Overview
Gain advanced knowledge in data science principles and applications, develop the ability to analyse complex data trends using statistics and specialised software, and apply your skills through an applied research project.
Key Facts
In today’s data-driven world, the ability to analyse and interpret vast amounts of information is essential for improving productivity, efficiency, and leadership.
The Applied Data Science programme from University of Canterbury provides advanced technical, analytical, and practical skills to help you thrive in this high-demand field. You'll develop expertise in data science principles, master software tools for tracking and describing data trends, and apply your knowledge to real-world challenges.
Programme Structure
Courses include:
- Data Science
- Computer Programming
- Data Management
- Scalable Data Science
- Big Data
Key information
Duration
- Full-time
- 18 months
- Part-time
- 36 months
Start dates & application deadlines
- StartingApplication deadline not specified.
- StartingApplication deadline not specified.
- StartingApplication deadline not specified.
Language
Prepare for Your English Test
AI-powered IELTS feedback. Clear, actionable, and tailored to boost your writing & speaking score. No credit card or upfront payment required.
- Trusted by 300k learners
- 98 accuracy using real exam data
- 4.9/5 student rating
Credits
Delivered
Campus Location
- Christchurch, New Zealand
Disciplines
Data Science & Big Data View 3 other Masters in Data Science & Big Data in New ZealandWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
Prepare for Your English Test
AI-powered IELTS feedback. Clear, actionable, and tailored to boost your writing & speaking score. No credit card or upfront payment required.
- Trusted by 300k learners
- 98 accuracy using real exam data
- 4.9/5 student rating
Other requirements
General requirements
- Qualified for a university degree in an area which is relevant to data science - e.g. biological sciences, computer science, digital humanities, economics, environmental science, finance, geography, geology, mathematics, physics, psychology, statistics, or any other relevant degree subject to approval of the Amo Matua, Pūtaiao | Executive Dean of Science or delegate; and
- Passed 90 points in relevant 300-level courses with at least a B Grade Point Average; and
- Been approved as a student for the degree by the Amo Matua, Pūtaiao | Executive Dean of Science or delegate; and
- Met any other prerequisites specified in the Regulations for the Master of Applied Data Science.
Tuition Fees
-
International Applies to you
Applies to youNon-residents5175 NZD / module≈ 5175 NZD / module -
Domestic Applies to you
Applies to youCitizens or residents1176 NZD / module≈ 1176 NZD / module
Additional Details
- Domestic learners
- International learners
Funding
In order for us to give you accurate scholarship information, we ask that you please confirm a few details and create an account with us.
Scholarships Information
Below you will find Master's scholarship opportunities for Applied Data Science.
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility