Level 8

(Strands in Data Analytics and Cyber Security)

Study an IT postgraduate in data analytics or cyber security

Want to gain or advance your skills and knowledge in cyber security or data analytics? Get the in-depth knowledge to solve tomorrow’s complex IT problems.
Overview

Programme highlights

Want to gain or advance your skills and knowledge in cyber security or data analytics?

Whether you are already working in the industry and looking to upskill or if you want to add specialist skills to an existing qualification this postgraduate diploma will provide you with in-depth knowledge to solve tomorrow’s complex IT problems.

You can choose a specialist strand in:

  • Data analytics or
  • Cyber security.

You will also undertake an applied project that is connected to your own practice and industry experience.

This programme has been designed in conjunction with industry experts so what you learn is relevant in the workplace.

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.

Upon successful completion of this programme you could complete the Master of Applied Technologies (Level 9) in only 17 weeks.

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:

  • A recognised bachelor degree in a relevant discipline, with merit achievement, deemed to be an average grade of B- (65%) or higher in all level 7 courses*; 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.
 
 
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Programme structure

Programme structure

You will need to complete two compulsory courses and one elective course (60 credits):

Compulsory courses

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.

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.

Careers and pathways

Career opportunities

Opportunities for employment include:

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

For potential salaries visit careers.govt.nz.

Recognition of Prior Learning (RPL)

Your work experience or previous tertiary study may count towards achieving your qualification. Recognition of Prior Learning (RPL) at MIT is designed for those who already have on-the-job skills and knowledge, but want to take their career to the next level with a qualification.

With RPL we can measure and match your existing skills against credits in our courses – creating a tailored path of study that will not only save you money but also help you to complete your qualification faster. Learn more.

Information is correct as at 5 November 2022. 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 2023 fee structure. The indicative programme fees for 2023 do not include the Compulsory Student Services Fee (CSSF). The CSSF is an additional levy to your 2023 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 2023 are based on the 2022 fee structure and subject to funding confirmation for 2023. 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 Pukenga 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.