CDT541/4 – Industrial Digital Transformation
This course introduces the concepts and process of industrial digital transformation by leveraging the emerging and next-generation technologies to accelerate the adoption of digital transformation across industries. This course navigates the world of digital ecosystem, understand the collision between traditional and digital business model, understand how technologies disrupted the industries and the impact of transformation on innovation and decision-making within industries.
At the end of this course, the students will be able to:
CDT542/4 – Digital Entrepreneurship
Technology has enabled a new age of entrepreneurship as entrepreneurs find digital tools that enable new ventures in order to exploit commercial opportunities around the world. This course provides students with expert guidance on using digital technology platforms to start new ventures. In addition, this course also gives students a background into digital entrepreneurship, some of the established models used in constructing a marketing strategy and a focus on how they can apply digital technology.
At the end of this course, the students will be able to:
CDT543/4 – Systematic & Lean Innovation Management
The TRIZ methodology focuses on systematic innovation and problem solving. All TRIZ tools including structured problem solving, function analysis, cause and effect chain analysis, ideality, S-curve analysis, etc., will be introduced. For Lean processes techniques, it introduces the concepts and principles of Lean processes techniques. Students will be introduced to the integration of Lean processes techniques with Six Sigma.
At the end of this course, the students will be able to:
CDT544/4 – Enterprise Architecture for Digital Business Transformation
Enterprise architecture (EA) is required to address the digital innovation and transformation challenges faced by today’s organizations. This course introduces students to an understanding of enterprise architecture concepts, design principles, practices, tools, and techniques so that they can stay ahead of the digital curve.
At the end of this course, the students will be able to:
CDS501/4 – Principles & Practices of Data Science & Analytics
This course introduces the basic goals and techniques in the data science and analytics process. It introduces theoretical foundations which include useful statistical and machine learning concepts so that the process can transform hypotheses and data into actionable predictions. The course provides basic principles on the important steps of the process which include data collecting, curating, analysing, building predictive models and reporting and presenting results to audiences of all levels. Data science programming languages and techniques are introduced.
At the end of this course, the students will be able to:
CDS506/4 – Research, Consultancy and Professional Skills
The course provides knowledge and effective skills that are required in research, consultancy, and professional practice. This course covers the fundamental areas in research. Students will be equipped with the necessary mindset, tools, and skills. Lastly, professional issues such as ethical and legal aspects will also be covered.
At the end of this course, the students will be able to:
CDT594/4 – Digital Transformation Project & Practicum
This experiential work-based course is designed to equip students to confidently help conceive, lead and execute digital transformation initiatives and develop new business models for existing organizations through the implementation of a consultancy project. Students are required to complete the practicum at their respective workplaces or their chosen/assigned organisations. Students work under the supervision of a lecturer and an industry supervisor. The students are required to solve a real-world problem or tap opportunities related to digital transformation during their practicum.
At the end of this course, the students will be able to:
CDT545/4 – Cyber Security in Digital Transformation
This course introduces students to the basic knowledge on cyber security and its applicability in digital transformation. Aspects and standard methods in related cyber security risk management will be explained. Students will be exposed to different applications of the knowledge on big data, cloud computing, Internet-of-Things, digital forensics, blockchain, etc.
At the end of this course, the students will be able to:
CDS504/4 – Enabling Technologies & Infrastructures for Big Data
Data science is advancing the inductive conduct of science, and is driven by big data available on the Internet. This course will explain the technologies and techniques to improve the access, security, and performance of big data processing, storage systems and networks.
At the end of this course, the students will be able to:
CDS511/4 – Consumer Behavioural and Social Media Analytics
This course provides a broad and interdisciplinary research and practise focusing on two areas: behavioural and web & social media analytics. Specifically, behavioural analytics concerns the process of systematically utilising multimodal data to model human behaviour when consuming products. The focus is on humans as consumers. This involves human-computer interaction (HCI), user behaviour modelling, computational models of emotions, and emotion sensing and recognition. Social media analytics concerns the strategies to leverage powerful social media data concerning customer needs, behaviour, and preferences. Students will learn the strategies to derive insights from the above-mentioned data that are crucial for business decisions. Students will be exposed to social media analytics tools.
At the end of this course, the students will be able to:
CDS512/4 – Business Intelligence & Decision Analytics
The course will focus on the knowledge and skills to select, apply, and evaluate business intelligence and decision analytics techniques which discover knowledge that can add value to a company. The course will also discuss innovative applications and exploitation of the current techniques and approaches related to business intelligence, performance measurement, and mathematical modelling to facilitate the decision-making process in business and operations.
At the end of this course, the students will be able to: