The master’s degree positions graduates for specialist and leadership roles. For candidates considering an academic career through doctoral studies, progression from the masters programme is possible, subject to a student’s performance meeting the entry requirements of the receiving institution.
The aim of the programme is to enable Master’s graduates to gain a higher-level qualification, extending specialised knowledge, skills and expertise, and meet industry needs through increased relevance in critical fields of IT.
The Master of Information Technology (MIT) is a 180-credit postgraduate programme taken over three trimesters full-time (1 year). It builds on the three-year Bachelor's degrees in the same academic field. Two specialisations are offered: Cyber Security and Data Science.
Certain specialist courses are 85% aligned with world-leading IT industry certifications, such as network defence essentials, ethical hacking essentials, digital forensic essentials, and Certified Chief Information Security Officer. Students enrolled into this programme will get a chance to obtain these certifications free of cost.
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:
Core course:
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 - Year 2
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
Where could this programme take you?
- Graduates of the Postgraduate Diploma in Information Technology will develop an ability to solve Information Technology programmes in a systemic and coherent way with an emphasis on analysis and innovation.
Jobs related to this programme
- Cyber Security Manager
- Cyber Security Consultant
- Cyber Security Analyst
- Security Operations Centre (SOC) Manager
- Penetration Tester
- Security Information and Event Management (SIEM) Administrator
- Network Security Engineer
- Security Consultant
- Governance, Risk Management and Compliance (GRC) Consultant
- Technology Solutions Architect
- Senior Technology Advisor
- Senior Data Scientist
- Data Architect
- Big Data Engineer
- Business Analytics Specialist
- Data Visualization Developer
- Business Intelligence (BI) Engineer
- BI Solutions Architect
- BI Specialist
- Analytics Manager
- Statistician
Duration
Online
USA
UK
India
UAE
South Africa
Canada
New Zealand
Australia
Malaysia
Singapore