Level 9

(Strands in Data Analytics and Cyber Security)

Master your IT career in data analytics or cyber security

Enhance your digital technologies qualification and further develop your high-level problem-solving skills to lead the constantly evolving IT industry.

Programme highlights

Want to enhance your digital technologies qualification?

High-level problem solvers are needed to keep up with the constantly evolving IT industry. Designed in conjunction with industry experts this programme will provide you with the tools and knowledge to solve tomorrow’s complex IT problems.

With blended delivery, this programme is perfect if you’re wanting to earn and learn. Study online and attend group sessions with your peers and a facilitator/subject expert.

Studying part-time gives you the opportunity to be working in industry while completing your studies. You will undertake an applied research project that is connected to your own practice and industry experience.

You can choose a specialist strand in:

  • Data analytics or
  • Cyber security.
Entry requirements

Entry requirements

Academic requirements

To be admitted to this programme an applicant must meet the following requirements:

Applicants must have one of the following, or equivalent:

For direct entry into the final applied research project:

  • Bachelor honours degree in a relevant discipline; or
  • Postgraduate diploma in a relevant discipline; or

For entry into the Master of Applied Technologies by coursework and applied research project:

  • A recognised bachelor degree in a relevant discipline, with merit achievement, deemed to be an average grade of B or higher in all final-year courses*. Candidates with a B- or better average grade may be admitted to the Postgraduate Diploma in Applied Technology, and may be allowed to continue to the applied research project upon attaining an average grade of B or better; or
  • A professional qualification in a relevant discipline recognised as being equivalent to merit achievement in a bachelor degree and documentary evidence of outcomes in the discipline work environment to demonstrate an ability to perform in the programme and commit to achieving its outcomes, including recommendations from employers or professional colleagues.

*For Data Analytics pathways, the candidate’s previous qualification should be in an area related to either Data Science, Data Analytics, Computer Science, Software Engineering, Information Systems, Computer Engineering, Machine Learning, or Business Intelligence. Graduates of other disciplines may be accepted on a case-by-case basis and upon approval from the School of Digital Technologies.

English language requirements

Applicants must have sufficient competence in the English language to undertake this programme, which is taught and assessed in English.

International students: English Language Entry Requirements
For the minimum English language requirements refer to the requirements set out in the NZQF Programme and Accreditation Rules https://www.nzqa.govt.nz/providers-partners/qa-system-for-teos/english-international-students/

Selection criteria

Applicants will be selected in order of successful application

Exceptions to entry

An applicant may be considered for special admission if they have:

  • An undergraduate degree in an unrelated discipline, with merit achievement, and have a minimum of two years’ appropriate work experience that is relevant to the aims of this qualification; or
  • A graduate diploma qualification in the same or similar discipline, with a B grade average or better, and has a minimum of two years’ appropriate work experience.  A grade average of B- will allow entry to the Postgraduate diploma, with entry to the Master’s degree upon completion with a B grade average.
Recognition of prior learning (RPL)
  • There must be documentation of methods used to assess RPL credited where no formal documentation of the previous learning can be provided.
  • Specific RPL processes must ensure that any prior learning has been matched with the learning outcomes, levels, and amount of credit of any components of the proposed programme.
  • Applicants will need to demonstrate graduate and learning outcomes through a range of: portfolio, challenge tests, attestations and a professional conversation.
  • Gaps identified through the challenge test will be completed via enrolment onto MIT courses.
  • Fees apply.
Cross crediting/credit transfer
  • Credit recognition/transfer will be done on the basis of matching paper/courses learning outcomes and assessments passed against those of the provider’s qualification and programme.
  • Where there is not a direct match between papers passed and those of the cross crediting/credit transferring institution a minimum of at least an 80% match is expected in cross crediting each paper/course.
  • Credit recognition will be available upon application along with a relevant academic transcript of less than 3 years since last date of attendance. Applicants may be required to do a challenge test. Fees apply.
  • Credit transfer may be available upon application along with a relevant academic transcript of less than 3 years since last date of attendance. No Fees apply.

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Give yourself credit with Recognition of Prior Learning (RPL)

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Your previous work experience and on-the-job skills, volunteering, professional development, and other providers’ qualifications can be recognised as prior learning, matched against credits in our courses, and put towards your qualification – potentially saving you money and possibly helping you to complete your qualification faster Learn more.

Programme structure

Programme structure

You will need to complete three compulsory courses and one elective course (120 credits):

Compulsory courses

Level 8

561.800 Research methods in applied technologies (15 credits)

Learn research skills in your chosen field of applied technologies. This may include: literature reviews, writing research proposals, formulating research questions or hypotheses, and applying methods that answer research questions.

561.801 Applied project (30 credits)

Critically analyse applied technologies through the lens of your chosen pathway. You will devise and conduct a small applied technologies-based investigative project in a practice-based learning environment through industry-relevant learning, or through a project aligned to your area of interest.

Level 9

561.900 Applied research project (60 credits)

Design the process, carry out the analysis, and report on an applied research investigation.
This project will be aligned with work that you are undertaking in either a practice-based or simulated environment. You will conduct applied technologies practice-based research within a specialist pathway area that extends elements of earlier work on the programme according to your research interests and particular skills.

Elective courses

561.812 Design thinking and innovation (15 credits)

Learn the basic principles of right-brain thinking in order to access and leverage your ‘inner-designer’.

After a range of introductory exercises in creative thinking styles and behaviours, you will learn the basic stages of a design process. You will use a selection of design tools and methods so you can experience the typical elements in a design life cycle. These include:

  • Discovery
  • Interpretation
  • Ideation
  • Experimentation
  • Evolution.

561.813 Principles of user experience design (15 credits)

Learn the skills to analyse and evaluate the foundational principles, tools and best practices for the design of content and user experience across a range of applied technologies. Gain a holistic understanding of UX design, through a range of teaching methodologies and application in practice.

Plus, you will also need to complete the compulsory courses from your chosen strand (60 credits):

Data analytics strand

561.802 Data analytics and intelligence (15 credits)

Learn how data analytics create organisational values and learn how to demonstrate visual representation of big data sets for exploring business intelligence and opportunities.

561.803 Data warehousing and big data (15 credits)

Understand the concept and challenges of big data, design and implementation of a data warehouse, and create sophisticated decision models and scenarios.

561.804 Advanced data analytics (15 credits)

Design, develop and implement an advanced Data Analytics system from a big data set using a data analytics tool.

561.805 Database application development (15 credits)

Design and develop a transaction management database applications using a mainstream platform and object library to present and manipulate data stored in a relational database, and to process data and generate reports.

Cyber security strand

561.807 Cyber security concepts and practice (15 credits)

Analyse real-world cyber security challenges that organisations face, and address them through current systems and processes.

561.808 Cryptography and information security (15 credits)

Get an introduction to modern cryptographic techniques in the context of information security in the workplace. You will develop an understanding of the different types of cryptosystems available, the practical issues of applying cryptographic methods and key issues in the management of information security.

561.809 Cyber security business and data (15 credits)

Learn to negotiate the constantly changing use of data and information in a business environment that requires constant and ongoing cyber security awareness and attention. You will have access to live environments in which to practice offensive and defensive protection in a simulated environment.

561.810 Cyber law (15 credits)

Analyse local and international laws regarding issues around cyber security as well as short and long term impact.

Do you want to study a single course, without enrolling into the full programme?

Courses within some of our programmes may be offered as an individual Certificate of Proficiency (COP). Programme entry requirements and course fees apply. For more information, please speak to our friendly Ask Me! team.

Careers and pathways

Career opportunities

Opportunities for employment include:

Data analytics
  • Data analyst
  • Business analyst
  • Business intelligence analyst
  • Data insight analyst
  • Big data engineer, marketing analyst
  • Research analyst/manager
  • Business performance analyst
  • Business process engineer
  • Data or fraud analyst
  • Project manager
  • Data engineer/scientist
  • Data warehouse analyst
  • Digital forensic analyst
  • Quantitative analyst.
Cyber security
  • Fraud analyst
  • Digital forensic analyst
  • Incident analyst
  • Information assurance analyst
  • Malware analyst
  • Network forensic analyst
  • Operations analyst
  • Security analyst/consultant/developer/engineer.

For potential salaries visit careers.govt.nz.

Information is correct as at 29 November 2023. Programme fees are based on a full-time student and may vary depending on your final selection of courses that make up your programme. To provide you with an indication of costs, the approximate fees quoted in this publication are based on the indicative 2024 fee structure. The indicative programme fees for 2024 do not include the Compulsory Student Services Fee (CSSF). The CSSF is an additional levy to your 2024 programme or course fees. Further information about the CSSF can be found here www.manukau.ac.nz/cssf. Programmes stated as eligible for free study in 2024 are based on the 2023 fee structure and subject to funding confirmation for 2024. All fees are in New Zealand Dollars. You will be advised of the current fees at the time of enrolment. All courses and programmes will proceed subject to numbers and academic approval. Manukau Institute of Technology is part of Te Pūkenga – New Zealand Institute of Skills and Technology. Te Pūkenga is accredited under the provisions of the Education and Training Act 2020. International students must study in class and will not be able to enrol for online study options.