CITS5553 Data Science Capstone Project

Credit
6 points
Offering
(see Timetable)

If this unit does not have an online alternative, then students who are presently unable to enter Western Australia and whose studies would be delayed by an inability to complete this unit, should contact the unit coordinator (details given on this page) to ascertain, on an individual case-by-case basis, if alternate arrangements can be made to support their study in this unit.

AvailabilityLocationMode
Semester 2UWA (Perth)Face to face Predominantly face-to-face. On campus attendance required to complete this unit. May have accompanying resources online.
Content
This unit provides a capstone experience where students integrate and apply knowledge and skills acquired in earlier units to a substantial real-world information technology project. Students work in teams of typically four to six members, supervised by an academic and/or industry mentor. Each team is responsible for managing their project through group meetings and mentor/client meetings, submitting group deliverables against milestones, preparing the necessary design documentation, and choosing and following appropriate software processes. Individuals are expected to perform professionally in a team-based environment and reflect on their contributions to the team. A number of lectures are given to teach communication skills, principles of project management and the fundamental ethical and social principles involved in large-scale data science projects. The academic objectives of this unit are to lead students through a sizeable team-based effort to go through design, synthesis, development and deployment, the full data science practice life cycle, to better prepare them as professional data scientists.
Outcomes
Students are able to (1) assess the scope, dimensions, scale of effort and indicative costs of a complex data science project; (2) analyse data by carrying out exploratory data analysis; (3) build predictive or other suitable computational models for data-driven business decision making; (4) evaluate model performance against a set of standard metrics recognised by the data science community; (5) interpret model results meaningfully for effective communication with all stakeholders via written, oral and visual means; and (6) perform professionally as an individual and as part of a multidisciplinary and multicultural team.
Assessment
Indicative assessments in this unit are as follows: (1) individual essay; (2) group project deliverable; and (3) individual project assessment. Further information is available in the unit outline.

Supplementary assessment is not available in this unit.
Unit Coordinator(s)
Professor Eun-Jung Holden
Unit rules
Prerequisites:
62530 Master of Data Science
and
completion of 24 points of Level 4/Level 5 units
Contact hours
lectures: 10 hours; project mentor sessions: 4 hours; project: 60 hours
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  • Unit readings, including any essential textbooks, are listed in the unit outline for each unit, one week prior the commencement of study. The unit outline will be available via the LMS and the UWA Handbook one week prior the commencement of study. Reading lists and essential textbooks are subject to change each semester. Information on essential textbooks will also be made available on the Essential Textbooks. This website is updated regularly in the lead up to semester so content may change. It is recommended that students purchase essential textbooks for convenience due to the frequency with which they will be required during the unit. A limited number of textbooks will be made available from the Library in print and will also be made available online wherever possible. Essential textbooks can be purchased from the commercial vendors to secure the best deal. The Student Guild can provide assistance on where to purchase books if required. Books can be purchased second hand at the Guild Secondhand bookshop (second floor, Guild Village), which is located on campus.