Data Science Research Methods (970G5)

15 credits, Level 7 (Masters)

Autumn teaching

This module will provide you with the practical tools and techniques required to build, analyse and interpret 'big data' datasets. It will cover all aspects of the Data Science process including collection, munging or wrangling, cleaning, exploratory data analysis, visualization, statistical inference and model building and implications for applications in the real world.

During the module, you will be taught how to scrape data from the Internet, develop and test hypotheses, use principal component analysis (PCA) to reduce dimensionality, prepare actionable plans and present their findings. In the laboratory, you will develop your Python programming skills and be introduced to a number of fundamental standard Python libraries/toolkits for Data Scientists including NumPy, SciPy, PANDAS and SCIKIT-Learn. In these sessions and your coursework, you will work with real-world datasets and apply the techniques covered in lectures to that data.


50%: Lecture
50%: Practical (Laboratory)


100%: Coursework (Observation, Report)

Contact hours and workload

We’re currently reviewing contact hours for modules and will update with further information as soon as it is available.

This module is running in the academic year 2019/20. We also plan to offer it in future academic years. It may become unavailable due to staff availability, student demand or updates to our curriculum. We’ll make sure to let our applicants know of such changes to modules at the earliest opportunity.


This module is offered on the following courses: