COMP SCI 7209 - Big Data Analysis and Project
Career: | Postgraduate Coursework |
---|---|
Units: | 3 |
Term: | Trimester 2 |
Campus: | North Terrace |
Contact: | Up to 2 hours per week |
Restriction: | Master of Data Science, Master of Cyber Security (and nested programs), and Master of Artificial Intelligence and Machine Learning students only |
Available for Study Abroad and Exchange: | No |
Available for Non-Award Study: | No |
Assumed Knowledge: | Basic Python knowledge and skills |
Assessment: | Project report and presentation, assessments and quizzes |
Syllabus: |
The purpose of this course is to help you further develop your data science skills and knowledge, as well as demonstrate autonomy, initiative and accountability by completing a medium-scale data science project using real-world datasets. This project will entail assessing, selecting and applying relevant data science techniques, principles and theory to a data science problem. You will consider the nature of your data and identify any social or ethical concerns, as well as appropriate ethical frameworks for data management. As part of this learning experience, you will develop, hone and demonstrate your professional communicative competence. |
Course Fees
Study Abroad student tuition fees are available here
Only some Postgraduate Coursework programs are available as Commonwealth Supported. Please check your program for specific fee information.
EFTSL | |||
---|---|---|---|
0.125 |
![]() |
![]() |
Course Outline
A Course Outline which includes Learning Outcomes, Learning Resources, Learning & Teaching for this course may be accessed here
![]() |
![]() |
Critical Dates
Term | Last Day to Add Online | Census Date | Last Day to WNF | Last Day to WF |
---|---|---|---|---|
Trimester 2 | Mon 05/06/2023 | Thu 08/06/2023 | Fri 21/07/2023 | Wed 16/08/2023 |
![]() |
![]() |
Class Details
Enrolment Class: Workshop | |||||||
---|---|---|---|---|---|---|---|
Class Nbr | Section | Size | Available | Dates | Days | Time | Location |
33068 | WR01 | 80 | 7 | 22 May - 14 Aug | Monday | 5pm - 7pm | Schulz, 307, Teaching Room | Note: This class will be delivered both online and face to face. Please refer to MyUni for details once enrolled. |
![]() |
![]() |