This module covers the basic architecture of microcontrollers and the interfacing of various input and output devices to the microcontroller.  It provides knowledge and skills on programming the microcontroller to interface with the real world through the input and output devices.

This module provides you with working knowledge on microcontroller architecture, the features and characteristics of the internal peripherals in the microcontroller, such as interrupts, Timer and Pulse Width Modulation in order to design and implement an embedded system that involves hardware and software interfacing.  The subject also covers the features of evolving microcontrollers that support Industrial Internet of Things (IIoT) applications.

This module equips student with the knowledge and skills essential for data acquisition from the real world through sensors for further processing and control of equipment, as well as integration with other subsystems through networking.. Commonly used industrial connectivity standards and fieldbuses, as well as relevant hardware and software interfaces suitable for such integration, are also covered.

This module provides you with the basic knowledge of designing and implementing of a database, and the appropriate retrieval of the data through queries from the client application through a business logic layer.

This module covers the development of applications on mobile and wireless computing platforms. It provides an overview of Mobile Web and Mobile Applications, their importance and benefits, as well as the technologies and methodologies for their development, such as the architectures, frameworks, standards, programming languages, design process and tools.

This subject introduces the concepts of web application development. Topics covered include web page design, front-end and back-end web development and web deployment.

This subject provides knowledge, skills and design approaches in using embedded systems, sensors, actuators and appropriate data communication technologies such as sensor networks, edge and cloud computing to build and setup an IIOT environment. A systems engineering approach will be adopted, under which you will review key technologies from prior learning for the different levels of the IOT (Internet of Things) stack and figure out how these different levels could be integrated to form complete IIOT systems in Advanced Manufacturing.

This subject provides the essential concepts and skills needed for implementing digital transformation in smart manufacturing plants. It covers the application of industrial software platforms to wirelessly interconnect sensors, Internet of Things (IoT) devices and equipment. The students will learn to develop dashboard for acquiring, analyzing and displaying data that is commonly found in Advanced Manufacturing. Modern approaches in activation of hardware and software responses when interventions are required for process improvement or corrective actions are also covered in detail.

This subject introduces the security and privacy issues involved in the implementation of Internet of Things (IoT) applications and services. Topics covered include cryptography, capability, access-control mechanisms, authentication models and privacy support through data abstraction, integration and data synchronisation.

This subject covers the data analytics lifecycle, including gathering, cleaning, processing and visualizing of data. Exploratory data analysis methods, descriptive and predictive analytics and the presentation of insights will also be covered.

This module provides you with basic knowledge and hands-on digital transformation skills on rapid multi-experience application development and integration of users, tasks and systems towards enhancing productivity, human augmentation and automatic data-driven decision-making. It covers techniques on how to leverage on data from information systems and IoT devices for agile response and productivity. This subject will enable you to automate data-driven decision making through integration of advanced analytics and learning models to applications.

This module provides students with the fundamental concepts of Artificial Intelligence (AI) and Machine Learning (ML). It covers knowledge and skills in AI techniques and tools to build intelligent learning models from real-world data, through training, testing, validation and optimisation. Through hands-on group projects, they will build AI-based applications to add intelligence to existing systems.