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Overview

The School of Mathematics and Statistics (MathsStats) offers a number of Honours streams including in Quantitative Data Science. The Honours year introduces students to the investigative and research aspects of knowledge and consists of advanced lecture courses, an Honours thesis and seminar participation. Our Honours students are supervised in their … For more content click the Read More button below. Students who enrol in the Quantitative Data Science Honours Stream are expected to have completed the  Quantitative Data Science major in the Bachelor of Data Science and Decisions (program 3959), or one of the other majors in that program including at least three level 3 MATH courses. Students who have completed degrees in other cognate disciplines and who are completing a project within the usual concerns of data science may also apply for entry to this stream. Honours in Quantitative Data Science can be completed full-time or part-time. Most students commence their enrolment in term 1  but entry in term 3 is available subject to resources.  Students should check the MathStats Honours webpages for application procedures and enrolment deadlines.  Stream structure The thesis component of Quantitative Data Science honours requires a student to undertake an 18uoc thesis by enrolling in the course MATH4001 (Mathematics and Statistics Honours Thesis) in each of three successive terms. These courses form one thesis/project. Students (full or part-time) can complete the honours thesis  in any three consecutive terms of their honours enrolment. Students will also be required to participate in the weekly honours seminar, which will be timetabled as a joint class in the thesis courses. This seminar is intended to allow students to practise their final honours seminar presentation, listen to presentations of other honours students and engage in other honours training activities. Students should also attend any appropriate seminars in their thesis area.  The thesis will be assessed by at least two academic staff. The supervisor or supervisors of the thesis is expected to submit a report, but will not be a marker for the thesis. Students are required to give a short seminar on their thesis and this will account for 10% of the final mark for the thesis, the remaining 90% coming from the written thesis report. The 30uoc coursework component of Quantitative Data Science Honours will consist of five 6uoc lecture courses selected from the list below, or others, including at least 18UoC of MATH courses, taken with the approval by the Head of School or nominee and the advice of the honours thesis supervisor.

Learning Outcomes

1.
Plan and execute a piece of research or a professional project in Quantitative Data Science with some independence.
  • Professionals
2.
Demonstrate an understanding of international perspectives relevant to Data Science.
  • Leaders
  • Global citizens
3.
Reflect critically on existing theoretical knowledge, ideas and practice in Quantitative Data Science to address the research topic.
  • Scholars
  • Professionals
4.
Communicate their research ideas to a suitable audience.
  • Leaders
  • Global citizens
5.
Demonstrate an understanding of specialised knowledge within a systematic and coherent body of knowledge, including established theories relevant to Data Science as a discipline and professional field.
  • Professionals
  • Scholars

Graduate Capabilities

For more information on Graduate Capabilities please click on this link

Available in Program(s)
Single degree program(s) in which this specialisation is available:

Bachelor of Science (Honours) - BSc(Hons)4500 - Science (Honours)

Specialisation Structure

Students must complete 48 UOC.

Thesis Course18 Units of Credit:

Prescribed Electives 1

Prescribed Electives 2

Quantitative Data Science

Enrolment Disclaimer

Please note that this Handbook is a comprehensive catalogue of our offerings and includes courses that can be taken to satisfy program requirements irrespective as to their availability for a particular year. Availability of courses is best checked using filters on this site or on the class timetable site.

You are responsible for ensuring that you enrol in courses according to your program requirements and by following the advice of your Program Authority. myUNSW enrolment checks that you have met enrolment requirements such as pre-requisites for individual courses but not that you are enrolling in courses that will count towards your program requirements.

Additional Information

Entry Requirements

So that students have sufficient background to attempt the courses in the honours year, students must discuss their selection of Level III courses with the Mathematics Honours Coordinator or another academic adviser.

To enter honours in Quantitative Data Science, students must have

  • Completed the Bachelor of Data Science and Decisions program (any stream) but including at least 18uoc in level III MATH or DATA courses or;
  • Completed a suitable quantitatively based data science bachelors degree at any other university or
  • Completed a bachelors degree which includes at least three level III, or higher level, courses in mathematics or statistics, and at least two level III, or higher level, courses in computer science and/or business that are listed as electives in program 3959

In addition, students will normally be required to have an average above 70 in their level III MATH courses 

With the permission of the Head of School (or nominee), a student may be allowed into Quantitative Data Science Honours without having satisfied the specific requirements, and instead have shown some evidence of the ability to undertake independent study.

Final Mark

The marks for the thesis and other honours courses will be combined to give a weighted average mark forming a final honours mark which will be rounded up and used to decide the grade of honours the student will be awarded as follows:

  • Honours class 1 -- final mark of 85 or over
  • Honours class 2, Division 1 -- final mark from 75 to 84
  • Honours class 2, Division 2 -- final mark from 65 to 74
  • Honours class 3 -- final mark from 50 to 64

Pathways

Students who successfully complete Quantitative Data Science Honours are qualified to continue further in their research careers by applying to undertake postgraduate studies by PhD or Masters. Students with successful honours are qualified to enrol in a PhD program at UNSW. Students achieving a high Honours Grade (Class 1 or 2.1) may apply for an Australian Postgraduate Award (APA) PhD scholarship to support such studies. Further information can be obtained from MathsStats postgraduate studies webpages:

http://www.maths.unsw.edu.au/futurestudents/postgraduate-coursework

http://www.maths.unsw.edu.au/futurestudents/postgraduate-research

Graduates of a Quantitative Data Science honours plan are also well qualified to find employment in many sectors. Past honours graduates in mathematics and statistics have found employment in areas such as banking, computing, education, finance, government, medical research and meteorology. The Australian Mathematical Society  and Australian Mathematical Sciences Institute to maintain up-to-date information on career prospects in mathematics and statistics.

Pre-2019 Handbook Editions

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Pre-2019 Handbook Editions