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Data Science Research Project Pt2 (MAST90109)
Graduate courseworkPoints: 12.5Dual-Delivery (Parkville)
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About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Summer Term
Semester 1
Semester 2
Overview
Availability | Summer Term - Dual-Delivery Semester 1 - Dual-Delivery Semester 2 - Dual-Delivery |
---|---|
Fees | Look up fees |
In this subject, students undertake a substantial research program in the area of Data Science. The research will be conducted under the supervision of a member of the School of Mathematics and Statistics or the Computing and Information Systems academic staff. The results will be reported in the form of a thesis and an oral presentation.
Intended learning outcomes
After completing this subject students should have:
- discovered the challenge of research in Data Science;
- a deeper knowledge of in Data Science;
- completed a substantial piece of research; and
- a sound preparation for future research in Data Science.
Generic skills
Upon completion of this subject, students should gain the following generic skills:
- problem-solving skills including the ability to engage with unfamiliar problems, identify relevant solution strategies and conduct research;
- analytical skills through the ability to construct and express logical arguments and to work in abstract or general terms to increase the clarity and efficiency of analysis;
- presentation skills, both written and oral; and
- time management skills: the ability to meet regular deadlines while balancing competing commitments.
Last updated: 31 January 2024
Eligibility and requirements
Prerequisites
Students must have agreement from a supervisor.
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 31 January 2024
Assessment
Description | Timing | Percentage |
---|---|---|
A preliminary literature survey and research plan
| In the last week of teaching in Data Science Research Project pt1 | N/A |
Students will give a presentation on their research projects where they will be assessed on their presentation skills and their ability to communicate their research to a general audience in a concise manner
| During weeks 6-9 of the teaching period in Data Science Research Project pt2 | 10% |
A thesis is the main requirement. Theses are expected to be 30-40 pages in length, excluding references, appendices, figures, and tables. Two bound hard copies of the thesis are to be submitted, due in the last week of the teaching period in Data Science Research Project pt2
| After the full 25 points of enrolment in the Data Science Research Project component | 90% |
Additional details
The assessment requirements are applicable to the entire 25 point research project.
Last updated: 31 January 2024
Dates & times
- Summer Term
Coordinators Karim Seghouane and Michael Kirley Mode of delivery Dual-Delivery (Parkville) Contact hours This subject is an individual research project and weekly contact hours will vary depending on the nature of the project. The minimum contact hours will be weekly one hour (6 X 1 hour). Total time commitment 170 hours Teaching period 4 January 2022 to 4 February 2022 Last self-enrol date 7 January 2022 Census date 21 January 2022 Last date to withdraw without fail 4 February 2022 Assessment period ends 25 February 2022 Summer Term contact information
- Semester 1
Coordinators Michael Kirley and Karim Seghouane Mode of delivery Dual-Delivery (Parkville) Contact hours This subject is an individual research project and weekly contact hours will vary depending on the nature of the project. The minimum contact hours will be weekly one hour (12 X 1 hour). Total time commitment 170 hours Teaching period 28 February 2022 to 29 May 2022 Last self-enrol date 11 March 2022 Census date 31 March 2022 Last date to withdraw without fail 6 May 2022 Assessment period ends 24 June 2022 Semester 1 contact information
- Semester 2
Coordinators Michael Kirley and Karim Seghouane Mode of delivery Dual-Delivery (Parkville) Contact hours This subject is an individual research project and weekly contact hours will vary depending on the nature of the project. The minimum contact hours will be weekly one hour (12 X 1 hour). Total time commitment 170 hours Teaching period 25 July 2022 to 23 October 2022 Last self-enrol date 5 August 2022 Census date 31 August 2022 Last date to withdraw without fail 23 September 2022 Assessment period ends 18 November 2022 Semester 2 contact information
Time commitment details
170 hours
Last updated: 31 January 2024
Further information
- Texts
Prescribed texts
There are no specifically prescribed or recommended texts for this subject.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Data Science - Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 31 January 2024