After graduating with qualifications in the Science, Technology, Engineering and Mathematics (STEM) arena, Wang Ziqiao and Ye Zhiqiu could have had their pick of job opportunities.

However, the duo, who both hail from China, decided not to join the workforce. They saw how globalisation and technological disruption were affecting industries and job roles. Change was on the horizon; Ziqiao and Zhiqiu felt that they needed to be able to access opportunities beyond what their Bachelor’s Degrees in Environmental Science and Engineering respectively had prepared them for. They needed something more than classroom knowledge so that they could stand out from other fresh graduates. They needed a graduate qualification that would help them become in-demand, future-ready talents.

The multidisciplinary nature of the programme was also a draw (since it involves a collaboration among five different academic units at NUS: Faculty of Science, School of Computing, NUS Business School, NUS Institute of Systems Science, and NUS College of Design and Engineering).

On top of that, NUS enjoys a stellar academic reputation, with 16 academic programmes placed in the top ten globally in the Quacquarelli Symonds (QS) World University Rankings by Subject 2022. 

Won over by the curriculum structure and the quality of education offered by NUS, they applied for the MSc (Industry 4.0) programme and arrived in Singapore to commence their studies.

A Sound Education

Once they became immersed in the MSc (Industry 4.0) programme, Ziqiao and Zhiqiu found themselves learning about a range of topics, including data analytics. Incidentally, the module Data Analytics for Sense-making (IND5003) is one of Ziqiao’s favourites. It covered applications in multiple domains, from consumers to human resources to retail, allowing him a first-hand experience in studying data in various environments. Through his classes, he picked up tools and techniques for performing supervised and unsupervised learning of structured and unstructured data.

Zhiqiu, on the other hand, found the course Foundations of Machine Learning (DSA5102) to be her most memorable. The course introduced to her the fundamentals of machine learning, and she had the chance to delve into how these systems work. She was also fond of the Strategic Procurement in a Digital World (IND5024) module. Although not part of her Graduate Certificate coursework, it allowed her a deeper insight to how companies have different strategies with regards to procurement and their roadmaps for digital transformation.