Dhruv Garg

After completing his Bachelor’s in Electrical and Electronics Engineering from Shiv Nadar University, Dhruv Garg worked as a data scientist in his native India for several US-based start-ups such as SprigHub and Highbrow. For the latter, Garg helped evaluate LLM responses and he cites both experiences as exposing him to different aspects of the data science field.

However, it was during his third year of his bachelor’s that Garg realized how data science was becoming pivotal in every industry.

“What excited me the most was the possibility of applying data science across industries helping companies succeed through data-driven insights and, at the same time, learning about different domains along the way,” he added.

Even though Garg was already working as a data scientist, he saw that he had some knowledge gaps and looked for a program to help fill those gaps. Enter the UBC Master of Data Science (MDS) in Vancouver program.

“The focus on statistics really stood out for me. I always felt this was an area where I needed to strengthen my skills. I also wanted a formal education in data science to deepen my understanding of core concepts. The balance between practical skills and theory that MDS offered was exactly what I was looking for,” he explained.

During his time in MDS program, Dhruv found the MDS faculty amazing. “They’re incredibly knowledgeable and approachable. I’ve had long conversations with almost every faculty member about different topics, and they were always friendly and open to our opinions and critiques.”

In particular, Garg found MDS Lecturer, Daniel Chen, inspiring. 

“[Daniel] is incredibly knowledgeable and explains things so clearly. I always walked away from his classes having learned something new, even after reading the lecture notes in advance. I really admired how quickly and thoughtfully he answered our questions,” said Garg.

As well, being amongst a cohort of diverse backgrounds was a valuable experience for Garg. 

“It opened my eyes to the different applications of data science. I saw people applying machine learning in contexts I hadn’t considered before. It really broadened my understanding of where and how the skills we were learning could be applied,” he added.

Also, because Garg had some industry experience, he found that he was sharing tips to his classmates.

One aspect of the MDS program that Garg felt was important was the opportunity to work with real data during labs as well as the capstone project. 

“[This is] especially for those who hadn’t worked with real-world data before. It helps you see how different real data is compared to the nearly perfect datasets you use in class. You realize the challenges that come with cleaning and analyzing messy data,” Garg noted.

In addition, capstone helped Garg learn the importance of clear communication and collaboration with peers, something that he will take into his career as a data scientist.

During his time at the MDS program, Garg attended the career workshops offered. Garg found those workshops helped him learn about how the Canadian job market works and what to expect in terms of networking and hiring.

After program completion, Garg is looking for data scientist or machine learning engineer roles.

Dhruv’s Top 3 Tips on Succeeding in the MDS Program:

1. Read the lecture notes carefully and make cheat sheets as you go through them the first time.
2. Attend the labs: Even if you feel you can learn from LLMs or other resources, talking to instructors and asking questions gives you insights that tools like ChatGPT won’t.
3. Don’t lose focus, even if you do well on the first quiz: I’ve seen people slack off afterward, but everything you’re learning is important and builds up over time.

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