Why is the Diploma in Computer Engineering the best course for me in 2025?

This module provides a general overview of computer networking. It provides a general introduction to networking terminology, concepts, devices, functionality, applications and standards required for computer networking. Students will learn to build simple LANs, perform basic network and service configurations, and implement IP addressing schemes.

Introduces students to the knowledge, understanding and design techniques necessary to enable them to design simple combinational circuits using commercial SSI and MSI integrated circuits. Additional topics covered include introduction to simple sequential logic circuits such as flipflops and mono-stables

Builds on basic material covered earlier with advanced topics such as adders, multiplexers/ demultiplexers, decoders/ encoders, counters and shift registers and some application examples of these circuits.

Equips students with the knowledge of drawing office practice, ISO drawing standards and drawing skills using latest AutoCAD software and the ability to read and produce good technical sketches and projection drawings as a form of engineering communication. The module will cover basic 2D drawings, isometrics and orthogonal projections, 3D-Design using Autodesk software for 3D-Printing & Laser cutting assignments, and the use of workstation based CAD/CAM software for computer-aided drafting.

This module equips students with engineering fundamentals set in the context of CDIO (conceive, design, implement and operate) in real-world systems with basic electronic projects. It aims to nurture students toward self-directed learners by giving them a challenging environment to plan, manage, review and extend their learning outcomes using growth mind-set and meta-cognitive learning systems in achieving their electronic projects. Besides, students will be exposed to a range of generic process skills such as troubleshooting skills, creative and critical thinking, teamwork and communication.

This module teaches students to write programs in a structured way. It emphasises on good programming techniques and covers topics on fundamental data types, input / output, selection control and loop constructs, functions and basic structures such as arrays. At the end of the module, the students will be able to write programme for simple engineering application that runs on computer and simple engineering application that runs on basic embedded system and control it.

This module covers the fundamental concepts of electricity. Understanding and application of electrical phenomena are further enhanced using circuit simulation on worked examples and tutorial problems and via hands-on sessions. Topics covered include scientific notation, engineering notation, metric prefixes, basic elements of an electrical circuit, definitions of energy and power, power sources, measuring instruments, DC and AC concepts, simple series and parallel networks, electromagnetism, inductor, inductance, transformers, capacitor and capacitance, characteristics of inductor and capacitor in DC, Kirchhoff’s Voltage and Current Laws, Current and Voltage Divider Rules and Superposition Theorem.

Extends the basic concepts onto other electrical and electronic devices. Topics covered include: Semiconductor physics, semiconductor devices such as diodes, special diodes and bipolar transistors, transducers such as thermistors, and application of operational amplifiers, complex numbers and concepts of phasors, phasor angle, phasor diagrams, reactances, impedances, susceptances and admittances. Upon completion, this module consolidates students’ foundation of the electrical and electronic engineering.

This module equips students with basic mathematical skills and knowledge in Algebra and Trigonometry to enable them to understand and solve engineering problems encountered in the course of studies. It also serves as a foundation for subsequent mathematics modules.

This module equips students with the necessary mathematical knowledge and skills to solve problems encountered in their course of study. Among the topics covered are Determinants and Matrices, Complex Numbers and Calculus.

This module aims to help students discover their strengths, values and interests. It also supports students in making informed educational and career choices to achieve their career aspirations.

Develop essential AI literacy and human-AI collaboration competencies for the future workforce. Gain foundational AI knowledge aligned with Singapore's Generative AI Skills Framework while applying creative and computational thinking. Learn to use AI as a thinking partner for critical evaluation, ethical awareness, and value creation in domain-specific projects addressing the Sustainable Development Goals (SDGs).

Find out what goes into a healthy and productive team where ideas, insights, and responsibilities are shared meaningfully. Sharpen your interpersonal and communication skills to collaborate effectively in a digital environment.

Develop critical and analytical thinking skills, along with the ability to present your point of view with credible and relevant evidence. Enhance your knowledge and appreciation of local and global issues covered in the 17 SDGs, with a focus on the former.

Develop essential workplace communication skills to communicate effectively in professional settings through written documents and oral presentations. Strengthen your ability to adapt messages for different purposes, audiences, and contexts, while applying sound judgement in the use of information sources and AI tools.

This is an introductory module to Cloud Computing. It introduces students to the fundamental knowledge and overall understanding of cloud computing concepts. Using contents from Amazon Web Services (AWS)’s “Cloud Practitioner” course, this module provides a detailed overview of cloud computing concepts, core services, security, architecture, pricing, and support. Students will apply their cloud computing knowledge in practice with elements of hands-on in lab practical work and projects. This training will prepares students to progress towards practical experience with cloud computing, and the industry recognised “AWS Certified Cloud Practitioner” exam, which represents the first milestone to achieve while working through the AWS Academy Cloud Computing Architecture courses.

This module begins with an introduction to Python programming, equipping students with the foundational skills necessary to write and understand Python code. It then introduces the concepts and various algorithms of Machine Learning and edge AI computing. This will enable students to apply AI and Machine Learning in real-world application projects. Additionally, the module covers the design and data studies needed to drive organisational decisions and insights using statistical and computational techniques and tools, algorithms, predictive data modelling, and data visualisation.

Introduces the use of microcontrollers in a range of system applications. Students are taught how a microcontroller works, how to program it, and the use of microcontroller. In addition, students will learn basic analogue and digital support circuitry, sensors and actuators/displays required for a microcontroller based application. This module allows students to develop a project conceived around a microcontroller system with sensors and output devices.

This module introduces students to the foundational infrastructure layer that underpins modern computing and AI systems. Students develop a grounding in AI ecosystem concepts, accelerated computing, networking, and GPU architecture, alongside working proficiency in Linux, virtualisation, and containerisation. This prepares students for the growing demands on compute infrastructure driven by the rapid adoption of AI technologies. Upon completion, students will be able to administer Linux environments, deploy containerised applications, and articulate how GPU-accelerated infrastructure supports AI workloads.

The module is designed to provide students with further knowledge in mathematics and analytical skills to solve engineering problems encountered in their studies. Among the topics covered are Calculus, Ordinary Differential Equations, Laplace Transforms and Fourier Series.

Develop the ability to understand, question, and use data effectively in everyday and workplace contexts. Learn to evaluate information, select appropriate digital tools, and use data responsibly to support informed decision-making and communication.

Work in multi-disciplinary groups to apply design thinking methods, backed by research and qualitative data, to tackle local sustainable issues mapped to the SDGs. Tap into knowledge and skills learnt in CCC modules to create innovative prototypes for real-life issues faced by local communities.

Please refer to Elective Modules Framework for more information.

Please refer to Elective Modules Framework for more information.

This module provides an introduction to DevOps (Development Operations) and its role in the Software Development process today in the development of AIoT (Artificial Intelligence + Internet of Things) applications. The basic Software Development process is explained to the students and the role and as a basis to of explaining how DevOps has become an essential component the modern Software Development process. Students will have hands-on experience using DevOps tools such as Git / Github, Jenkins, Docker, Kubernetes, etc. To consolidate the student’s grasp of DevOps and its importance in the Software Development lifecycle, students will implement an AIoT application supported by a full DevOps infrastructure.

This module aims to teach student fundamental knowledge, skills and tools necessary to become proficient in developing end-to-end web applications. Through this course, students will gain practical experience in both front-end and back-end development, enabling them to design, implement, and deploy fully functional web applications.

Provides an understanding of network fundamental and computer network routing principles. Students will learn the difference between routing and routed protocols and to configure routers for LAN communications. Students will also be equipped with network troubleshooting skills and able to discuss LAN design issues involving multiple routers at the completion of the module.

Provides students a complete foundation in Wireless Networking and LAN Switching. Wireless Networking covers basic RF theory, hardware installation, configuration and management, troubleshooting, security, and site surveying. LAN Switching covers basic switch concepts and configuration, virtual LANs, VLAN protocols and Inter-VLAN Routing.

The Internship Programme aims to provide students with an authentic on-the-job work experience in an engineering, or technology-enabled business field, to prepare them to be truly work-ready. Students will also be able to establish an industry network and learn from the experience of working professionals. Students will undergo a structured learning programme, including attending safety induction and participating in the industry projects as part of their internship. The intent of the programme is to enable students to apply and enhance their range of technical skills, hone their knowledge in areas such as professional ethics, role and responsibility of engineers, and understand the business environment in which companies are situated – as advocated by the CDIO syllabus.

Get a head start in your career with the necessary skill sets, knowledge and tools to create your personal brand. Learn effective strategies to set yourself apart from the competition, build positive connections, and cultivate adaptability for success in the future workplace.

Please refer to Elective Modules Framework for more information.

- This module equips students with the conceptual and applied knowledge needed to support the deployment and integration of compute, network, and storage infrastructure for AI workloads at scale, with particular emphasis on the physical and architectural engineering of high-density AI compute systems. Students engage with GPU server architecture, AI hardware platform integration, high-performance networking for distributed AI workloads, and storage architecture for AI data pipelines. Students are also introduced to the power and cooling demands of rack-level AI compute infrastructure, developing an awareness of how these physical constraints shape infrastructure design decisions.

This module develops students' ability to monitor, operate, troubleshoot, and optimise AI infrastructure, covering key operational tasks from day-to-day observability and incident management to performance tuning and capacity planning. Students work with monitoring and operations tools across both cloud-managed and enterprise-managed AI infrastructure environments, building the diagnostic and operational skills needed for roles in AI infrastructure operations and cloud operations. The module also introduces managed AI platform services and Infrastructure as Code practices that are commonly used in modern AI operations workflows.

This is an introductory module to architecting cloud-based IT solutions using public cloud services. Using contents from the “AWS Academy Cloud Architecting” course, this module covers the fundamentals of building IT infrastructure on AWS. Students will learn to optimize the use of the AWS Cloud by understanding various AWS services and how to best-fit them in cloud-based solutions. Students will learn the best practises of architectural solutions to serve different industries, different types of applications, and different size of the business. Throughout the module, students will experience the building of a variety of infrastructures. This module helps students prepare for the “AWS Certified Solutions Architect – Associate” exam.

This module provides a comprehensive introduction to cloud-native application development. It equips students with the foundational knowledge and tools required to build modern, scalable, and resilient applications in cloud environments. Throughout the course, students will gain hands-on experience with various essential technologies, including microservices architecture, containerisation, and continuous integration and delivery (CI/CD), which are crucial for developing cloud-native applications.

This module provides an in-depth exploration of edge computing, a transformative technology that processes data closer to the source, reducing latency and bandwidth usage. Students will explore the architecture, technologies, and applications of edge computing, including its integration with IoT and cloud computing. The course also addresses the critical aspects of security and privacy in edge computing environments. The module is designed to equip students with the knowledge and skills needed to design, implement, and manage edge computing solutions across various industries.

To provide students with knowledge and understanding of low cost and small size but powerful embedded computer systems, used commonly for industrial and home devices. The practical use of such systems is shown by how the Internet is used to control common devices.

This module provides students with the skills to understand and design smart infrastructures, focusing on essential technologies for building sustainable smart cities. Key topics include smart city applications, networking basics, M2M communication, sensor networks, IoT security, data analytics, video analytics systems, and smart city application design. Through these topics, students will learn to create and manage efficient, secure, and innovative smart systems that promote sustainability.

The aim of this module is to introduce the students to the basic knowledge of 5G Technology, and the potential of 5G technology in enabling the development of new business models and advanced applications. Students will learn about the key domains of 5G technology: wide bandwidth, low latency, and massive IoT, and the use cases that tap on these characteristics of 5G connections. This module will also briefly cover other wireless technologies, for comparison with 5G and also as alternative connection solutions. This module will discuss some use cases where the combination of 5G, Artificial Intelligence (AI), and Internet of Things (IoT) technologies can bring to the creation and implementation of some emerging engineering applications.

This module demonstrates structural organization and hardware design of digital computers. Various fundamental mechanisms such as register transfers, micro-operations, control units and timing, instruction set design, and input/output devices will be explained. It will also introduce the principles and practices of high-performance computing (HPC), including the use of Graphics Processing Units (GPUs).

This module provides a theoretic understanding and hand-on in data structures and algorithms commonly encountered in computer programming. Student will receive further understanding in data types, construction and operations of more complex data types and structures beyond their previous programming modules. Principles and reasoning of algorithms and methods commonly encountered will be covered. Constructions and associated operations of linked lists, stacks, queues, and binary trees will be included. Applications associated with common data structures and algorithms will be introduced.

This module provides a comprehensive understanding of deep learning. Students will learn the core concepts of neural networks, including how to design, implement, and train them using Python and TensorFlow. Key topics include the basics of convolutional networks, sequence models, and essential techniques for model optimisation. The module emphasises practical applications, enabling students to apply deep learning techniques to solve real-world problems.

This module introduces quantum computing, starting with the basics of quantum theory and how it differs from classical computing. Students will learn the concept of qubits, their interactions, and the mechanics of quantum computing. Students will learn various technologies and setups for quantum computers, programming languages relevant to quantum computing, and recap necessary mathematical concepts. It also introduces applications of quantum computing in fields like machine learning, simulation, AI, and cryptography.

Covers secure network design and the technologies for securing the perimeter of a network. Security features of perimeter devices (routers and firewalls) including various filtering techniques (e.g. packet filtering, Proxy filtering and Stateful filtering) are covered. Other topics include Virtual private network, Intrusion detection and prevention, disaster recovery and business continuity. In laboratory, students will learn to configure Cisco routers and ASA (Adaptive Security Appliance) for De-Militarised Zone, Virtual Private Network, and authorization.

Teaches the use of Network Analysis and Packet Capture tools to analyse data flowing through a network. Students will learn how to use analysis tools to perform forensic tests to determine the nature of any security breaches and exploits. The module will also use case studies to determine the nature of different exploits used by hackers on the Internet.

The aim of this module is to introduce the core security concepts and skills needed to monitor, detect, analyse and respond to cybercrime, insider threats, advanced persistent threats, regulatory requirements, and other cybersecurity issues facing organizations. It emphasizes on the practical application of the skills needed to maintain and ensure security operational readiness of secure networked systems. The module takes the contents from Cisco Certified CyberOps Associate certification course.

This module introduces students to the necessity of acquiring knowledge of Internet security and the inner workings of a hacker attacking a server over the Internet. Students will be introduced to the concept of AI and Machine Learning for Cybersecurity. In addition, students will delve into using various applications of AI tools and techniques to detect and mitigate various cyber threats and attacks.