Useful links
The focus of this unit is on understanding and applying relevant concepts, techniques, algorithms, and tools for the analysis, management and visualisation of data- with the goal of enabling discovery of information and knowledge to guide effective decision making and to gain new insights from large data sets. To this end, this unit of study provides a broad introduction to data management, analysis, modelling and visualisation using the Python programming language. Development of custom software using the powerful, general-purpose Python scripting language; Data collection, cleaning, pre-processing, and storage using various databases; Exploratory data analysis to understand and profile complex data sets; Mining unlabelled data to identify relationships, patterns, and trends; Machine learning from labelled data to predict into the future; Communicate findings to varied audiences, including effective data visualisations. Core data science content will be taught in normal lecture + tutorial delivery mode. Python programming will be taught through an online learning platform in addition to the weekly face-to-face lecture/tutorials. The unit of study will include hands-on exercises covering the range of data science skills above.
Code | COMP5310 |
---|---|
Academic unit | Computer Science |
Credit points | 6 |
Prerequisites:
?
|
None |
---|---|
Corequisites:
?
|
None |
Prohibitions:
?
|
INFO3406 OR OCMP5310 |
Assumed knowledge:
?
|
Good understanding of relational data model and database technologies as covered in ISYS2120 or COMP9120 (or equivalent UoS from different institutions) |
At the completion of this unit, you should be able to:
Unit outlines will be available 2 weeks before the first day of teaching for the relevant session.
Key dates through the academic year, including teaching periods, census, payment deadlines and exams.
Enrolment, course planning, fees, graduation, support services, student IT
Code of Conduct for Students, Conditions of Enrollment, University Privacy Statement, Academic Integrity
Academic appeals process, special consideration, rules and guidelines, advice and support
Policy register, policy search
Scholarships, interest free loans, bursaries, money management
Learning Centre, faculty and school programs, Library, online resources
Student Centre, counselling & psychological services, University Health Service, general health and wellbeing