| Type: | Postgraduate Subject |
|---|---|
| Code: | DTSC71-200 |
| 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
Organisations use their data for decision support and to build data-intensive products and services. The collection of skills required by organisations to support these functions has been grouped under the term Data Science. This subject will articulate the expected output of data scientists and then equip students with the ability to deliver against these expectations. A particular focus will be given to the tools required to model, store, clean, manipulate, and ultimately extract information out of stored data.
Subject details
Learning outcomes
- Demonstrate proficiency in common and advanced statistical learning techniques using the R programming language.
- Demonstrate ability to access data from databases using SQL, APIs and traditional formats and categorise the usage of different data formats.
- Build data-driven statistical models to address data focused on common and complex business problems.
- Apply advanced data visualisation techniques to communicate solutions to management.
- Communicate technical solutions to technical and non-technical stakeholders in a professional, concise written report.
Enrolment requirements
| Requisites: |
Nil |
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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. Basic R programming (equivalent to the first part of DTSC71-100). Students without the assumed knowledge of R programming, are encouraged to take both subjects DTSC71-200 and DTSC71-100 together (in the same semester). |
| Restrictions: |
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Subject outlines
- January 2025 [Standard - Data Science]
- September 2024 [Standard - Data Science]
- January 2024 [Standard - Data Science]
- September 2023 [Standard - Data Science]
- January 2023 [Standard - Data Science]
- September 2022 [Standard - Data Science]
- January 2022 [Standard - Data Science]
- September 2021 [Standard - Data Science]
- January 2021 [Standard - Data Science]
- September 2020 [Standard - Data Science]
- January 2020 [Standard - Data Science]
Subject dates
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January 2024
Standard Offering Enrolment opens: 12/11/2023 Semester start: 15/01/2024 Subject start: 15/01/2024 Last enrolment: 28/01/2024 Teaching census: 09/02/2024 Withdraw - Financial: 10/02/2024 Withdraw - Academic: 02/03/2024 -
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 -
January 2025
Standard Offering Enrolment opens: 10/11/2024 Semester start: 20/01/2025 Subject start: 20/01/2025 Last enrolment: 02/02/2025 Teaching census: 14/02/2025 Withdraw - Financial: 15/02/2025 Withdraw - Academic: 08/03/2025
| Standard Offering | |
|---|---|
| Enrolment opens: | 12/11/2023 |
| Semester start: | 15/01/2024 |
| Subject start: | 15/01/2024 |
| Last enrolment: | 28/01/2024 |
| Teaching census: | 09/02/2024 |
| Withdraw - Financial: | 10/02/2024 |
| Withdraw - Academic: | 02/03/2024 |
| 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: | 10/11/2024 |
| Semester start: | 20/01/2025 |
| Subject start: | 20/01/2025 |
| Last enrolment: | 02/02/2025 |
| Teaching census: | 14/02/2025 |
| Withdraw - Financial: | 15/02/2025 |
| Withdraw - Academic: | 08/03/2025 |