Information Session and Workshops: Master of Artificial Intelligence

Discover RMIT's Master of Artificial Intelligence program and get a taste of the classroom experience through immersive workshops conducted by our lecturers.

Event highlights

  • Learn about the Master of Artificial Intelligence program, including its transformative curriculum, career outcomes, entry requirements, scholarships and exclusive offers
  • Join program lecturers in two exclusive workshops to experience a real Master's classroom
  • Explore diverse study options at RMIT Vietnam and Melbourne
  • Meet one-on-one with our Senior Program Manager, leading lecturers and professional program advisors

Financial opportunities

  • 20% tuition fee reduction for all students enrolling in 2025, who have achieved an overall average of 3.0/4.0 (75%) in their Bachelor’s program*
  • 50% scholarships for those who successfully apply and meet criteria. A scholarship can be combined with other tuition fee assistance.

* Eligibility subject to program entry requirements

Notes

  • Presentations and workshops will be conducted in English.
  • The event will be filmed and photographed for media purposes. If you prefer not to be included, kindly inform the organisers upon your arrival.

Perks for attendees

  • Application fee waiver
  • Exclusive gifts upon successful program deposit

Workshop Sneak Peek: Experience a Taste of the Master’s Classroom!

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Get hands-on with Large Language Models (LLMs)! Learn the fundamentals of transformer architectures, tokenisation, encoding/decoding, and generative approaches like autoregressive models and Generative Adversarial Networks (GANs). Through practical exercises with GenAI techniques, participants will examine model behavior and apply LLMs to tasks like summarization and content generation.

Join us to move beyond "how AI works" to "how to make AI work responsibly." This workshop covers the AI development lifecycle, from data collection and training to evaluation and deployment, with a focus on ensuring responsible and trustworthy outcomes. Explore the foundations of responsible AI (fairness, transparency, accountability) and learn how to detect and mitigate bias through real-world case studies.

Register to join

Meet our faculty

Speaker Quang Tran

Senior Program Manager Quang Tran

With over 15 years of teaching and extensive professional experience in the USA, Canada and Vietnam, Mr Quang is a driving force in technology education at RMIT. His expertise spans coding, software engineering design, and the development of robust technical solutions. His research interests focus on the practical application of these skills within computer science and artificial intelligence education.
Speaker Tri Dang

Dr Tri Dang

Lecturer, Artificial Intelligence. He holds a PhD in Computer Science, with over 20 years of teaching and professional experience. His research focuses on Security & Privacy, Information Visualisation, and Human-Computer Interaction. His teaching areas include Data Structures & Algorithms, Database Systems, and Information System Security.
Speaker Thuy Nguyen

Dr Thuy Nguyen

Senior Lecturer, Artificial Intelligence. She holds a PhD from Austria. With over 15 years in teaching and research in Computer Science and AI, she has authored more than 70 papers and patents, received multiple awards, co-founded AI Academy Vietnam and trained CEOs, CTOs and IT specialists in AI and Machine Learning.
Speaker Ginel Dorleon

Dr Ginel Dorleon

Lecturer, Artificial Intelligence. He earned his PhD in France, focusing on using AI techniques to mitigate data bias within health decision-making systems. His research expertise encompasses Machine Learning, AI for Healthcare, Explainable AI, Data Bias, and Algorithm Fairness.
Speaker Vinh Dang profile image

Dr Vinh Dang

Lecturer, Artificial Intelligence. He holds a PhD in Computer Science from France. His teaching areas are Machine Learning, Data Analysis and Statistics. His research interests include cybersecurity, financial analysis and network learning.

About RMIT’s Master of Artificial Intelligence

Two postgraduate students, one male, one female, holding laptops and chatting in front of cables.

Gain a comprehensive education through core courses and electives that allow you to build expertise in AI development, machine learning, deep learning, and data science.

Tailor your pathway

  • Project Stream: Engage in a practical AI project with an industry partner or your current workplace to gain hands-on experience.
  • Research Stream: Focus your studies on a specific interest and complete a minor thesis, paving the way for further research or a PhD program.

Why Study Artificial Intelligence at RMIT?

Globally recognised degrees

RMIT is ranked #123 university globally and top 10 in Australia by QS World University Rankings 2025

Excellence in research

RMIT is ranked above world standard in Artificial Intelligence research by Excellence in Research for Australia*

Professional recognition

The Master of Artificial Intelligence program is conditionally provisionally accredited at the professional level by the Australian Computer Society (ACS)**

Industry connections

Collaborate with industry leaders such as Microsoft, Heineken, VinGroup, KPMG, Intel, De Heus, Ericsson, OUCRU, CIMB, VaticAI, Dizim.ai to gain valuable insights

* Excellence in Research for Australia reports are run by the Australian Research Council, part of the Australian government.

**The ACS is a signatory of the Seoul Accord, which accredits tertiary-level computing and IT qualifications globally. By joining ACS, graduates connect with over 47,000 members from Australia's tech community, boosting their chances of finding international employment.

Some of Our Graduates – Shaping The Future of AI

During the final semesters, students in the Master of Artificial Intelligence program choose projects or research topics that showcase their expertise and address pressing societal and business challenges.

Oliver Harold Joergensen, PhD Candidate

Oliver Harold Joergensen, PhD Candidate

“I chose the Research Stream to focus on Reinforcement Learning (RL), which has the potential to revolutionise industries through super-human performance. My thesis aims to enhance the robustness of RL methods for real-world applications. Studying at RMIT fuelled my passion for the field and led to a PhD position at Dalhousie University, where I plan to explore model-based RL and contribute to meaningful breakthroughs.”
Nguyen Thi Dieu Chi, Data Manager, Masterise Homes

Nguyen Thi Dieu Chi, Data Manager, Masterise Homes

“I conducted research supervised by Dr Minh Dinh, focusing on building optimal software to summarize online customer reviews for actionable business recommendations. Two courses, Data Structures and Algorithms and Social Media and Networking Analytics, equipped me with essential concepts and techniques to extract reliable business insights.”
Vy (Gavin) Nguyen, Co-founder, Hello Clever

Vy (Gavin) Nguyen, Co-founder, Hello Clever

“In my research stream, my thesis explored the dynamic role of emotions in conversations, identifying triggers for emotional shifts to enhance empathetic virtual assistants and improve conflict resolution. A highlight was working with Professor Jenny Zhang in Melbourne, whose guidance enriched my research approach and bolstered my confidence to pursue a PhD.”
Nguyen Hoang Khang, Data Scientist, Rackspace Technology

Nguyen Hoang Khang, Data Scientist, Rackspace Technology

“In the project stream, I developed an automated credit loan system to streamline the loan application process for clients and reduce information-gathering time for the financial industry. My lecturers kept us updated on new technologies, and Dr Vinh Dang's Deep Learning course balanced theory and practice effectively. Networking with my diverse cohort enriched my technical and soft skills.”
Phan Quoc Hung, PhD Candidate

Phan Quoc Hung, PhD Candidate

“The program sparked my passion for research, leading me to the research stream where I collaborated on an academic paper with Dr Quang Tran, leveraging my background in trading, finance, and economics to help develop a forecasting price system for agricultural products. Additionally, Dr Nguyen Hieu Thao made mathematics enjoyable by simplifying complex concepts, overcoming my aversion to the subject.”
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