Unit details

CITS4009 Computational Data Analysis

Credit

6 points

Offering
(see Timetable)

Availability	Location	Mode
Semester 2	UWA (Perth)	Face to face
Semester 2	Online	Online timetabled

Content

This unit answers an urgent call to harness the unprecedented amount of data now generated from every facet of our daily
life by introducing data science as the discipline dealing with collecting, representing, manipulating and visualising data in
contemporary society. Students taking the unit learn to write computer programs to extract, transform and integrate data
from multiple heterogeneous sources, including traditional relational databases and web-based resources. Different data
representation formats such as XML, JSON and HDF5, as well as storage options including SQL and NOSQL type of
databases, are introduced and compared. Another core objective is the development of programming skills to enable
effective and meaningful visualisation of the data. Students are given the opportunity to put the learned knowledge
in data acquisition, data processing, data representation and exploratory visualisation into practice through projects that are
highly relevant to real-world data analytics. The unit provides the fundamental knowledge, introduces the essential
processes for exploratory data analysis and builds the specific critical programming skills required during the journey of growing a student into a capable data scientist.

Outcomes

Students are able to (1) write programs to systematically collect, process and integrate data of different types and from different sources.; (2) select appropriate data visualisation options; (3) demonstrate programming abilities to build solutions for exploratory data analysis using visualisation and clustering techniques; (4) critically assess the outcomes of a data analysis; and (5) communicate effectively with stakeholders.

Assessment

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

For units commencing in May 2022 or later the availability of the supplementary assessment is subject to confirmation.

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

Except where supplementary assessment is not available in a unit, it will be offered to students in all units who:

• Are in good academic standing overall;
• Have passed over half the units taken in the teaching period concerned, except where they are only enrolled in two or less units in the period;
• Have submitted all assessment items in the unit;
• Have achieved a mark between 45 and 49 for the unit overall, or the same mark in any failed component item in the unit; and
• No finding of academic misconduct has been made against them in the unit concerned.

Additionally student may apply for supplementary assessment in any unit which is the final unit required for graduation in there course and where they have achieved a mark between 45 and 49 for the unit overall, or the same mark in any failed component item in the unit.

Unit Coordinator(s)

Dr Du Huynh

Unit rules

Prerequisites:

Enrolment in in the ( 62510 Master of Information Technology or the 62530 Master of Data Science or the 62560 Master of Renewable and Future Energy or the 63550 Master of Engineering ) or ( the 62550 Master of Professional Engineering and the SP-ECHEM Chemical Engineering specialisation or the SP-EMINI Mining Engineering specialisation or the SP-ESOFT Software Engineering specialisation ) or ( the 72530 Master of Environmental Science and the SP-SSDSC Sensing and Spatial Data Science specialisation ) or ( BH011 Bachelor of Engineering [Honours] and the MJD-ECHEM Chemical Engineering major )

Co-requisites:

Nil

Incompatibility:

Nil

Contact hours

lectures: 2 hours per week; labs: 2 hours per week

Texts

To be advised by the School of Computer Science and Software Engineering.