NCI/ Intersect Training Partnership – Teaching and Learning Stories

Janil Perez
17 Aug 2022

Teaching story from Intersect eResearch Trainer: Khuong Tran

By Jianzhou Zhao & Jonathan Arthur

Khuong Tran is a Ph.D. candidate and a Research Assistant at the University of Technology Sydney. His research involves modelling AI-enabled agents to perform decision-making under uncertainty using reinforcement learning and deep learning architectures. Khuong is enthusiastic about teaching and sharing his knowledge of digital tools and technologies (such as programming, and applied machine learning) and has been an eResearch Trainer at Intersect for 3 years. Khuong delivered over 14 courses throughout the NCI/Intersect training program and we asked him to share some of his teaching stories from the program. 

In terms of his motivation for being an eResearch Trainer at Intersect, Khuong told us that Intersect provides a great opportunity for him, as a PhD student, to exercise his knowledge by teaching people how to use digital tools. As an international student, this job also provides extra support for his study and life in Australia. “I have also got a chance to talk to researchers from different universities and institutions and build networks when delivering the courses”, Khuong also mentioned. 

“Thanks to the popularity of Python frameworks, like Numpy, Pandas, Seaborn and Scikit-learn, people with no or minimal background in programming can jump in and start to manipulate high dimensional arrays or perform visualisation with just a few lines of code. These things were not easily accessible [when I started my Ph.D.]” 

Khuong emphasised that the Intersect courses facilitate the implementation of such tools in research, 

“We are not teaching all the theories of programming. Instead, we raise the awareness of the tools/technologies that are ready to use, and teach how to read the documentations and to utilise them immediately after the courses. This is extremely beneficial for researchers who have no background in Computer Science or Engineering.”

“It is encouraging to see that more researchers from, for instance, the Social Sciences or the Business School, are adapting the programming and HPC tools for their research”, Khuong further added. He acknowledged the contribution of Intersect courses in terms of helping researchers build their confidence to transition from conventional tools to more cutting-edge technologies, resulting in significant improvement in their research productivity. 

“In terms of machine learning (my research field), there are many tutorials out there and as a beginner, it can be hard to pick the appropriate learning material. The Intersect machine learning courses, normally delivered in three consecutive weeks, cover the fundamentals, terminologies, workflows, and more importantly, the applications of the relevant packages and functions. From my perspective, this would otherwise take beginners several months through the self-paced training in order to reach the same level of understanding of Intersect courses.”

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