POSTGRADUATE STUDY

Postgraduate study in Applied Data Science

Fast-track your career by gaining a broad and practical understanding of the principles and applications of data science through our Postgraduate Diploma or Master of Applied Data Science. Learn how to identify and describe data trends using statistics and specialised software to help achieve success and enhance productivity. 

Ready to start learning in January 2024? Applications open now until 21 January.

ENTRY TIMES
29 January 2024
April 2024 TBC
July 2024 TBC
October 2024 TBC

DURATION
Master of Applied Data Science (MADS): 3 years part-time

Postgraduate Diploma in Applied Data Science (PGDipADS): 2 - 4 years part-time

PRICE
$1,109* per 15 point course for domestic learners
$4,375* per 15 point course for international learners

*Fee estimates are based on the 2024 fee schedule and are subject to revision each year. Actual fee will be determined by course selection. Prices include GST where applicable. Non-tuition fees, such as the Student Services Levy (SSL), will also apply. 

QUALIFICATIONS
MADS: 180 points
PGDipADS: 120 points

Overview



In our rapidly changing world, data is being captured, stored and shared every day. Being able to use and understand the vast amounts of information that we access can lead to better productivity; and efficiency, and is increasingly necessary for effective leadership.  

Skills in data science and data management are in hot demand around the world, and graduates will stand out from the crowd with applied skills, technical knowhow, and analytical expertise. 

With flexible study options, you can choose as you learn whether you'd like to graduate with a Postgraduate Certificate in Applied Data Science, or progress through to complete a Master of Applied Data Science.

With the Master of Applied Data Science, you'll test your skills through a research project based in industry, giving you a head start into your next career move.

With the Postgraduate Diploma in Applied Data Science, you'll gain a broad understanding of the principles of data science, the software tools that can be used to track and describe data trends, as well as analytical capability in a fast-tracked timeframe.  

 

Requirements


To ensure that our learners have the necessary background and experience to succeed, you will need an undergraduate degree in any field, with a grade average of B or greater in your 300-level courses. Alternatively, you must have evidence of academic achievement at a postgraduate level. 

To enter the master's degree programme, you will also need to confirm placement availability, and subject to approval. 

If English is your additional language, you are also required to meet UC's English language requirements.

For the full entry requirements, see the Regulations for the Postgraduate Diploma in Applied Data Science, the Regulations for the Master of Applied Data Science, or use the admission requirements checker
 
Not sure about your eligibility? 
Please register your interest  here, let us know your eligibility questions, and our team will be in touch. 

 

Structure


The Postgraduate Graduate Diploma in Applied Data Science can be studied part-time over 2 years, subject to course availability. The programme must be completed within 4 years. 

The Master of Applied Data Science includes an additional 15-point paper, and a 45-point research project course based in industry. It can be studied part-time over 3 years.  Sign up to our mailing list to find out more. 

Time commitment   
Unless otherwise stated, Tuihono UC | UC Online learners study across terms, rather than semesters. We have four terms per year (starting January, April, July and October) which consist of nine-weeks of study (including a one-week study break), followed by a two-week period of marking and feedback.

Part-time learners complete one 15-point course every term, requiring approximately 18.5 hours of study per week. Full-time learners complete two courses every term, requiring approximately 37.5 hours of study per week. Study time includes taking in course material, reflection time and writing assessments. Our courses are flexible, enabling you to plan your study around your other commitments. 

Upcoming term dates  
Our current nine-week learning dates can be found below (please note: these dates exclude our two-week period of marking and feedback).

  • 29 January - 1 April 2024
    • Study break: 26 February - 3 March 2024
  • 22 April - 24 June 2024
    • Study break: 20 - 26 May 2024
  • 15 July - 16 September 2024
    • Study break: 12 - 18 August 2024
  • 7 October - 9 December 2024
    • Study break: 4 - 10 November 2024

Please note: these dates are provisional and may be subject to change.

 

Begin

   

Get started with 3 foundation courses. 

Courses taken: Introduction to Data Science (DATA401), Computer Programming (COSC480), and Data Management (MBIS623). 

Learn

   

Having successfully completed the foundation courses, take the next step in your learning.

Courses taken: two Tuihono UC micro-credentials Data Ethics (10 points) and Professional Project Management (5 points) 

Diploma

   

Once you have successfully completed the above courses, you take the final four courses for the Postgraduate Diploma in Applied Data Science.

Courses taken: Scalable Data Science (DATA420), Texts, Disclosures and Data (DIGI405), Data Mining (STAT462), and Big Data (STAT448)

Master's

   

If you would like to upgrade your PGDipADS into an 180-point Master of Applied Data Science, you need to complete all of the programme above plus two more courses.

Courses taken:

  • 1 x 15-point course from Data Wrangling for Data Science (DATA422) OR Computational Social Choice (DATA415) 
  • plus a 45-point research project (DATA601) based in industry
Entry to the master's degree is not automatic but will be based on your grades in the previous courses and is subject to approval.

Please note: our courses may not be offered in order shown below, depending on availability. 

What you'll study


The Postgraduate Diploma is comprised of nine postgraduate courses detailed below. The Master of Applied Data Science is comprised of those same nine courses, plus one additional 15-point course (DATA422 or DATA 415), concluding with a 45-point research project (DATA601). 

Introduction to Data Science (DATA401) | 15 points

Description 
This course covers the development of statistical concepts and their application to complex systems. 

Computer Programming (COSC480) | 15 points

Description
This course covers computer programming and program development in a high-level language with special emphasis on style and structure. 

Data Management (MBIS623) | 15 points

Description
This course introduces students to a range of topics that underpin the successful use and management of databases in contemporary organisations. The course exposes the students to associated real life issues related to data management and database management systems. 

Data Ethics | 10 points

Description
From the board room to the shop floor, employees today are constantly raising, responding to, and thinking through various ethical issues surrounding data. This course goes beyond the regulatory requirements of what you can do, building an in-depth understanding of these issues to determine what you should do.

Note that this course will be studied at the same time as Professional Project Management.

Professional Project Management | 5 points

Description
Learn how to ensure project management success with practical project management consultant, Sean Whitaker. Learn the skills you need to deliver projects on-time and on-budget, with positive stakeholder engagement. 

Note that this course will be studied at the same time as Data Ethics.

Scalable Data Science (DATA420) | 15 points

Description
This course will introduce students to new computational methods used in data science. We will look at methods for data from a range of contexts, including scalable methods used for big data and distributed computing.  

Data Mining (STAT462) | 15 points

Description
Suited to anyone with an interest in analysing large datasets. This course will introduce a variety of statistical learning and data mining techniques for classification, regression, clustering and association purposes. Possible topics include, classification and regression trees, random forests, Apriori algorithm, FP-growth algorithm and support vector machines.  

Texts, Discourses and Data: the Humanities and Data Science (DIGI405) | 15 points

Description
This course examines computer-aided methods used in digital humanities and the social sciences for analysing discourses, an object of study that draws together multiple ways that language reflects and shapes social meanings. Within this context, it introduces concepts and methods for analysing natural language data and applies these through a series of practical lab classes.  

Big Data (STAT448) | 15 points

Description
Suited to anyone with an interest in data, and how it can be used in decision making, this course will introduce you to big data and some of the techniques you can use to access, explore and investigate it.   

Data Wrangling for Data Science (DATA422) | 15 points - MADS elective

This course develops learners' skills in data cleaning and processing, data integration techniques and implementing data wrangling workflows for a real-world datasets.

Computational Social Choice (DATA415) | 15 points - MADS elective

This course provides a thorough introduction to both classical and computational social choice. Social choice theory is the study of mechanisms for collective decision making, such as voting rules or protocols for fair division. Computational social choice addresses problems at the interface of social choice theory with computer science, it uses concepts from social choice theory in the presence of big datasets.

Data Science Project (DATA601) | 45 points - MADS only

This applied research project will give you the skills, and experience to work in a team to solve real world data science problems.

 

If you would like to study the master’s option, entry would be based on your grades in the courses required for the postgraduate diploma, and you would need to apply before graduating with the diploma. Please register your interest to find out more.  

 

Our people


The postgraduate programmes in Applied Data Science are coordinated by Gabor Erdelyi, Clemency Montelle, Taylor Winter, and Jennifer Brown.

Gabor-Erdelyi

Gabor Erdelyi

Associate Professor, Director of Teaching | University of Canterbury

Gabor Erdelyi’s primary research interest is in the theoretical foundations of artificial intelligence (AI), in particular in multi-agent decision-making and algorithmic decision theory. He is also interested in the societal and regulatory aspects of AI. In addition to his role at UC, he is serving as an expert at the International Organization for Standardization’s (ISO) AI committee (ISO/IEC JTC 1/SC 42), actively shaping standardization on AI.

Gabor is also an affiliate of the International Panel on the Information Environment, providing neutral assessments on the condition of the global information environment and evaluate the best policy solutions for addressing threats to it. 

Clemency-Montelle

Clemency Montelle

Professor, Head of School | University of Canterbury

Clemency Montelle's research interests include the history and philosophy of mathematics; the preparation, translation, and commentary of ancient mathematical texts in Greek, Latin, Sanskrit, Arabic and Akkadian; and ancient mathematical astronomy and modelling.

Taylor Winter

Taylor Winter

Lecturer | University of Canterbury

Taylor Winter is currently investigating how different societal and group factors can elicit transient changes in an individuals levels and types of authoritarian state. He uses a range of longitudinal and momentary data with a focus on Bayesian methods and structural equation modelling.

More broadly, Taylor uses a number of data sources, including surveys, administrative data, and experimental data, to understand wellbeing. This is a complex topic that can involve a broad range of variables such as an individuals environment, relationships, or even physical health.

Jennifer-Brown

Jennifer Brown

Professor | University of Canterbury

Jennifer Brown's primary research interest is in environmental statistics and she has expertise in survey design and environmental monitoring. Research in environmental statistics is collaborative by its very nature, and Jennifer works with both statisticians and biologists. As an applied statistician, Jennifer is involved in projects in a variety of application areas and as such publishes in a wide range of journals.

Jennifer's research interests are broad and go beyond environmental statistics. She works in other application areas, most recently, human health and wellbeing. She also works in theoretical statistics, with publications in topics ranging from theoretical sampling to regression trees.

Express interest


If you're keen to know more, stay updated on when enrolments open, ask a question or assess your eligibility, please express your interest below.  

Please note: UC Online has a minimum enrolment threshold that must be met to enable opportunities for interaction, discussion, and feedback. If the minimum number of enrolments required for a course is not met, enrolled learners will be given the option to defer their enrolment to the next course date, or receive a refund. 

29 January 2024

Applications open until 21 January. 

Future enrolments

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Need more information?

Contact us to learn more

FAQ

What is an online Postgraduate Diploma in Applied Data Science?

The Tuihono UC | UC Online Postgraduate Diploma in Applied Data Science is a fast-tracked programme designed for those with non-technical backgrounds to develop advanced knowledge, skills and competencies in data science. 

What is an online Master of Applied Data Science?

The Tuihono UC | UC Online Master of Applied Data Science is a taught master's degree to enable you to move into your next career step in Data Science, and is designed for those with non-technical backgrounds. 

Why study with Tuihono UC | UC Online?

Bringing together the latest industry-informed learning applicable to your life and career, the Tuihono UC | UC Online postgraduate study in Applied Data Science gives you the same quality education as our on-campus programmes, with the flexibility of online learning. 
 
This includes 24/7 learning, academic advice and technical support, giving you the support to study anywhere, anytime, at your pace. 

What career opportunities do these programmes offer?

Aotearoa New Zealand and many other countries are currently experiencing a skills shortage in this area, and the need for data savvy professionals with applied experience is growing. 

Graduates will be ready to work in a range of industries including: government, corporates, the IT sector, market research and finance, agriculture, and transport. 

What are the tuition fees?

The estimated tuition fees per course based on the 2024 fee schedule:

  • for domestic learners is $1,109* per 15 point course
  • for international learners is $4,375* per 15 point course 

Total programme investment for the 120-point PGDipADS based on the 2024 fee schedule:

  • for domestic learners is $8,872
  • for international learners is $35,000

Total programme investment per year for the 180-point MADS based on the 2024 fee schedule:

  • for domestic learners is $13,316
  • for international learners is $52,500

*Fee estimates are based on the 2024 fee schedule and are subject to revision each year. Actual fee will be determined by course selection.  Prices include GST where applicable. Non-tuition fees, such as the Student Services Levy (SSL), will also apply.  

Student Services Levy costs
Each year university students around Aotearoa New Zealand are charged a Student Services Levy (SSL) in addition to their tuition fees. All the SSL money collected can only be used for the benefit of students - never for academic or administrative costs.

The SSL is automatically calculated on how many points you enrol in per academic year, capped at a maximum of 150 points. UC Online learners are charged a reduced SSL rate, which is 20% of the usual on-campus student levy. This is calculated as $1.83 per academic point in 2024. You can learn more about the Student Services Levy here, and more about UC Support Services here.

How long does online postgraduate study in Applied Data Science take?

The PGDipADS can be completed part-time over 2 years, and must be completed within four years. 

The MADS can be completed part-time over 2 and a half years, and must be completed within three years. 

What are the benefits of studying an online Master of Applied Data Science?

Studying online allows for flexibility in completing coursework, and Tuihono UC’s programme provides learners with the same quality education and resources as our on-campus programmes. 

A taught master's degree can give you the next step in your career, or support you to shift into a new career in data science.

How does an online Applied Data Science programme differ from a traditional on-campus programme?

The robustness of the academic programmes are the same, but the online programmes offer greater flexibility in terms of scheduling and location. 

How is an online Master of Applied Data Science or a Postgraduate Diploma in Applied Data Science delivered?

Each programme is delivered with a majority of coursework online, using a range of technologies including video conferencing, online discussion forums, and interactive learning experiences.   

What kind of support is available to learners enrolled in the online postgraduate study in Applied Data Science?

Learners have access to the same support services as on-campus students, including academic advising, technical support, and library resources. There are also great resources for both Canterbury based and remote learners at the UC RecCentre. Learn more here.

Learners also have the support of our Tuihono UC Learner Experience team

How can I finance my online study in Applied Data Science?

There are a range of options you can use to finance your study, which you can learn more about here. 

How do I apply?

Applications are made online through our UC Online website – view open enrolments and/or expressions of interest for when enrolments open. 

What are the expectations for participation?

Learners are expected to participate actively in forum discussions, and complete assessments on time.  

Can these online programmes in Applied Data Science lead to further study?

Each programme is a standalone professionally relevant qualification.

Any learner interested in pursuing a PhD or further research would be encouraged to contact the Faculty of Science advisors

Can I study on campus?

An on-campus version of the PGDipADS as well as an on-campus version of the MADS are both available through the University of Canterbury. 

We are also developing our online offerings - if you'd like to hear about our latest news and offers, join our mailing list