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AI, semiconductor courses test training capacity

by Vietnam Today10 September 2026 Last updated at 12:32 PM

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VTV.vn - Demand for AI and semiconductor degrees is rising in Vietnam, with more applications and higher admission scores this year. However, these fields rely heavily on practical training.

Universities are now under pressure to expand teaching capacity, update their courses and provide enough hands-on experience for students.

At the University of Science, Viet Nam National University Ho Chi Minh City (VNU-HCM), two training cleanrooms give semiconductor students basic experience with cleanroom procedures and fabrication. Capacity is limited, so this year's intake remains at 70 students.

Assoc. Prof. Vu Thi Hanh Thu of the Faculty of Physics & Engineering Physics, University of Science, VNU-HCM, said: Laboratory training is essential for semiconductor students. They need hands-on experience in cleanrooms and fabrication, and they need to know how to operate advanced equipment. These are skills they will need when they enter the industry.

Vietnam aims to train at least 50,000 people with university degrees or higher for the semiconductor industry by 2030. However, scaling up is expensive. Semiconductor laboratories cost a great deal to build and run. AI training brings another expense: computing power and paid access to commercial models.

Lam Quang Vu, Vice Dean of the Faculty of Information Technology, University of Science, VNU-HCM, said: "Using commercial AI models costs money because access is charged by token. For student projects, the main challenge is having enough budget to give students regular access to these tools.

With budgets still limited, universities are sharing laboratories, using facilities in related departments and seeking support from companies.

Assoc. Prof. Tran Thien Phuc, Vice President of the University of Technology, VNU-HCM, said: "Some companies have given us access to their servers and workstations for design work. This kind of support is very useful. If we can expand partnerships like this, it will give students much better access to the tools used in the industry".

For AI and semiconductor training, classroom knowledge alone is not enough. Students need the facilities and practical experience to solve real technical problems before they graduate. That is the foundation for building the skilled workforce that these industries will need.

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