Module code: DAT5501
Credits: 30.0
Semester: SEM1
Contact: Dr Seth Zenz
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.
Connected course(s): UDF DATA
Assessment: 75.0% Coursework, 25.0% Examination
Level: 5
