Data Science Research Project Pt1 (MAST90108)
Graduate courseworkPoints: 12.5On Campus (Parkville)
About this subject
Contact information
Semester 1
Semester 2
Overview
| Availability | Semester 1 Semester 2 |
|---|---|
| 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: 3 November 2022
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: 3 November 2022
Assessment
Additional details
The assessment requirements are applicable to the entire 25 point research project.
- A preliminary literature survey and research plan (of 2 pages) due at the endo of week 8 of the Data Sciecne Research Project pt1 (hurdle)
- Students will give a 15 minute 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, due two weeks before end of the teaching period in Data Science Research Project pt2 (10%)
- A thesis is the main requirement due after the full 25 points of enrolment in the Data Science Research Project component, 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 last week of the teaching period in Data Science Research Project pt2 (90%)
Last updated: 3 November 2022
Dates & times
- Semester 1
Principal coordinator James Bailey Mode of delivery On Campus (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 26 February 2018 to 27 May 2018 Last self-enrol date 9 March 2018 Census date 31 March 2018 Last date to withdraw without fail 4 May 2018 Assessment period ends 22 June 2018 Semester 1 contact information
- Semester 2
Principal coordinator James Bailey Mode of delivery On Campus (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 23 July 2018 to 21 October 2018 Last self-enrol date 3 August 2018 Census date 31 August 2018 Last date to withdraw without fail 21 September 2018 Assessment period ends 16 November 2018 Semester 2 contact information
Time commitment details
170 hours
Last updated: 3 November 2022
Further information
- Texts
- Related Handbook entries
Last updated: 3 November 2022