This course will also introduce students to the lifecycle of a Data Science project from data capturing to data visualisations.

Students will explore the tools and techniques available to capture and analyse data to allow them to create a data science solution to meet business requirements. The student will demonstrate fundamental design principles and techniques to create meaningful visualisations of quantitative and qualitative data to facilitate decision making.

The learning outcomes enable learners to appraise data categories, including nominal and ordinal data, and understand how data can be processed to solve real‑world problems or answer research questions. Learners will critically appraise data analysis techniques used to ingest raw unstructured data, and to transform, clean and manipulate this data for further analysis, as well as examine and justify the selection of suitable statistical techniques for given requirements.

They will apply best practice for data gathering, data cleaning and data formatting to a specific use case, hypothesis or research question, and design and implement a data solution that meets professional requirements, including data visualisation and reporting. Learners will also apply data analysis and reporting techniques with an awareness of emerging trends in data science, and analyse and reflect on the design and implementation techniques used, presenting the findings of the completed data analysis and visualisation.