Huy Tran Nghiem is currently pursuing his Master’s degree in Computer Science at USC. He has worked as a Data Analyst upon graduation and was motivated to come back to a graduate school and learn more about data science. The practicality of data science intrigued his desire to solve a real-world problem such as diagnosing cancer or predicting the onset of dementia using machine learning. Like other students, he encourages students to work on practical, fun projects.
- What are your undergraduate and graduate majors?
I am pursuing my Master’s degree in Computer Science at USC. For my undergraduate, I double-majored in Applied Mathematics and Public Health Sciences from UC Irvine.
- What was your turning point (event, person, or work) that motivated you to study data science?
I have always had an active interest in quantitative fields, hence my undergrad majors. After graduating, I worked in various capacities as a Data Analyst. This period coincided with the bloom of social media and big data, further motivating my desire to learn more about data science.
- Have you worked in the field of data science (either a work or a research experience)? Please pick one work experience that you enjoyed the most and explain it in detail.
In addition to my professional experience, I have participated in research in the field of social science. It has been an amazing opportunity to leverage data science into actionable findings, especially for policymakers. I enjoy learning and combining the domain knowledge in social research and the tools in data science to shed insights. In recent years, the advent of big data and the bloom in computational resources has also reached social science, enabling new directions into existing topics. I am grateful to be a part of this scientific intersection.
- Looking back to the beginning of your journey, do you have any advice for students or beginners who want to learn more about data science?
Now is a wonderful time to learn about data science. There are so many resources for beginners to get the basic foundation. I recommend certified courses from platforms like Coursera, Udemy, etc. to get a comfortable introductory experience. But pursuing a degree in data science or related fields is, of course, a wonderful way to receive a systematic education. And finally, I cannot stress enough the importance of working on practical projects, especially applying your skills on fun problems to expand your repertoire.
- How will you apply your skills to solve real-world problems? Why do you care about solving this problem?
In a way, I have been doing this through my research experience. The beauty of data science lies not only in its theory, but also in its real-world usefulness. I am particularly interested in leveraging data science in the biomedical field, such as using machine learning to diagnose cancer, diabetes or predict onset of dementia. These are all projects that have profound and far-reaching impacts on human lives.
- Why do more people need to study data science?
If I haven’t raved about data science enough, it’s beautiful, it’s fun, it’s useful…oh did I mention that it pays J?