Turn data into decisions that change outcomes.

Explore common cyber threats, defensive techniques, digital forensics and the human side of security.

Combine hardware, software, sensors and actuators to understand simple robotics and connected-device systems.

Develop algebra, functions, graphs, differentiation and integration as foundations for technical study.

Design algorithms and structured programs using sequence, selection, iteration and list processing.

Use statistical software to summarise, visualise and interpret data and test evidence-based conclusions.

Apply interest, depreciation and amortisation calculations to practical financial problems using spreadsheets.

Study information processing, algorithms and data structures alongside quality, complexity, privacy and security.

Understand how organisations use data, knowledge and information systems to support performance and decisions.

Work with sets, logic, relations, functions, algebra, vectors, differentiation and integration for computing.

Design, document, implement and test object-oriented programs using established development techniques.

Model, store, retrieve and process data using practical engineering tools and collaborative workflows.

Use Python, data structures and robust input-output techniques to prepare and present data solutions.

Apply exploratory statistics, correlation and linear regression across the full data-analytics lifecycle.

Analyse requirements, model relational data and implement databases using SQL and sound design principles.

Examine the legal, social, ethical and professional responsibilities that shape computing and research.

Prepare, model, evaluate and visualise data to deliver useful insight in modern business contexts.

Fit and interpret statistical models for real financial data using tools such as Excel, R and SPSS.

Apply AI reasoning and machine-learning techniques to tasks such as recognition and forecasting.

Complete an approved professional activity that builds experience, reflection and industry connections.

Create a complex database-backed web application using advanced SQL and contemporary data technologies.

Evaluate how organisations select, manage and lead strategic big-data and AI initiatives.

Use project methods such as Agile and modelling tools such as UML within a collaborative business scenario.

Plan and deliver an approved data-science project that solves a problem, creates an artefact or investigates innovation.