Qualification Overview

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Qualification Title Master of Data Science
Qualification Type Masters Degree
Level 9
Credits 240
Subject Area
  • Information Technology » Computer Science » Computer Science not elsewhere classified
Strategic Purpose Statement
The Master of Data Science (MDataSc, 240 points) is a taught Masters programme. Graduates will have an advanced knowledge of techniques of data science including machine learning and statistical methods, and their uses in the world of big data. They will be able to analyse critically the data requirements and sources relevant in several areas of application from the sciences, humanities, social sciences, business or government. They will also have experience of undertaking supervised research, consultancy and data analysis in the workplace. Some graduates will be able to proceed to doctoral studies in Data Science or its uses. Graduates will be prepared to take a leadership role in data-related positions in the workforce.
Graduate profile
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Education pathways
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Entry Requirements
A bachelor's degree with a major in Data Science, Computer Science or Statistics, with an average grade of B+ or better in courses in those subjects. Candidates with a major in Data Science or a double major in Computer Science and Statistics may be exempted Part 1 (60 points).
Education Organisation Victoria University of Wellington
Developed By Victoria University of Wellington
Quality Assured By Committee on University Academic Programmes
Number VI004O
Status Current
Created 2020-09-07 15:50:21.183
Content
The MDataSc comprises Part 1 (60 points) and Part 2 (180 points). Part 1 courses address fundamental techniques of Data Science, statistical methods and machine learning. Part 2 includes a compulsory core of statistical methods and computational techniques; a research component of a research preparation course and an individual research project; a workplace practicum giving students real world experience where they can apply their skills. Students complete the degree with a set of elective courses drawn from statistics, computer science and mathematics, and from suitable data rich advanced courses in other disciplines.

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Credits

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Strategic Purpose Statement

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Education pathways

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