Studying online

There are now 2 possible online modes for units:

Units with modes Online timetabled and Online flexible are available for any student to self-enrol and study online.

Click on an offering mode for more details.

Unit Overview

Description

Data is ubiquitous in modern society. It is used to monitor the economy, inform business decisions, understand how the environment is changing, and communicate public health messages. Data science is a booming field that harnesses raw data and turns it into actionable knowledge. Data Scientists develop and employ tools to collect, understand and communicate data and its meaning. They are able to identify trends, understand demographics and inform interventions. They are able to work across disciplines, from science to business, health, media and politics. But data can also be misused, and a professional Data Scientist will understand the ethical demands of responsible use of data. This hands-on unit provides practical experience, using the programming language Python, for solving real-world data science problems, from acquiring data from public sources, to understanding the data through analysis and modelling, to visualising and presenting the results.

Credit
6 points
Offering
(see Timetable)
AvailabilityLocationMode
Semester 2UWA (Perth)Face to face
Outcomes

Students are able to (1) understand and implement the stages in the data science lifecycle, from data acquisition and cleaning through to analysis, modelling and visualisation; (2) independently research, solve and communicate results for real-world data science problems from across a range of disciplines; (3) demonstrate a command of computational structures and operations, and discuss the relevant efficiency and storage implications of alternative solutions; (4) utilise appropriate encoding and visualisation methods for different types of data, including categorical, numerical and time-series data; (5) understand the power of data used well or used poorly, and critically assess the way data is used and presented in business, science, the media and the wider community; and (6) recognise and discuss the ethical responsibilities of a data scientist.

Assessment

Indicative assessments in this unit are as follows: (1) mid-semester test; (2) project; and (3) final examination. Further information is available in the unit outline.



Student may be offered supplementary assessment in this unit if they meet the eligibility criteria.

Unit Coordinator(s)
Dr Debora Correa
Unit rules
Prerequisites
CITS1401 Computational Thinking with Python
or CITX1401 Computational Thinking with Python
or CITS2401 Computer Analysis and Visualisation
Contact hours
lectures: 2 x 1 hour per week
laboratory: 1 x 2 hours per week.
  • The availability of units in Semester 1, 2, etc. was correct at the time of publication but may be subject to change.
  • All students are responsible for identifying when they need assistance to improve their academic learning, research, English language and numeracy skills; seeking out the services and resources available to help them; and applying what they learn. Students are encouraged to register for free online support through GETSmart; to help themselves to the extensive range of resources on UWA's STUDYSmarter website; and to participate in WRITESmart and (ma+hs)Smart drop-ins and workshops.
  • Visit the Essential Textbooks website to see if any textbooks are required for this Unit. The website is updated regularly so content may change. Students are recommended to purchase Essential Textbooks, but a limited number of copies of all Essential Textbooks are held in the Library in print, and as an ebook where possible. Recommended readings for the unit can be accessed in Unit Readings directly through the Learning Management System (LMS).
  • Contact hours provide an indication of the type and extent of in-class activities this unit may contain. The total amount of student work (including contact hours, assessment time, and self-study) will approximate 150 hours per 6 credit points.