Nicole Lopez

For years, Nicole Lopez was standing at the intersection of language and data, but didn’t have the technical tools to go further. For the past three years, Nicole worked as a content designer in San Diego, where she found herself managing large translation projects, collecting and organizing massive amounts of company language data.

“While working on large-scale translation projects, I kept thinking about all the untapped potential in the language data I was organizing. I wanted to learn what insights we could get from our data, and not just collect it. I didn’t know it at the time, but computational linguistics was the missing link,” she explained.
 

When Nicole discovered UBC’s Master of Data Science (MDS) in Computational Linguistics program, it was a place where her love of language and her interest in math, logic, and programming could finally come together.

“I’d considered master’s programs in computer science before, but nothing quite matched the blend of language and applied data science I wanted. I was looking for a program that would challenge me and get me hands-on experience with language data, without having to commit years to something I’d never really tried in practice,” added Nicole.

Along with its 10-month format, Lopez liked MDS Computational Linguistics’ fast-paced, application-based curriculum.

“The curriculum emphasized applied skills using real data, which was great for someone like me who wasn’t aware of the many industry applications for natural language processing. The four-week courses meant we could quickly move through the essentials, explore new topics, and spend our energy outside of class deepening our knowledge where we were most interested,” she noted.

One aspect of the MDS Computational Linguistics curriculum is that it teaches students how to solve problems involving language data (i.e., text) and how to use and build AI models including Large Language Models (LLMs). “Professors are committed to keeping the curriculum current, not just technically but also ethically, especially as LLMs and AI change so quickly.”

And being able to learn these topics in-person on UBC’s Vancouver campus was important to Nicole. 
“Doing this in-person was absolutely non-negotiable for me. I came from a remote job, and didn’t take the in-person privileges for granted. Team morale and camaraderie kept me going through the toughest parts. You can’t replicate those shared, spontaneous moments or that sense of community in an online program,” she said.

Nicole added that she loved her cohort and learned so much from working closely with people from all walks of life, which included linguists, mathematicians, speech therapists, software engineers, paralegals, and even a former linguistics professor. “People brought so many unique strengths: some were amazing coders; others were natural communicators or researchers. It taught me the value of learning from and leaning on others, and really showed me how much more you can accomplish as a team. I genuinely think I wouldn’t have gotten this in a more traditional or less diverse program.”

Nicole attended many alumni events and career talks during the MDS Computational Linguistics program to give her a realistic picture of the many different paths one can take after graduation. 

“Talking with alumni early on helped me understand what skills actually matter day-to-day in the jobs I was interested in, so I could prioritize my time in the program more intentionally. I also participated in the mentorship program and was lucky to be paired with Hao Chen He, whose energy and insight really matched what I was hoping to get out of my time at UBC,” she said.

Of the MDS-facilitated extracurriculars, it was engaging with research that stuck with Nicole the most–especially learning from the Computational Linguistics faculty about the research questions they explore, and how it connects with the courses they teach and the larger trends in the field. With the program now complete, Lopez leaves with the confidence to keep learning and push through challenges, feeling much more comfortable with both technical work and ambiguity, and better equipped to handle the realities of future research and industry careers.

“The MDS Computational Linguistics program didn’t just provide the technical training I needed—it completely changed the trajectory of my career.”

Nicole’s Top 3 Tips on Succeeding in the MDS Computational Linguistics Program:

1. Start early and often: You won’t get good at coding or data science overnight. The program moves fast, so practice and fail early—it’s part of the process.
2. Use your resources: You’re only here for a year. Go to office hours, talk to your professors, grab lunch with classmates, ask about research, get involved.
3. Schedule breaks and protect your sleep: There’s always more work, but you can’t do it all if you’re burned out. Be as committed to your downtime as you are to your assignments—even if it means submitting something incomplete now and then.

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