The aim of the Graduate Diploma in Data Anaytics is to provide students with work-ready skills and specific knowledge to effectively use IT tools to support management in making informed business decisions, which will benefit large corporations, SMEs, NGOs, Māori and Pacific businesses and communities. Students will be career changers, and people upskilling to gain advanced skills and knowledge to collect and analyse big data, write machine learning algorithms, AI application, and optimise decision making. This programme will incorporate a focus on the importance of Te Tiriti o Waitangi and biculturalism and how it might apply in a professional context.

Graduates will be able to:
Integrate theoretical and technical knowledge and processes to implement solutions for complex business and technical challenges.
Apply effective communication skills, project management tools and techniques in the contexts of projects, collaboration and leadership, to deliver integrated solutions to diverse technical and non-technical audiences.
Apply advanced professional, ethical, social, legal, and environmental skills in a business and IT context that uphold the values of Te Tiriti o Waitangi and Aotearoa/New Zealand's bicultural society.
Apply critical thinking, problem-solving, research skills, creativity and strategic thinking techniques to solve problems in a range of technical and business contexts and to support continuous self-improvement.
Critically analyse data using data collection and transformation methods, analysis methods, data and decision modelling concepts and visualisation tools to address complex business situations ensuring ethical professional considerations are met.
Apply problem solving and strategic thinking skills to establish and create data warehouses, apply data mining techniques, and find data patterns to enhance business decision making.
Apply machine learning, AI and big data analytical technologies to data analytic systems that support and improve business decision-making through critical thinking, programming and research skills.
Apply a range of mathematical concepts and statistical models for analysis and forecasting in time series data to predict trends.

Graduates of this qualification will be able to apply for postgraduate study.

Domestic and International applicants must hold a relevant and recognised Degree Level qualification equivalent to at least 360 credits at NZQA Level 7 or equivalent.

Applicants aged 20 years or above who have not met the General Admission and Entry Requirements may be eligible for special admission. We consider a number of factors when assessing special admissions, such as previous education and training, work experience, and motivation to study. Special admission may be granted upon evaluation by the Head of School and the Academic Board, or delegated authority, based on supplied evidence. This may include a resume, personal statement, and portfolio. It is expected these documents provide evidence of a minimum of 2 years' relevant work experience undertaken by the applicant. This will be based on a case-by-case evaluation for each applicant.

English Language Requirements
Students must have the English language competence to undertake this programme which is taught and assessed in English. Applications who have English as a second language are required to have an International English Language Test System (IELTS) Academic score of 6.0 with no individual band score lower than 5.5; or equivalent. The score must have been achieved in one test taken within the preceding two years. This is subject to NZQA Rule 18, details of which can be found at:here

International Students

International students must meet the General Admission Criteria (or equivalent), English Language requirements and hold a valid study visa to enrol in this programme.

International students on study visas will not be eligible to enrol in part-time courses.