University of St Andrews

Key information

SCOTCAT credits : 15

ECTS credits : 7

Level : SCQF level 10

Semester: 1

Availability restrictions: "Available only to students in the second year of the Honours Programme, Research Methods in Psychology or Master of Research Neuroscience programmes."

Planned timetable: Wednesdays 2-4pm

Data science has become a critical part of scientific and industry working. This module will introduce students to modern data science methods such as machine learning and data mining. Emphasis will be given to the practical utilisation of these methods in the context of psychology and neuroscience.

Relationship to other modules

Pre-requisite(s): Before taking this module you must ( take PS3021 or take PS3023 or take PN3025 ) and ( take PS3022 or take PS3024 or take PN4026 ) or take PN3322

Learning and teaching methods and delivery

Weekly contact: "1 lecture, 1 practical (x10 weeks)"

Assessment pattern

As used by St Andrews: Coursework = 100%


Re-assessment: "Coursework=100%, Re-assessment applies to failed components only"

Personnel

Module coordinator: Dr J M Ales
Module teaching staff: Dr Justin Ales
Module coordinator email jma23@st-andrews.ac.uk

Intended learning outcomes

• "By the end of the module, students will be able to understand basic methods for data science analysis"
• "By the end of the module, students will be able to implement basic data science analysis methods"
• "By the end of the module, students will be able to recognise common difficulties that arise with data"
• "By the end of the module, students will be able to understand ethical issues that occur when using data science methods in society"