Data Science – Bachelor of Information Sciences

This degree will enable you to become a hi-tech data specialist with the relevant skills to take you to the forefront of this fast-paced industry.

Where you can study

Auckland campus
Distance and online

International students

International students are not New Zealand citizens or residents.

Definition of New Zealand citizens and residents

Open to international students on campus in New Zealand

Specialise in Data Science for your Bachelor of Information Sciences at Massey

The Bachelor of Information Sciences (Data Science) gives you the skills to fill the rapidly growing number of jobs in the area of data science and analytics.

You’ll learn how to make sense of complexities so others can understand them and how to apply computing to data-oriented challenges. You may have an interest in commerce, government, natural and social sciences. You can learn how to apply technology to drive potentially world-changing innovation, decision-making and research in those fields.

Data Science brings together some of the most interesting aspects of computer science, IT and statistics in order to make a unique, custom-designed and relevant specialisation for the current job market.

A Bachelor of Information Sciences in Data Science is a good fit if you:

  • you are curious, love problem solving and making discoveries
  • want to be on the cutting-edge of artificial intelligence innovations shaping the world
  • want a dynamic and stimulating career for life.

Planning information

This is a guide. You are advised to check the Courses and specialisations section and the regulations for this programme on this page for the latest information on courses.

Your first year

First year for a full-time student usually consists of eight courses.  Take electives (or courses from other majors) to get the total number of courses to eight.  Make sure you include courses that are prerequisites for the next level of courses you wish to study.  You can change your major up until the start of your second year and it is a good idea to keep your options open by taking courses such that you are ready to move on to several different majors.  In the first year of study, you should take the following courses:

  • 159101 Technical Programming 1
    159102 Technical Programming 2
  • At least one mathematics course – one or more of 160105, 160101, 160102
  • At least one statistics course – one of 161111 or 297101 Statistical Data Science. Note: 297101 is more relevant to computing majors
  • 247112 Science and Sustainability for ICT (or another Science and Sustainability course) 

See Courses and specialisations for the required courses at 200-level and 300-level.

Minors 

Completing a minor is optional. Minors increase the breadth of your degree. They give you extra knowledge, attributes and capabilities. 

A minor must be in a different subject from your major. 

A Bachelor of Information Sciences (Data Science) with a minor 

You may choose a minor from any University undergraduate degree that has recognised minors. If the minor is from another undergraduate degree, the regulations of that qualification will apply.  

A data science minor (for students who are studying a different degree)

If you are not studying towards a Bachelor of Information Sciences (Data Science) and wish to complete a minor in data science see the regulations for the requirements of this minor.  

Computer requirements

You will need:

  • Computer (laptop or desktop) (Mac or Windows) - needs to be no more than two years old at the commencement of your study
  • Recent version of operating systems
  • Chromebooks are not suitable

Official regulations

To understand what you need to study and must complete to graduate read the official rules and regulations for this qualification.

You should read these together with all other relevant Statutes and Regulations of the University including the General Regulations for Undergraduate Degrees, Undergraduate Diplomas, Undergraduate Certificates, Graduate Diplomas and Graduate Certificates.

Returning students

For returning students, there may be changes to the majors and minors available and the courses you need to take. Go to the section called ‘Transitional Provisions’ in the Regulations to find out more.

In some cases the qualification or specialisation you enrolled in may no longer be taking new enrolments, so may not appear on these web pages. To find information on the regulations for these qualifications go to the Massey University Calendar.

Please contact us through the Get advice button on this page if you have any questions.

Courses you can enrol in

Course planning key

Prerequisites
Courses that need to be completed before moving onto a course at the next level. For example, a lot of 200-level courses have 100-level prerequisite courses.
Corequisites
Courses that must be completed at the same time as another course are known as corequisite courses.
Restrictions
Some courses are restricted against each other because their content is similar. This means you can only choose one of the offered courses to study and credit to your qualification.

Core courses for the Bachelor of Information Sciences

As well as the specialisation courses listed below, this qualification has core courses that you will need to complete.

Bachelor of Information Sciences core courses

Data Science courses

Compulsory courses

Choose 45 credits from
Course code: 158337 Database Development 15 credits

A study of enterprise data models, including how data storage and retrieval methods have changed over time. Modern techniques for handling relational and non-relational data and their implications in transactional and analytical processing are evaluated. Students will gain practical skills in designing, creating and querying databases using database management systems.

Prerequisites: One of 1582xx or 1592xx Restrictions: 158247

View full course details
Course code: 297201 Data Wrangling and Machine Learning 15 credits

An introduction to the data science workflow involving the acquisition, processing, transformation and integration of data from disparate sources having inherently different data structures, from which actionable insights can be extracted. Entry-level machine learning and statistical techniques for analysing and extracting knowledge from data will be covered. Particular emphasis will be placed on attaining competency in using a high-level programming language for conducting data-driven problem solving and appreciating the necessary agility such tools afford.

Prerequisites: 297101 or 161122 or (one of 159101, 159100 and one of 1611xx, 160101, 160102) Restrictions: 158222

View full course details
Course code: 297301 Applied Machine Learning and Big Data Processing 15 credits

An in-depth exploration of methods for developing intuition and insights about data that enables effective problem formulation and its solution through data-driven methods. A broad range of advanced machine learning and data mining algorithms will be used to build predictive models from real-world contexts. A particular emphasis will be on developing data-products, rapid prototyping and effectively communicating their value through visual storytelling and interpretable summaries. Practical skills for processing large datasets will be taught.

Prerequisites: 158222 or 297201 Restrictions: 158333

View full course details

Subject Courses

At least 30 credits from

Any 161.2xx Courses

At least 15 credits from

Any 161.3xx courses

At least 15 credits from

Course code: 158258 Web Development 15 credits

An introduction to web-based application development. Students will gain practical experience in the use of modern techniques relevant to the design and development of web-based systems.

Prerequisites: 1581xx or 1591xx Restrictions: 158256

View full course details
Course code: 159201 Algorithms and Data Structures 15 credits

An introduction to the analysis and implementation of algorithms and data structures including linear data structures, trees, graphs, hash tables, searching algorithms, sorting algorithms, optimization problems and complexity analysis. The course includes a significant practical component covering the implementation and application of important data structures and algorithms.

Prerequisites: 159102 Restrictions: 159271

View full course details

At least 15 credits from

Course code: 158326 Software Construction 15 credits

An advanced study of methods used to model, design, build and test robust software artefacts. The course provides an in-depth study of multiple techniques to support software design and implementation. It takes a practical approach using current methods and tools.

Prerequisites: 158256 or 158258 or 159234 or 159270

View full course details
Course code: 159302 Artificial Intelligence 15 credits

An advanced study of the principles and techniques used in developing Artificial Intelligence applications. The course includes the implementation and application of a range of AI methods including state-space representation and search, knowledge representation, constraint satisfaction, game playing, logic systems and machine learning.

Prerequisites: 159201 or 159234 Restrictions: 159372

View full course details

Compulsory capstone course

Choose 15 credits from
Course code: 158383 Information Technology Project 15 credits

Based on an initial project specification, students work individually or in groups on carrying out an information technology project. This includes understanding the project context, selecting appropriate methods and approaches, constructing the project artifacts, and reporting on project outcomes.

Prerequisites: At least two (2) 1582xx courses

View full course details
Course code: 159333 Computer Science Project 15 credits

A capstone computer science project. Students will develop a piece of software or conduct a computer science research project under the supervision of an academic staff member. Projects will be completed individually or as part of a team depending on staff availability. Students must produce a written technical report and give an oral presentation demonstrating their work.

Prerequisites: Four (4) of 1592xx or One (1) of 1593xx

View full course details

Entry requirements

Admission to Massey

All students must meet university entrance requirements to be admitted to the University.

Specific requirements

There are no specific entry requirements for this qualification, outside of university admission regulations.

English language requirements

To study this qualification you must meet Massey University's English language standards.

English language skills

If you need help with your English language skills before you start university, see our English for Academic Purposes (EAP) courses.

Can't meet the entry requirements?

If you need to do a course before you start your qualification, there may be options for you in Summer School.

Fees and scholarships

Fees, student loans and free fees scheme

Your tuition fees may be different depending on the courses you choose. Your exact fees will show once you have chosen your courses.

There will also be some compulsory non-tuition fees and for some courses, there may also be charges for things such as study resources, software, trips and contact workshops.

Already know which courses you're going to choose?

You can view fees for the courses that make up your qualification on the course details pages.

Student loans (StudyLink) and Fees Free scheme

You may be eligible for a student loan to help towards paying your fees.

The New Zealand Government offers fees-free tertiary study for eligible domestic students. Find out more about the scheme and your eligibility on the Fees Free website. To use the site's eligibility checking tool, you will need your National Student Number.

Current and returning Massey students can find their National Student Number in the student portal.

Fees disclaimer

This information is for estimation purposes only. Actual fees payable will be finalised on confirmation of enrolment. Unless otherwise stated, all fees shown are quoted in New Zealand dollars and include Goods and Services Tax, if any. Before relying on any information on these pages you should also read the University's Disclaimer Notice.

Careers and job opportunities

A shortage waiting to be filled

LinkedIn’s 2020 Emerging Jobs Report lists Data Scientist and Artificial Intelligence Specialists as being the top three professions for the last three years. This trend is likely to continue throughout the disruptions in the job market and economic uncertainties.

Data scientists are in high demand because they:

  • innovate new products
  • drive greater efficiency in profitability in competitive environments
  • enable management to make better decisions.

The skills you learn at Massey University and the qualification you will receive are recognised throughout the world and enable you to work in any industry or government sector.

A career with variety

Some examples of careers that could lead on from this qualification include:

  • data science engineer
  • Hadoop big-data engineer
  • business analytics consultant
  • data-product entrepreneur
  • banking fraud detection analyst
  • machine learning specialist
  • government researcher
  • government communications and security analyst
  • customer insight analyst
  • data management architect
  • text mining analyst
  • software developer
  • scientific researcher.

International students

New Zealand is a great place to study. Massey University’s reputation is supported by our international rankings, accreditations and associations. We are rated five star plus by the QS World University Rankings.

Massey University has small class sizes, and our lecturers and staff are friendly and approachable.

As an international student, there are entry requirements that will apply to you. We recommend that you apply at least three months before your anticipated start date so your application can be processed in time. There are additional steps you will need to take. These include obtaining a visa and travel bookings if your study is to be in New Zealand.

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