Qualification Overview
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Qualification Title | Postgraduate Diploma in Applied Data Analytics | |
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Qualification Type | Postgraduate Diploma | |
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Level | 8 | |
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Credits | 360 | |
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Subject Area |
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Strategic Purpose Statement |
The aim of the Postgraduate Diploma in Applied Data Analytics is to enable ākonga who have completed a bachelor's degree in a field with a high mathematical focus, such as engineering (including software engineering), science, economics, finance, or mathematics/statistics, to develop postgraduate-level knowledge and skills in applied data analytics through coursework and an applied project.
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Graduate profile |
Graduates of the Postgraduate Diploma will be able to: 1. Demonstrate advanced and integrated knowledge of data analytics concepts, methods and theoretical approaches, and apply this knowledge to complex analytical contexts. 2. Critically analyse data-related problems and apply advanced analytical techniques to generate evidence-informed insights for organisational decision-making. 3. Critically source, evaluate, and apply high quality data to produce evidence-based conclusions. 4. Communicate analytical findings, insights and recommendations effectively to diverse technical and non-technical audiences. 5. Apply ethical, legislative and regulatory frameworks related to data governance, privacy and data sovereignty in organisational and societal contexts. 6. Demonstrate professional responsibility and culturally responsive data practices consistent with the expectations of data professionals in Aotearoa New Zealand. 7. Engage in investigative applied analytics activities and contribute to the development of data-driven solutions to real-world challenges.
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Education pathways |
Bachelors or higher in a field with a quantitative focus>> Postgraduate Diploma >> 180/240 Masters >> Further Study
Bachelors or higher in a field with a quantitative focus>> Postgraduate certificate>> Postgraduate Diploma >> 180/240 Masters >> Further Study |
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Entry Requirements |
The academic entry requirement for the Master of Applied Data Analytics (240), Master of Applied Data Analytics (180), Postgraduate Diploma in Applied Data Analytics and the Postgraduate Certificate in Applied Data Analytics is one of the following: * an NZQCF-listed undergraduate degree (or equivalent) which has a quantitative focus5 with a minimum of the equivalent to a B minus (B-) average in the final year of study (as per the EIT-specified 11-point achievement-based grading system) or * a Bachelor Honours or Postgraduate degree which has a quantitative focus with 120 credits at Level 8 or * a degree or equivalent professional (quantitative-focused) qualification with a minimum of the equivalent to a B minus (B-) average in the final year of study (as per the EIT-specified 11-point achievement-based grading system) and/or verifiable evidence of quantitative experience at degree level, and assessment from the programme coordinator or * at the Dean's discretion, where an applicant's situation is compelling but not covered by the requirements listed above. All applicants must demonstrate an acceptable level of English language fluency prior to acceptance in the programme. For international ākonga, ways in which English language fluency may be demonstrated include the following: * successful study of a programme in which English was the language of instruction (subject to the conditions in EIT's Database for English Language Proficiency (DELP)) * completion of a New Zealand Certificate in English Language Level 5 (Academic) * IELTS Academic score of 6.5, with no band score lower than 6, achieved in a single test within the two years preceding enrolment * accepted international equivalents to the above IELTS scores (see equivalency tables in the DELP). An international ākonga must be in possession of an appropriate visa for the duration of their programme.
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Education Organisation | Eastern Institute of Technology | |
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Developed By | Eastern Institute of Technology | |
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Quality Assured By | New Zealand Qualifications Authority | |
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Number | 5789 | |
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Status | Current | |
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Created | 2026-11-12 11:50:59.157 | |
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Next Review | 2031-09-30 00:00:00.0 | |
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Content |
Quantitative methods and contemporary tools, data engineering, data analytics and visualisation, analytics for decision-making, intelligent analytics in practice, data governance and sovereignty, applied research methods, 300 hour project (Work Integrated Learning 2) and a 450 hour project (integrated project)
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