This module provides a wide range of appropriate data analysis techniques focusing on building from unstructured data to
models that allow patterns to be understood and acted upon organisationally. This includes implementing and validating
models of relationships between data, testing correlation vs causation, feature selection and introductory applications of
machine learning techniques. The module also includes professional software development techniques (e.g. distributed version
control, unit testing, continuous integration), key software for data professionals, project management, CV-writing, job interview
skills, communication, effective presentation and report writing with students working collaboratively to draw conclusions and
extract useful information from available datasets. They will gain the invaluable skills on how to interpret and report their analysis
and results in ways that are informative and appropriate to varied audiences including internal and external stakeholders for
informed decision-making purposes. This module is taught through a combination of lectures on theoretical background,
writing and presentation workshops, and computer lab-based group work, where students will complete investigative projects
on example real-world problems.
models that allow patterns to be understood and acted upon organisationally. This includes implementing and validating
models of relationships between data, testing correlation vs causation, feature selection and introductory applications of
machine learning techniques. The module also includes professional software development techniques (e.g. distributed version
control, unit testing, continuous integration), key software for data professionals, project management, CV-writing, job interview
skills, communication, effective presentation and report writing with students working collaboratively to draw conclusions and
extract useful information from available datasets. They will gain the invaluable skills on how to interpret and report their analysis
and results in ways that are informative and appropriate to varied audiences including internal and external stakeholders for
informed decision-making purposes. This module is taught through a combination of lectures on theoretical background,
writing and presentation workshops, and computer lab-based group work, where students will complete investigative projects
on example real-world problems.
