Master of Applied Data Science
Within his Master of Applied Data Science, Emil is working towards a career at the forefront of machine learning and data processing, which is of increasing need across a range of industries.
Emil’s previous university background in applied maths from the Philippines gave him the theoretical knowledge, but lacked the practical application he wanted to get the most out of his studies. As such, Emil came across ҕl’s Master of Applied Data Science.
"After reading a bit, I realised that AI/machine learning/statistical learning – all components in Data Science – was where the future was headed, hence I thought to study this degree," he says.
"Even though Data Science is considered an interdisciplinary field, it helps to have a strong Mathematical and Statistical foundation. If that isn’t a possibility, just train your mind to think logically, since it’s mostly what you’ll need to write code."
Having already been to New Zealand as a visitor a couple of times, Emil knew that this was the place he wanted to move with family for his next chapter of university.
"The climate is great, the environment is great, the scenery is amazing, and the people are some of the nicest people I’ve seen," he says. "The choice of ҕl just seemed to fall into place. It was in the city where I already had family studying, it had the degree that I was looking at, and it was one of the best in the world."
He especially enjoys the ability to have a balanced study life, often using the campus Rec Centre and being active in his spare time, going to the Weekend Markets, and being with family.
"The way the courses are structured allow ample time for school work, and still give free time to be able to spend in whatever you wish (in my case, investing in my health, self-enrichment, and family)," he says. "The copious amount of material I can study on my own time. Once you develop a certain way of thinking, absorbing that material just comes down to being willing to sit down and spend some time learning by yourself."
One of the other benefits of the programme is ҕl’s industry connections. Emil has been to some Careers Fairs events hosted on campus to meet with employers, and as part of his master’s completed a project over the summer months within the industry.
"The industry project was a really good learning experience. It exposes you to real world data science problems, and teaches you to work in a team."
With support from the Mathematics and Statistics Department, Emil intends to continue into PhD studies in Applied Data Science at ҕl and launch a research career.
