University Course Planner The University of Adelaide Australia

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

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

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Student Status


What type of place are you studying in

Commonwealth supported
Full fee paying

Study Level

Postgraduate Coursework
Non Award

Program of Study

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.


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.