University of St Andrews

Key information

SCOTCAT credits : 15

ECTS credits : 7

Level : SCQF level 11

Semester: Both

Availability restrictions: Available only to students studying the PG Cert/PG Dip/MSc in Data Science (Digital)

This module provides an introduction to Data Science research methods and to the types of skills necessary for the planning, data gathering, data analysis and dissemination stages of Data Science research. This module will help students to familiarise themselves with how academic data scientists evolve research projects from study design, through data collection and analyses, to publication and further dissemination. It will also help students with preparation for their dissertation module later in the programme.

Learning and teaching methods and delivery

Weekly contact: Students should expect to engage in approximately six tutorials over the course of the module, which will be scheduled with an awareness of the pace at which they are progressing, rather than at a fixed time each week. Students should consider the amount of independent study time this module involves when planning their learning.

Scheduled learning hours: 6

Guided independent study hours: 148

Assessment pattern

As used by St Andrews: Coursework = 100%

As defined by QAA
Written examinations : 0%
Practical examinations : 0%
Coursework: 0%

Re-assessment: Coursework = 100%

Personnel

Module coordinator: Professor T W Kelsey
Module teaching staff: Professor Tom Kelsey

Intended learning outcomes

• Understand the governance and ethical issues underpinning data use
• Be aware of concepts and options for study design and the precise formulation of research questions
• Understand the relationship between methodological approach and study design
• Have experience of the careful reporting of study methodologies and results
• Understand the technical, scientific and ethical issues that underpin the production and maintenance of data science solutions for use by the research and wider public communities