| Type: | Postgraduate Subject |
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| Code: | DTSC71-304 |
| EFTSL: | 0.125 |
| Faculty: | Bond Business School |
| Semesters offered: |
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| Credit: | 10 |
| Study areas: |
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| Subject fees: |
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Description
Knowing how to understand, analyse and present data is a key to entry in any industry. This subject requires students to apply the concepts, theories and frameworks from their entire program to a big data research project. Working under the supervision of an academic staff member, students will apply the research process, develop a research question that is relevant to both industry and the academic community, synthesise the relevant literature, use appropriate big data techniques and interpret the results and evaluate their implications. Projects may be created internally or be sourced from industry.
Subject details
Learning outcomes
- Apply advanced knowledge from previous subjects n the discipline and industry insights to a real data analytics project.
- Critically analyse and synthesise the relevant literature on an approved advanced data analytics research topic.
- Design and undertake appropriate advanced data collection and analyses to investigate a research question.
- Demonstrate sophisticated and nuanced interpersonal skills and teamwork in completing the data analytics research project.
- Critically reflect on the experience of working as part of a team to solve a problem in data analysis.
Enrolment requirements
| Requisites: |
Pre-requisites:Co-requisites:There are no co-requisites |
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| Assumed knowledge: |
Assumed knowledge is the minimum level of knowledge of a subject area that students are assumed to have acquired through previous study. It is the responsibility of students to ensure they meet the assumed knowledge expectations of the subject. Students who do not possess this prior knowledge are strongly recommended against enrolling and do so at their own risk. No concessions will be made for students’ lack of prior knowledge.
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| Restrictions: |
This subject is not available to
This subject is not available as a general elective. To be eligible for enrolment, the subject must be specified in the students’ program structure. |
Subject outlines
- January 2025 [Standard - Applied Data Analytics Project]
- September 2024 [Standard - Applied Data Analytics Project]
- September 2023 [Standard - Applied Data Analytics Project]
- September 2022 [Standard - Applied Data Analytics Project]
- September 2021 [Standard - Applied Data Analytics Project]
- September 2020 [Standard - Advanced Big Data Projects]
- January 2020 [Standard - Advanced Big Data Projects]
Subject dates
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May 2024
Standard Offering Enrolment opens: 19/03/2024 Semester start: 13/05/2024 Subject start: 13/05/2024 Last enrolment: 26/05/2024 Teaching census: 07/06/2024 Withdraw - Financial: 08/06/2024 Withdraw - Academic: 29/06/2024 -
September 2024
Standard Offering Enrolment opens: 14/07/2024 Semester start: 09/09/2024 Subject start: 09/09/2024 Last enrolment: 22/09/2024 Teaching census: 04/10/2024 Withdraw - Financial: 05/10/2024 Withdraw - Academic: 26/10/2024
| Standard Offering | |
|---|---|
| Enrolment opens: | 19/03/2024 |
| Semester start: | 13/05/2024 |
| Subject start: | 13/05/2024 |
| Last enrolment: | 26/05/2024 |
| Teaching census: | 07/06/2024 |
| Withdraw - Financial: | 08/06/2024 |
| Withdraw - Academic: | 29/06/2024 |
| Standard Offering | |
|---|---|
| Enrolment opens: | 14/07/2024 |
| Semester start: | 09/09/2024 |
| Subject start: | 09/09/2024 |
| Last enrolment: | 22/09/2024 |
| Teaching census: | 04/10/2024 |
| Withdraw - Financial: | 05/10/2024 |
| Withdraw - Academic: | 26/10/2024 |