Master of Information Technology

The Master of Information Technology is a 180 credit programme, consisting of three trimesters full-time.

Semester 1:

4 courses of 15 credits each

Core courses:

• Research Methods and Skills
• Technology Management

AND 2 elective courses

• Cyber Security
• Data Analysis
• Machine Learning
• Ubiquitous Computing and Intelligent Systems

Semester 2:

2 courses of 30 credits each

Core courses:

• Special Topic

AND 1 elective courses

• Information Security Standards and Operations
• Data Science: Introduction, Management and Practice

Semester 3:

1 course of 60 credits

Core course:

• Project

Research Methods and Skills (15 credits)

To formulate a research proposal with focused questions developed through analysis, and appropriate research methods for gathering, evaluating and reporting data to support inquiry.

Indicative Contents:

• Scientific method
• Types of Research (Historical, Descriptive, Correlational Studies, Experimental research)
• Legal, cultural and ethical implications of research
• Searching and analysing the related material (internet search)
• Research question writing – steps to follow
• Design of experiments
• Design Thinking
• Statistical techniques for analysis
• Bibliographic Tools
• Introduction to Latex

Technology Management (15 credits)

To review, select, implement and optimise existing strategies for managing technology within corporate environments, including the use of cloud deployments for competitive business advantage and apply advanced knowledge of IT service management, technology maturity models, information management, including the application of information governance, current laws and regulations.

Indicative Contents:

• Detailed understanding of Technology strategy; how it underpins and facilitates the execution of business strategy.
• Identification and the execution of technology roadmaps to meet current gaps and future demand from business
• IT Service Management (ITSM) theory and IT Infrastructure Library (ITIL) frameworks for management of Technology operations
• Technology root-cause-analysis and solution exploration as part of technology problem solving
• Data Lifecycle Management (DLM). Strategies and management of data acquisition, backup and recovery, metadata tagging, data maintenance, archival and retention, purging and operational risk & compliance
• Ethical and social impact of IT solutions on IT business
• NZ Privacy Act, GDPR and CCPA laws, and the ability to undertake Privacy Impact Assessment (PIA) and influence existing systems usage and creation of new data systems
• Privacy by Design theory, and the ability to apply Privacy by Design (PbD) framework to new data driven solutions.
• Pros and Cons of data anonymisation techniques with guidance on what to use for given situations
• Measures of data anonymisation risk; k-anonymity, governance, and ongoing compliance measures
• Operational management, change management, organisational behaviour analysis.

Special Topic (30 credits)

To undertake an in-depth investigation in emergent areas of IT, practical or theoretical, to build maintain currency, competence and expertise.

Indicative Contents:

• Individual and small group tutorials in relevant subject topics
• Revision of research methodologies including the impact of legal, cultural, ethical and social practices.
• Literature reviews
• Academic writing
• Preparation for the oral presentation

Cyber Security (15 credits)

To protect the data and integrity of computing assets with the knowledge, tools and techniques used in Cyber Security to evaluate systems and technology from a security perspective, classifying threats and underlying risks and their management.

Indicative Contents:

• Cyber Security Principles
• Risk Management for Cyber Security
• System Security
• Public Cloud Security
• Cryptography
• Ethical Hacking
• Disaster Recovery and Incident Response

Data Analysis (15 credits)

To develop data analytical skills and data-driven mindset to provide deep knowledge of data visualization tools, analytical techniques and common web analytical tools to perform a comprehensive analysis of different data types using various techniques. To interpret data and results for a non-technical audience.

Indicative Contents:

Introduce and practice data visualization tools including Visual Basic for Applications (VBA) in Excel and Tableau.

Understand data:

• Relationships between variables
• Detect and analyse outliers
• Recognise and examine data trends
• Create and evaluate hypotheses for the future and/or population

Demonstrate and apply data analytical techniques for data types:

• Regression
• Classification
• Cluster analysis
• Association analysis

• Web analytical tool (Google
• Analytics) and its application
• Part of contents can cover briefly about Weka
• Build machine learning process
• Train data
• Evaluate results

Machine Learning (15 credits)

To develop important insights into data and formulate an in-depth classification of the internal mechanism of machine learning algorithms, principals, and techniques. To analyse and evaluate the performance results of machine learning algorithms for real-world problems and design appropriate solutions with a profound demonstration of mathematics and statistics.

Indicative Contents:

• Supervise ML
• Un-supervised ML
• Regression
• Model Generalisation
• Neural Networks
• Support Vector Machine
• Dimensionality Reduction and Anomaly Detection
• Recommender Systems
• ML for Large Datasets

Ubiquitous Computing and Intelligent Systems (15 credits)

To gain specialised knowledge of models and techniques used in ubiquitous computing and intelligent systems, to develop analytical skills for experiments and solution designs of real-life problems. To evaluate how computing can be integrated into the user’s environment and how technology becomes pervasive to create seamless interaction between humans and computers.

Indicative Contents:

Applications of Ubiquitous computing, Smart Devices, Environment and Interaction framework (Smart DEI Model)

• Modelling the key Ubiquitous Computing Properties, Interaction of Ubiquitous System with Environment

Smart Devices and Services

• Service architecture models (Multi-tier client service models, service oriented computing, device models)
• Service provision lifecycle (service announcement, discovery, selection and configuration)

Tagging, Sensing and Controlling

• Real world object tagging
• Physical and virtual tag management
• Modelling context aware systems

Intelligent Systems (IS) and Artificial Life

• Basics of Intelligent System leading to the Architectures of IS
• (such as Reactive intelligent system model, Environment model based intelligent systems, Goal based Intelligent Systems, Utility based intelligent systems, learning based intelligent systems, Hybrid intelligent systems
• Semantic Knowledge Based Intelligent Systems
• Intelligent Systems with Classical Logic
• Soft Computing IS Models (overview of probabilistic networks and fuzzy logic)
• Interaction Multiplicity
• Applications of intelligent interaction
• Autonomous Systems and Artificial Life
• Reflective and Self Aware systems
• Self-management and Autonomic Computing
• Complex Systems
• Artificial Life

Internet of Things

• IPV6
• 6LoWPAN, CoAP and MQTT
• Understanding the Contiki which is an OS to operate small (low powered)

Information Security Standards and Operations (30 credits)

To provide in-depth knowledge of key components in the areas of cyber-attacks, countermeasures, computer, web, and network forensics, including ethical, legal, and social considerations of IT industry to conduct independent research and working with advanced cyber security tools to implement standards and practices.

Indicative Contents:

• Network, Information Security and Ethical Hacking Fundamentals
• Data Security using Identification, Authentication, and Authorization
• Network Security Controls: Administrative, Physical, Technical
• Virtualization and Cloud Computing
• Wireless Network Security
• Mobile and IOT Device Security
• Cryptography and PKI
• Network Traffic Monitoring
• Password Cracking Techniques and Countermeasures
• Social Engineering Techniques and Countermeasures
• Network-Level Attacks and Countermeasures
• Web Application Attacks and Countermeasures
• Wireless Attacks and Countermeasures
• Mobile Attacks and Countermeasures
• IoT Attacks and Countermeasures
• Cloud Computing Threats and Countermeasures
• Penetration Testing Fundamentals
• Computer Forensics and Investigation Process
• Understanding File Systems
• Data Acquisition and Duplication
• Defeating Anti-Forensics Techniques
• Network and Operating Systems Forensics (Windows & Linux)
• Investigating Email Crimes
• Malware Forensics
• Governance & Risk Management (Policy, Legal & Compliance)
• Understand the essentials of Risk management and risk treatment. Comply with the IT audit process and IT audit standards.
• Information Security Controls, Compliance, & Audit Management
• Comprehend the concepts of Information Security Controls, controls classification and guidelines and identify the acts, laws, and statutes of compliance management
• Security Program Management & Operations
• Understand the security operations program that defines the capabilities of an organization to identify security events, respond appropriately, and quickly restore operations to normal.
• Information Security Core Competencies
• Evaluate physical security mechanisms, examine the issues and recommend the countermeasures to safeguard the network infrastructure.
• Demonstrate the knowledge of different factors that help in the implementation of access controls and design an access control plan. Identify standards, procedures, directives, policies, regulations, and laws for physical security.
• Evaluate physical security mechanisms, examine the issues and recommend the countermeasures to safeguard the network infrastructure.
• Demonstrate the knowledge of different factors that help in the implementation of access controls and design an access control plan. Identify standards, procedures, directives, policies, regulations, and laws for physical security.
• Strategic Planning, Finance, Procurement, & Vendor Management
• Analyse, forecast and develop the operational budget of the IT department and understand how to design vendor selection process and management policy

Data Science: Introduction, Management and Practice (30 credits)

To provide an overview of data science and its applications in resolving contemporary real-world problems, including skills to collect, manage, manipulate, and analyse data sets using statistical software to design applicable solutions to industry standards.

Indicative Contents:

• Data Science Overview
• Data Technologies
• Data Science Workflow
• Big Data Problems and Solutions
• Descriptive Statistics Fundamentals
• Central Tendency
• Spread of the Data
• Inferential Statistics Fundamentals
• Data Distributions
• Data Formats
• The Data Science Process
• Data Cleaning
• Data Transformation
• Data Exploration
• Data Quality
• Data Privacy
• Data Visualisation
• Data Analytics

Project (60 credits)

To enable the application of relevant research methodologies to an independent research project in the field of interest and/or expertise. To select a problem, identify the gaps in existing studies, propose and develop novel solutions, evaluate and test the developed methods, and compare the results with existing state-of-the-art techniques.

Learning Outcomes:

• Advanced understanding of techniques and methodologies to conduct evidence-based research, including the impact of legal, cultural, ethical and social practices
• Review, critical analysis and understand existing studies (literature review)
• Data gathering, analysis and preparation techniques
• Advanced techniques for designing experiments
• Reporting and documentation of research findings
• Qualitative and quantitative measures for performance evaluation and comparison studies

NZ Government key information link for students, that provides more information to support your decision making for this programme

Domestic Student Entry Requirements:

• Completed application form
• Applicant must have one of the following:
  • A recognised Bachelor's degree in Information Technology or a related discipline with a B- or higher average, OR
  • A Bachelor's degree (Honours) in Information Technology or a related discipline, OR
  • Graduate Certificate or Graduate Diploma in Information Technology or related field
• Special consideration may be offered for admission by the Deputy Chief Executive Academic based on evidence of academic capability and work experience

International Student Entry Requirements:

• Completed application form
• Passport copy
• Statement of purpose
• IELTS Academic overall score of 6.5 with no band less than 6.0 or equivalent
• Applicant must have one of the following:
  • A recognised Bachelor's degree in Information Technology or a related discipline with a B- or higher average, OR
  • A Bachelor's degree (Honours) in Information Technology or a related discipline, OR
  • Graduate Certificate or Graduate Diploma in Information Technology or related field
• Special consideration may be offered for admission by the Deputy Chief Executive Academic based on evidence of academic capability and work experience

BYOD (Bring Your Own Device) Requirements:

This programme has Bring Your Own Device (BYOD) requirements, we recommend you follow the specifications listed as these will support you to be successful in your studies.

Required IT Specifications:

• The latest Windows is the recommended operating system, with regular updates across the programme of study.

Recommended IT Specifications:

Minimum Hardware requirements 

• Intel® or AMD processor with 64-bit support; 2 GHz or faster processor with SSE 4.2 or later 
  
• 16 GB RAM 
• 500 GB SSD or higher hard drive with 10GB free space minimum    
• Wireless capability 802.11n dual-band    
• Up-to-date antivirus software    

Minimum Operating System     

• Windows 10 (64-bit) version 1809 or later; LTSC versions are not supported (a must for IT Students) 
  OR     
• Intel i5 or equivalent or above
• AMD Ryzen5 or equivalent processor 

• Internet and unlimited data plan recommended.    

Not Supported:    

• Chromebooks    
• Windows X or Windows S OS    
• Tablets (except Windows Surface Pro or iPad Pro)