Data Science for Cognitive Neuroscience and Psychology

Course aim

To develop students’ skills in the analysis, visualisation and critical understanding of data, to familiarise them with the basics of coding in an open source programming language relevant to data science, and to introduce the principles of open and reproducible science.

Course content

In this course, students will learn how to gain insights from data using contemporary computational tools. To this end, they will attain basic programming skills in an open source programming language (R or Python) and learn how to use online repositories such as GitHub or the Open Science Framework to share data and code. Students will also develop an understanding of how these tools help to foster open science, reproducible research and thus the ethical treatment of data. While critical for research in cognitive (neuro-)science, the data science skills acquired in this course generalise readily to other domains.

Textbook(s)

Hadley Wickham, Garrett Grolemund 2017, R for Data Science, 1st, O'Reilly, Sebastopol, CA

Prerequisite(s)

Common to all relevant programs
Subject Area & Catalogue Number	Course Name
BEHL 2005	Introductory Research Methods

Corequisite(s)

Nil

Teaching method

Component	Duration
INTERNAL, MAGILL
Workshop	3 hours x 10 weeks

Note: These components may or may not be scheduled in every study period. Please refer to the timetable for further details.

Assessment

Programming exercise, Report

Fees

EFTSL*: 0.125
Commonwealth Supported program (Band 4Y)
To determine the fee for this course as part of a Commonwealth Supported program, go to:
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Fee-paying program for domestic and international students
International students and students undertaking this course as part of a postgraduate fee paying program must refer to the relevant program home page to determine the cost for undertaking this course.

Non-award enrolment
Non-award tuition fees are set by the university. To determine the cost of this course, go to:
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Not all courses are available on all of the above bases, and students must check to ensure that they are permitted to enrol in a particular course.

* Equivalent Full Time Study Load. Please note: all EFTSL values are published and calculated at ten decimal places. Values are displayed to three decimal places for ease of interpretation.