Applied Data Science
Data Science is one of the fastest growing areas in science. There is a worldwide skills shortage of talented people with data science skills so if you are thinking about life after UC, this could be a good option for you.
Data Science has been described as the bridge linking large data sets (often called Big Data) with computational capacity to provide solutions for business, industry, other areas of science, health, and many more.
In this postgraduate programme you will develop your understanding of what Data Science is, learn new skills, and develop your communication and ability to work in a team. Effective communication and team work are listed as key attributes for a Data Scientist.
Potential students can come from a variety of undergraduate backgrounds. Students require a B Grade Point Average in 300-level bachelor's degree courses, or have evidence of achievement at postgraduate level.
If English is your additional language, you are also required to meet UC's English language requirements.
You will be required to enrol in all these foundational courses unless there is evidence of prior learning in the fundamentals of data science (exemptions must be approved by the Programme Director).
Group A: Advanced Data Science competencies
All students take the following courses (unless the Programme Director approves a substitution):
- DATA 420 Scalable Computing
- DIGI 405 Texts, Discourses and Data: the Humanities and Data Science
- STAT 462 Data Mining
- STAT 448 Big Data
Group B: Domain specific competencies
The remaining courses will be any relevant 400 or 600-level courses in: Biological Sciences, Computer Science, Data Science, Digital Humanities, Economics, Environmental Science, Finance, Geography, Geology, Mathematics, Physics, Psychology, Statistics. Or in any other relevant subject as approved by the Programme Director and the relevant Head of Department.
Some examples of courses students have enrolled in recently include:
- COSC 421 Advanced Topics in Security
- COSC 424 Secure Software
- COSC 428 Computer Vision
- DATA 415 Computational Social Choice
- DATA 416 Contemporary Issues in Data Science
- DATA 417 The Trustworthy Data Scientist
- DATA 419 Online Communities and Social Networks
- DATA 422 Data Wrangling
- DATA 423 Data Science in Industry
- DATA 430 Medical Data Informatics
- DATA 473 Special Topic: Foundations of Deep Learning
- DATA 475 Special Topic: Mixed Reality
- DATA 476 Special Topic: Information is Beautiful
- BIOL 459 Genomics
- HLTH 462 Quantitative Health Methods
- INFO 620 Information Systems Management
- INFO 634 Data Analytics and Business Intelligence
- POLS 443 Science, Technology and Environmental Policy
- STAT 446 Generalised Linear Models
- STAT 447 Official Statistics
- STAT 450 Advanced Statistical Modelling
- STAT 455 Data Collection and Sampling Methods
- STAT 456 Time Series and Stochastic Processes
- STAT 463 Multivariate Statistical Methods
Master of Applied Data Science capstone project course
This compulsory project for the Master's programme involves working in a team to solve real-world data science problems.
According to industry experts, data scientists know what the technology can offer, what analytics are possible, and can communicate on all those aspects to the wider business. This applies no matter the field or sector, as data and analytics have become so important and integral to organisational decision making. Graduates will be ready to work in a range of industries including: government, corporates, the IT sector, market research and finance, agriculture, and transport.
Aotearoa New Zealand and other countries are currently experiencing a skills shortage in this area, and the need for data-savvy professionals with applied experience is growing.
An Applied Data Science graduate's skills will include:
- advanced knowledge in data science
- the ability to use data to inform workplace solutions
- planning and implementing data-informed projects
- working in multidisciplinary teams
- an understanding of what programming can offer
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