Master of Science (Defence Technology and Systems)
The MDTS programme is divided into two parts, the Common Curriculum and the Specialized Curriculum.
This programme aims to provide students with a broad range of knowledge pertaining to systems engineering and introduction to key defence technologies. The learning emphasis is on systems thinking. The curriculum is multi-disciplined and broad based, including Guided Systems, Cybersecurity and Artificial Intelligence & Data Analytics, which are of growing importance to the defence community. It comprises a list of coursework modules conducted at the National University of Singapore (NUS) within the first 2 quarters of the programme. The students then proceed to Naval Postgraduate School (NPS) or Air Force Institute of Technology (AFIT) or Cranfield University (CU) where they will embark on the Integration Project over subsequent quarters.
MDTS Modules Linkages
DTS2701 Engineering Mathematics(Online Refresher Module)Introduction to vector fields, vector algebra and partial derivatives of vector and scalar fields. Gradient, divergence and curl. Introduction to line, surface and volume integrals; Green’s Divergence and Stokes’ Theorems. ODE classification and general solutions. First and second-order homogeneous and non- homogeneous ODEs. Introduction to error and sensitivity analyses. Matrix algebra: introduction and notation; rank, determinants, transpose and inverse; simple elementary row operations and linear independence; eigenvalues and eigenvectors. Complex numbers: introduction and geometrical representation; Argand diagram; complex algebra; Euler’s representation and De Moivre’s theorem. Fourier analysis: concept of transforms; Fourier series and orthogonality relations; Fourier transforms and applications. Probability axioms and event probability. Random variables and their probability distributions. Hypothesis testing, conditional probability and expectation
DTS2703 Probability and Statistics(Online Refresher Module)Topics include Descriptive Statistics, Probability Concepts, Conditional Probability, Discrete Distribution, Continuous Distribution, Non-normal, Multivariate
Quarters 1 and 2: Mar to Sep, at NUS (Singapore)
DTS 5701 Large Scale Systems Engineering
Large Scale Systems Engineering deals with the complexities of large-scale systems. The Systems Approach and Systems Engineering methodologies are used to understand and conceptualize the key issues in the planning, design and management of large scale systems. The module aims is to help students learn about Large Scale Systems Engineering (LSSE) with theories, stories and case studies on how systems are planned and implemented. By the end of the module, students are expected to be able to analyze and synthesize systems and design large-scale projects using the LSSE framework taking into consideration their goals, boundaries, stakeholders, complexities, tradeoffs, risks and unintended consequences.NUS Module Listing
DTS 5702 C3 Systems
This module provides the key underlying principles and concepts of C3 engineering and their application in the design, development and integration of C3 systems in modern armed forces.
Using a systems engineering approach, the module will also enable participants to have a good appreciation of the key considerations and challenges as well as good engineering practices associated with C3 design and integration with sensor and weapon systems.
Topics related to emerging trends, concepts and technologies will also be covered.
DTS 5703 Operations Research
This is an introductory module to operations research which will cover both deterministic and stochastic models for effective decision-making. Topics include mathematical programming (overview on models building and sensitivity analysis; computer-based solutions), multi-criteria decision analysis, reliability and maintenance, queueing theory and simulation. Relevant cases on military applications will be discussed.NUS Module Listing
DTS 5731 Fundamentals of Systems Engineering
This module is an introductory module providing an overview of the topic and a flavour of the details which should be more fully explored in depth through other modules. It explains systems, systems engineering, lifecycles, associated activities, products, applications, processes, models, methods and strategies.NUS Module Listing
DTS 5732 Artificial Intelligence and Data Analytics
This is an introductory module to artificial intelligence (AI) and data analytics (DA). It covers various topics of AI and DA. The AI topics include heuristic search, constraint satisfaction, logic and inference, and natural language processing. The DA topics include data preprocessing, data visualization, classification, model evaluation, decision trees, neural networks, deep learning, association analysis, and clustering.NUS Module Listing
DTS 5733 Sensors & Intelligence
This module introduces sensor and intelligence technologies and their applications in the operational context, mainly focusing on the most commonly deployed sensor technologies such as Radar and Electro-Optical (EO) sensors as well as established and emerging intelligence areas such as communications intelligence (COMINT), electronic intelligent (ELINT) and Open-Source Intelligence (OSINT).
The underlying technical principles for performance assessments in various environments, such as electronic warfare and design trade-offs will be covered and reinforced through the use of application examples.
DTS 5734 Guided Systems
The module covers the principles, technologies and operational aspects of smart weapon systems e.g. guided weapons, precision munitions and unmanned vehicles (UxVs). The interplay of various sub- systems for target identification & tracking, guidance/navigation, command and control and their impact on mission effectiveness will be examined with consideration of counter-measures and counter-counter- measures. Additional topics include advanced concepts for autonomy, interoperability and teaming and cooperation. The course will include case studies of these weapon systems in actual combat.
DTS 5735 Cybersecurity
This module introduces cybersecurity concepts and their applications. It aims to illustrate how systems can fail under malicious activities, and how the threats can be mitigated and managed. Topics include cryptography, communication channel security, system security, trusted computing, policy making, human factors, etc. Applications such as cloud security, IOT security, security operations centres, AI in cybersecurity, and case studies on well-known attacks will be used to reinforce the learning of various foundational concepts.
DTS 5736 Systems Design Project
The purpose of this module is to allow students to practise Systems Engineering Applications in realistic large scale defence/security problem solving. Students are required to adopt the systems approach in problem definition/framing and applying various technical disciplines taught in this programme, eg. C3, Sensors and Intelligence, DA/AI, Guided Weapons, Unmanned Systems, Cyber, Operations Research etc, in developing the system solutions. They are expected to conduct systems engineering studies to formulate and synthesize sound and cost effective systems solutions to address the operational requirements and scenario.NUS Module Listing
Quarters 3 to 5: Sep to Jun, at NPS or AFIT
With effect from MDTS 2013 Intake, students need to complete at least 40 module credits, including the Integration Project. Modules offered may change from year to year.