The Otago Business School's Master of Business Data Science degree recognises the global demand for qualified Data Scientists.
Key information about the Master of Business Data Science (MBusDataSc):
- 12 month duration
- Taught on campus and through distance learning
- Seven taught papers + either an applied or research project paper
- Applicants normally require a B+ average (at 300 level) in an appropriate undergraduate degree
- In considering an applicant’s undergraduate qualification, regard will be given to the course of study followed to gain that qualification, as well as the applicant’s performance
- Applicants with relevant practical experience may also be considered
- MBusDataSc brochure (PDF)
Regulations and online application for the MBusDataSc
Learn about the Regulations for the Master of Business Data Science and application details on the University of Otago website.
There is an enormous and increasing amount of data that is collected. Examples include not just traditional data such as sales transactions, but location data (GPS), interactions between people on social network, measurements of sleep patterns, medication being taken, state of health, and much much more.
A key challenge is then to make use of this wealth of data. How can we manage this data, and analyse it to exploit useful information that can guide decision making?
This emerging area goes under the name “Data Science”. There is growing demand for people, “Data Scientists”, who have the skills to manage and analyse enormous amounts of data using a range of techniques such as data mining, statistical techniques, and machine learning.
Data Scientist has been called the “Sexiest job of the 21st century”, and the unique combination of technical skills (stats, data management) and business understanding has been said to make Data Scientists “highly sought after and highly paid”.
The MBusDataSc primary focus is to equip you to become a practitioner, allowing you to meet the needs of industry, and solve the data problems of the world. However, there will also be an alternative path that will focus on preparing students for research in the area (e.g. going on to do a masters by research or PhD).
The proposed degree is inherently multidisciplinary, featuring Information Science and Marketing, which gives the degree a strong business focus; as well as contributions from Computer Science and from Statistics.
Once you have completed the MBusDataSc you will have developed an advanced knowledge of data science. You will understand how data analysis can be used in business, including being able to identify opportunities to use data, be aware of ethical and privacy issues and possible mitigations, and be able to select appropriate means of presenting the results of analysis. You will be able to select and apply techniques to manage and analyse large collections of data.
The 180 point programme of study shall consist of eight compulsory papers. Papers are either taught in semester one, semester two or are full-year papers.
You must complete:
- BSNS 401 – The Environment of Business & Economics
- COSC 430 – Advanced Database Topics
- INFO 408 – Management of large scale data
- INFO 411 – Machine Learning and Data Mining
- INFO 420 – Statistical Techniques for Data Science
- INFO 424 – Adaptive Business Intelligence
- MART 448 – Advanced Business Analytics
Including one of the following project papers
Papers within the MBusDataSc will be taught using a mixture of lectures, lab classes, and tutorials, as specified below. In all papers, teaching and learning is done not just through contact time, but also through non-contact time, including a range of assessments.
- COSC 430 – Lectures and lab-based tutorials
- INFO 408 – Mixture of in-class discussion and lab class work
- INFO 411 – Lectures and lab classes
- INFO 420 – Lectures and tutorials
- INFO 424 – Lectures and tutorials
- MART 448 – Lectures and lab classes
- BSNS 401 – Lectures and tutorials, seminars and group work
- INFO 501 – Applied project requiring supervision and also group classes
- INFO 580 – Research project requiring supervision and also group classes
For further information about the MBusDataSc please contact the programme coordinator: