly tutorial and workshop exercises as well as periodic formative diagnostic tests to enhance your learning. During tutorial and workshop sessions you’ll receive ongoing support and feedback on your work to promote engagement and provide the basis for tackling the summative assessments.

You’ll be assessed by a variety of methods throughout your studies. Module assessment typically consists of a combination of assessment methods including:

• Coursework
• In-class tests
• Exams

Coursework can include an artifact such as an output of dataset analysis, application of algorithms, data trends or program code in addition to a written report/essay. The volume, timing and nature of assessment will enable you to demonstrate the extent to which you have achieved the intended learning outcomes.

Formative and summative feedback will be provided using a variety of methods and approaches, such as learning technologies and one to one and group presentations of the submitted work at various points throughout the teaching period.

Where this course can take you

• This course will prepare you to work as a data analyst or in the fields of data programming, data visualisation, IT data consultation, big data solution designing or data solution development.
• This degree award can put you in a position to apply to companies such as Facebook, Mastercard, Amazon, Microsoft or the BBC for roles such as Junior Data Scientist, Data Science Operational Officer or Associate Data Analyst. 
• This course is also excellent preparation for further study or research.