AI fundamentals in RMIT's Master of AI

AI fundamentals in RMIT's Master of AI

With so many new AI applications disrupting numerous industries, alongside the fact that many international conglomerates have AI as a strategic pillar for future growth, you may wonder what it takes to become an AI professional? Read on to discover how RMIT’s Artificial Intelligence class helps students prepare for the workforce!

As artificial intelligence has leaped to the fore of social interest with generative AI applications, such as ChatGPT and Midjourney, as well as become major strategy pillar for numerous companies, having the necessary skills as an AI engineer and developer are increasingly in demand. 

The Artificial Intelligence course, as part of RMIT Vietnam’s Master of AI seeks to impart much the problem-solving and technical acumen that an AI professional requires to stand out in the workforce. 

Speaking with Senior Lecturer Thuy Nguyen, she notes that “in terms of knowledge, students learn a wide range of topics from AI fundamentals to reinforcement learning, the history of AI, the difference between narrow and general AI, the challenges, and ethical considerations associated with AI applications. AI methods and techniques, including heuristics search, knowledge representation and reasoning, automated planning and intelligent agent systems, amongst others, are also taught.”

Students pointing at white board

There are several industry guest speakers who have visited the AI class to talk about how AI is being utilised and making impact in their businesses.  Mr. Colin Blackwell was one recent visitor. He is the current Chairman of the Human Resources committee for the World Bank's Vietnam Business Forum and is the Founder of Enablecode & Hyperion Fintech AG. “Mr Blackwell has a wide range of experience in AI application, especially in human resource and intelligence management. His visit helped broaden our student’s understanding of AI’s impact on society,” Dr. Nguyen states. 

Another guest speaker was Mr. Le Minh Hung, from Bosch’s AI team. Mr. Le gave an insightful overview of how AI is revolutionising manufacturing, along with optimisation problem use cases for both AI and Machine Learning. 

Students completing the module will have gained strong problem-solving skills, enabling them to tackle complex AI challenges and devise effective solutions. Dr. Nguyen says that “reinforcement learning skills, as an example, are essential for training agents to make sequential decisions based on rewards by interacting with their environment. It has applications in robotics, games, and optimization, enabling students to develop autonomous and adaptive systems.”

The techniques offered in the AI course specifically, and the Master of AI in general can be applied to a wide variety of artificial intelligence problems and help serve as the foundation for further study in any application area that students choose to pursue. 

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