CITS4009 Computational Data Analysis

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

Supplementary assessment is not available in this unit except in the case of a bachelor's pass degree student who has obtained a mark of 45 to 49 overall and is currently enrolled in this unit, and it is the only remaining unit that the student must pass in order to complete their course.
Unit Coordinator(s)
Dr Wei Liu
Unit rules
Prerequisites:
enrolment in the Master of Data Science
or
Master of Information Technology
or
Master of Professional Engineering (Chemical Engineering specialsiation
or
Mining Engineering specialisation
or
Software Engineering specialisation)
or
Master of Renewable and Future Energy
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.

  • 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.
  • Books and other material wherever listed may be subject to change. Book lists relating to 'Preliminary reading', 'Recommended reading' and 'Textbooks' are, in most cases, available at the University Co-operative Bookshop (from early January) and appropriate administrative offices for students to consult. Where texts are listed in the unit description above, an asterisk (*) indicates that the book is available in paperback.