Curriculum

The programme equips students with deep conceptual grounding alongside applied, industry-facing training, preparing them to navigate and lead within AI-mediated social, cultural, and organisational environments.

To complete the programme, you will need to attain a total of 24 units of coursework, comprising of 4 core courses and 4 elective courses worth 3 units each. 

The programme structure is subject to change without prior notice.

Period of Study: One year
Study Mode: Full-time
Language of Instruction: All required and elective courses are taught in English

Term 1

Sep – Dec

2 core courses + 2 elective courses

Term 2

Jan – Apr

2 core courses + 2 elective courses

Course List

Required courses (12 units)
COMM5010 AI Foundations for Communication (3 units)
This course introduces students to the computational foundations of artificial intelligence (AI) and their implications for communication research and practice. It covers key concepts such as machine learning, classification, modeling, prediction, natural language processing, and generative systems, with a focus on how these technologies shape media production, audience engagement, creativity, and organisational workflows. Students learn to interpret how AI systems function, where they succeed or fail, and how their underlying logics influence communication industries. By connecting technical foundations with real-world applications, the course equips students with the conceptual and analytical literacy required for more advanced studies across journalism, global communication, advertising, corporate communication, and new media.
This course examines how artificial intelligence(AI)reshapes communication systems, industries, and public life through the analytical lens of Human– Machine Communication (HMC). It explores how people interpret, interact with, and are affected by AI agents embedded in media, platforms, workplaces, and civic environments. Drawing on sociological, infrastructural, cultural, and political–economic perspectives, students analyse scenario- based problems such as misinformation, automated decision-making, audience fragmentation, labour shifts, and algorithmic inequity. While not framed as a solutions course, it aligns with the University’s commitment to social impact and Sustainable Development Goals (SDGs)-related priorities by investigating how human–machine relations intersect with inclusion, sustainability, governance, and justice. Students learn to assess how AI-driven HMC dynamics contribute to broader patterns of societal change.
This course adopts a hands-on laboratory format to equip students with practical competencies in applying artificial intelligence (AI) tools within communication workflows. The course introduces content-generation systems, data visualisation tools, automation platforms, and emerging media technologies used in journalism, advertising, public relations, and digital communication. Students engage in guided tasks, collaborative exercises, and small-scale prototyping to explore the practical capacities and limitations of AI. Emphasis is placed on experimentation, iterative learning, and reflective practice, enabling students to connect technical skill-building with professional and ethical considerations.
This course offers a collaborative, creative, and practice-oriented capstone experience. Students work in cross- stream teams to design, build, test, and showcase artificial intelligence (AI)- augmented communication projects. Through themed challenges, micro- workshops, public demonstrations, and peer feedback sessions, the festival encourages students to synthesise conceptual understanding with practical experimentation. Projects may include campaigns, data stories, interactive media pieces, journalistic tools, or strategic prototypes. This course emphasises creativity, interdisciplinary collaboration, and critical reflection, preparing students to engage thoughtfully and innovatively with AI across professional communication domains.
Elective courses (12 units)
COMM5540 Strategic AI in Corporate Communications: Navigating Creativity and Complexity (3 units)
This course examines the transformative role of artificial intelligence (AI) in the strategic communication ecosystem, including creative campaign development, data-driven audience engagement, reputation management, and crisis communication. Students will critically analyse global cases in which AI played a pivotal role—whether driving award-winning innovation or triggering ethical concern and public scrutiny. The course further introduces frameworks for responsible AI strategic communication, including governance, transparency, bias mitigation, and public trust. By the end of the course, students will be equipped to navigate the complexities of AI-driven strategic communication and will be able to design, evaluate, and manage AI- enabled communication initiatives that balance innovation, strategy, ethical responsibility, and accountability.
This course will analyze the challenges and opportunities presented by new technologies, changing audience behaviors, and shifting media landscapes. We will scrutinize important innovation cases and discuss the ways in which journalism can adapt to meet the needs of a changing world. Through a combination of lectures, discussions, guest talks, case studies and newsroom practices, the course emphasizes both the normative roles of journalism and a grounded understanding of what is really happening in the global journalism industry.
This course explores emerging technologies as unsettled and unsettling forces reshaping social, political, economic, cultural, and interpersonal life. Using intersectional and global communication perspectives, it examines how technological transitions generate new relations of power, precarity, and possibility. Rather than treating technologies as inevitable, the course analyses moments of disruption, shifting infrastructures, and contested futures being built through policy, design, and everyday practice. Students learn to identify critical entry points for negotiation, intervention, and transformation, developing the conceptual and practical tools needed to imagine and articulate more just, liveable technological futures.
Artificial intelligence (AI) for advertising is a timely course to explore and understand the role and functions of AI used in advertising campaigns. Students will critically discover and examine the transitional and progressive use of AI agentic roles in the traditional human agentic advertising industry by comparing nature and effects of traditional and AI campaigns generated for the same client account. This course will adopt the mens et manus (head and hand) approach in applying knowledge and integrating AI skills into creating real life campaigns. This is also a collaborative course bringing in sharing from AI experts and practitioners for various topics.
This course is designed for students pursuing strategic roles in the new media industry, equipping them to apply data and AI strategies to real-world challenges. Bridging the gap between strategic vision and technical execution, it delivers essential data science concepts and practical processes for effective collaboration with data teams on projects that drive measurable business impact. Emphasizing strategic problem-solving and ethical data and AI practices, the course uses case-based learning to build multidisciplinary capabilities in strategy, analytics, data visualization, modeling, and machine learning. Students also explore the latest AI developments, preparing them to address complex challenges and leverage emerging opportunities.
This course explores the art and science of crafting precise, efficient, and contextually appropriate prompts to interact with artificial intelligence (AI) models, particularly large language models (LLMs) and Multimodal systems. This course bridges theoretical AI concepts with practical application, covering prompt design principles, optimization strategies, ethical considerations, and real-world use cases. Students will engage in hands-on projects to develop, test and refine prompt for diverse domains such as education healthcare, creative industries, and research.
Emerging technologies such as online social networking and mobile apps have deeply embedded in (become inseparable parts of) our lives. They alter our communication behaviors and generate Big Data for studying human psychology. This course will introduce students to computational methods and tools for analyzing Big Data to reveal new insights about communication and psychological processes. Topics include computer-mediated communication, characteristics of Big Data, computational text analysis, digital field experiments, and generative artificial intelligence.

Admission

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About the Programme

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