Data Science
You’ll develop the cultural awareness and critical thinking skills you need to analyze and produce a broad range of discourse in a full spectrum of careers — and to make a difference in whatever you do.
- 2 Years / Onsite
- Intakes: Jan, Apr, Jun, Oct
Overview
Data Science at Auckland Royal Academy prepares students to extract meaningful insights from large, complex datasets and translate those insights into decisions that drive real-world impact. The programme covers statistical modelling, machine learning, data visualisation, and programming with Python and R, giving graduates the technical foundation needed across industries from healthcare to finance, logistics, and government.
In the classroom, you will tackle authentic datasets sourced from New Zealand organisations and global repositories, working in teams to clean, analyse, and visualise information. Courses are taught by research-active academics and industry data scientists who introduce you to the full analytics pipeline — from problem definition and data collection through to model deployment and stakeholder communication.
Career Opportunities
Data Science graduates from Auckland Royal Academy are sought after by technology companies, banks, health authorities, government agencies, and consultancies throughout the region. Career pathways include data analyst, machine learning engineer, business intelligence specialist, quantitative researcher, and chief data officer roles across New Zealand, Australia, and the broader Asia-Pacific market.
Program Learning Outcomes
Apply machine learning algorithms, statistical inference techniques, and data visualisation tools to analyse complex datasets and generate actionable insights for organisational decision-making.
Design and implement end-to-end data pipelines using Python, R, and cloud-based platforms, demonstrating proficiency in data wrangling, feature engineering, and model evaluation.
Evaluate the ethical implications of data-driven systems, including issues of algorithmic bias, privacy, and transparency, ensuring responsible use of data science in professional practice.
Programme
| Semester 1 | Credits | Number |
|---|---|---|
| Statistics for Data Science | 4 | STAT 101 |
| Programming with Python | 4 | COMP 101 |
| Mathematics for Data Science | 4 | MATH 101 |
| Semester 2 | Credits | Number |
|---|---|---|
| Statistical Modelling | 4 | STAT 201 |
| Machine Learning Fundamentals | 4 | DSCI 210 |
| Data Visualisation | 3 | DSCI 220 |
| Semester 3 | Credits | Number |
|---|---|---|
| Big Data Technologies | 4 | DSCI 301 |
| Deep Learning | 4 | DSCI 310 |
| Data Ethics & Governance NZ | 3 | DSCI 320 |
| Semester 4 | Credits | Number |
|---|---|---|
| Predictive Analytics | 4 | DSCI 401 |
| Natural Language Processing | 3 | DSCI 410 |
| Data Science Capstone Project | 4 | DSCI 490 |
| Total for the entire period of study | 11 |
Contact us
3/60 Federal Street, Auckland CBD, Auckland 1010, New Zealand
How to Apply?
- You Apply
Tell us a little about yourself and we’ll help with the rest. Our convenient online application tool only takes 10 minutes to complete.
- We Connect
After you submit your application, an admissions representative will contact you and will help you to complete the process.
- You Get Ready
Once you’ve completed your application and connected with an admissions representative, you’re ready to create your schedule.