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Study Data Science at Otago

The science of learning from data.

Data is at the core of modern society. We are producing it, collecting it, wrangling it, analysing it, modelling it, understanding it, visualising it, using it on a scale that seemed impossible not so long ago.

Data Science is fundamentally about how we can learn from data and how we can meaningfully use it to improve our world. Studying Data Science leads to opportunities in fields as diverse as banking and biotechnology, entertainment and education, gaming and government, medicine and manufacturing, retail and research.

Data Science is also a broad area of study. At Otago, the Data Science programme pulls together the best that computer science, information science, and statistics have to offer while stressing application and understanding of the impact of Data Science on society.

Information on this page is about Data Science as a major for undergraduate science degrees, and as an endorsement for the Diploma for Graduates. The University of Otago also offers the Master of Business Data Science, a one-year postgraduate degree with a strong business focus:

Master of Business Data Science (MBusDataSc)

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Why study Data Science?

Data is everywhere and the demand for data scientists is exploding. Data Science is a broad field but it essentially boils down to extracting information from large and complex data sets. Working as a data scientist for an organisation means you will be at the heart of decision-making processes.

Data Science brings together techniques and methods from computer science, information science, and statistics. This means there are opportunities in areas that particularly interest you, whether it is efficient computation, data storage infrastructure, data analysis or applied machine learning. In addition to problem-solving skills that can be applied to many areas, you will gain valuable communication and data visualisation skills.

Career opportunities

There are opportunities for Data Science graduates at all levels of business, industry, government, and science.

Data Science at Otago

What will I learn?

Data Science brings together techniques and methods from computer science, information science, and statistics to extract insight from large and complex data sets, and to communicate this acquired knowledge through effective modelling and visualisation.

You will learn how to acquire, handle and analyse data to solve problems in a wide variety of areas. You will also learn to think critically and ethically about the increasing role Data Science plays in society.

How will I learn?

The programme is delivered using lectures, tutorials, and practical labs. Assessment is a combination of assignments, projects, presentations, and exams. There will be opportunities to work in groups.

Background required

Entry into the BSc (BSc) in Data Science is open to anyone, however taking Digital Technology for NCEA is useful and NCEA Level 3 Mathematics and Statistics is helpful.

Requirements

STAT papers

Paper Code Year Title Points Teaching period
STAT110 2025 Statistical Methods 18 Semester 1, Summer School
STAT115 2025 Introduction to Biostatistics 18 Semester 2
STAT210 2025 Applied Statistics 18 Semester 1
STAT260 2025 Visualisation and Modelling in R 18 Semester 2
STAT270 2025 Probability and Inference 18 Semester 1
STAT310 2025 Statistical Modelling 18 Semester 1
STAT311 2025 Design of Research Studies 18 Semester 1
STAT312 2025 Modelling High Dimensional Data 18 Semester 2
STAT370 2025 Statistical Inference 18 Semester 2
STAT371 2025 Bayesian Data Analysis 18 Semester 2
STAT372 2025 Stochastic Modelling 18 Semester 1
STAT399 2025 Special Topic 18 Not offered in 2025
STAT401 2025 Applied Statistical Methods and Models 20 Semester 1
STAT402 2025 Regression Models for Complex Data 20 Semester 2
STAT403 2025 Case Studies in Statistics 20 Semester 2
STAT404 2025 Advanced Statistical Inference 20 Semester 1
STAT405 2025 Probability and Random Processes 20 Semester 1
STAT423 2025 Bayesian Modelling 20 Semester 2
STAT424 2025 Research Design and Methods 20 Semester 1
STAT425 2025 Statistical Learning 20 Semester 2
STAT435 2025 Data Analysis for Bioinformatics 20 Semester 1
STAT441 2025 Topic in Advanced Statistics 20 Semester 2
STAT442 2025 Topic in Advanced Statistics 20 Not offered in 2025
STAT490 2025 Dissertation 40 Full Year
STAT498 2025 Special Topic 20 Not offered in 2025
STAT499 2025 Special Topic: Clinical Trials 20 Not offered in 2025

INFO papers

Paper Code Year Title Points Teaching period
INFO130 2025 Fundamentals and practice of spreadsheets 18 Semester 1, 1st Non standard period
INFO203 2025 Human-Computer Interaction and User Experience 18 Semester 1
INFO204 2025 Introduction to Data Science 18 Semester 2
INFO250 2025 Special Topic 18 Not offered, expected to be offered in 2026
INFO302 2025 Information Systems Strategy and Governance 18 Semester 1
INFO304 2025 Advanced Data Science 18 Semester 2
INFO305 2025 Advanced Human-Computer Interaction and Interactive Systems 18 Not offered in 2025
INFO310 2025 Software Project Management 18 Semester 1
INFO350 2025 Topics in Information Science 18 Semester 1, Semester 2
INFO351 2025 Special Topic: Virtual and Augmented Reality 18 Not offered in 2025
INFO352 2025 Special Topic: Pervasive Game Development 18 Not offered in 2025
INFO353 2025 Special Topic 18 Not offered in 2025
INFO390 2025 Research Topics 18 Not offered in 2025
INFO407 2025 Agent-based Software Technologies 20 Semester 2
INFO408 2025 Management of Large-Scale Data 20 Semester 1
INFO410 2025 Interactive and Immersive Systems 20 Not offered in 2025
INFO411 2025 Machine Learning and Data Mining 20 Semester 2
INFO420 2025 Statistical Techniques for Data Science 20 Semester 2
INFO424 2025 Adaptive Business Intelligence 20 Semester 1
INFO451 2025 Special Topic 20 Not offered in 2025
INFO452 2025 Special Topic 20 Not offered in 2025
INFO470 2025 Advanced Topics in Information Science 20 Semester 1, Semester 2
INFO490 2025 Dissertation 40 Full Year
INFO501 2025 Applied Project 40 1st Non standard period, 2nd Non standard period
INFO580 2025 Research Project 40 1st Non standard period, 2nd Non standard period, 3rd Non standard period

COSC papers

Paper Code Year Title Points Teaching period
COSC201 2025 Algorithms and Data Structures 18 Semester 1
COSC202 2025 Software Development 18 Semester 1
COSC203 2025 Web, Databases, and Networks 18 Semester 2
COSC204 2025 Computer Systems 18 Semester 2
COSC301 2025 Network Management and Security 18 Semester 1
COSC312 2025 Cryptography and Security 18 Semester 2
COSC326 2025 Computational Problem Solving 18 Semester 1
COSC341 2025 Theory of Computing 18 Semester 2
COSC342 2025 Visual Computing: Graphics & Vision 18 Semester 1
COSC343 2025 Artificial Intelligence 18 Semester 2
COSC344 2025 Database Theory and Applications 18 Semester 1
COSC345 2025 Software Engineering 18 Semester 2
COSC349 2025 Cloud Computing Architecture 18 Semester 2
COSC360 2025 Computer Game Design 18 Summer School
COSC385 2025 Research Project 18 Full Year
COSC402 2025 Advanced Computer Networks 20 Semester 2
COSC412 2025 Advanced Cryptography and Security 20 Semester 2
COSC420 2025 Deep Learning 20 Semester 1
COSC431 2025 Information Retrieval 20 Semester 1
COSC440 2025 Advanced Operating Systems 20 Semester 2
COSC444 2025 Advanced Database Technologies 20 Semester 1
COSC450 2025 Computer Vision and Graphics 20 Semester 1
COSC470 2025 Special Topic: Machine Learning 20 Not offered in 2025
COSC471 2025 Approved Special Paper 20 Not offered in 2025
COSC480 2025 Applied Project 40 Full Year
COSC490 2025 Dissertation 40 Full Year

COMP papers

Paper Code Year Title Points Teaching period
COMP101 2025 Foundations of Information Systems 18 Semester 2, Summer School
COMP111 2025 Information and Communications Technology 18 Not offered in 2025
COMP120 2025 Practical Data Science 18 Semester 1, Semester 2
COMP151 2025 Programming for Scientists 18 Semester 1
COMP161 2025 Computer Programming 18 Semester 1, Semester 2, 1st Non standard period
COMP162 2025 Foundations of Computer Science 18 Semester 2, Summer School
COMP210 2025 Information Assurance 18 Semester 2
COMP270 2025 ICT Fundamentals 15 Not offered in 2025
COMP371 2025 ICT Studio 1 15 Not offered in 2025
COMP372 2025 ICT Studio 2 15 Not offered in 2025
COMP373 2025 ICT Studio 3 15 Not offered in 2025
COMP390 2025 ICT Industry Project 30 Not offered in 2025

More information

Contact us

Matthew Parry
Department of Mathematics and Statistics
Tel +64 3 479 7780
Email matthew.parry@otago.ac.nz

Grant Dick
Department of Information Science
Tel +64 3 479 8180
Email grant.dick@otago.ac.nz

Brendan McCane
Department of Computer Science
Tel +64 3 479 8588
Email brendan.mccane@otago.ac.nz

Studying at Otago

This information must be read subject to the statement on our Copyright & Disclaimer page.

Regulations on this page are taken from the 2024 Calendar and supplementary material.

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