student story

Nhat Tran

Data Team Lead @ WeCloudData
Data Engineering Bootcamp, 2020
Diploma Program

Data Engineering Bootcamp

Data Team Lead, Beamdata

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How I Got to Know About WeCloudData

Back in 2015 or 2016, I was using Python coding for work. Data Science (DS) and big data were starting to get really hot; it kept coming up on forums and ads – it wouldn’t leave me alone! One of the ads I saw was a meetup with WeCloudData for DS. I decided to go and see what the hype was all about. I thought, “Let’s just go there and check out the info session”.

It was a very compelling, good info session. Shaohua was talking about his previous role at Blackberry and how he used DS tools to analyze customer cellphone data (anonymized) and tracked customer usage of the app in different locations. It was just very interesting how you could use the tools of DS and big data to convert raw data into insightful findings.

That was very exciting at that time because I was using Python for other things and I didn’t realize the power this tool could have that would open doors for so many other use cases. And that got me really excited! I wanted to learn more and decided to join the bootcamp. I was part of the first or second batch of Python for Data Science. At that time it was taught by Rex Liu.

I was hooked.

Rex was always very well organized and prepared – we knew what was being taught and why it was taught. The program had a live coding format so we coded along with him but for the topics that required more conceptual teaching, he used a whiteboard to draw the ideas and concepts which I really liked. A nice touch. There were also many examples provided and lots of exercises to reinforce the learning. Whenever we had problems or challenges Rex or the TAs would help us resolve the problems. In terms of the faculty and staff, they were very helpful.

Why I Chose WeCloudData

Back then (2015-2016) there weren’t many options to choose from – if I remember correctly, the other programs available were more known for web app and software development at the time. WeCloudData was the only one that provided training and career help. Maybe there were other companies outside of Toronto or Canada but I wasn’t interested. Obviously, times have changed and let’s say we were doing remote back then, I would explore more options knowing that I would have to do remote, there’s no reason to be pinned to Toronto. But back then, working remotely didn’t cross my mind so it was just a matter of places being in physical vicinity.

I think WeCloudData at that time was the most comprehensive program to train fully in DS and big data. The program had everything you needed to be ready for it. I really liked the atmosphere, it feels down to earth with a start-up feel to it. Also, the teams were always very helpful, whatever you needed they would find a way to help you with that. Very friendly staff.

How My Previous Background in Molecular Genetics Connects to Data Science

I studied molecular genetics in undergrad; I also did a master’s in genetics at UofT. What’s interesting was that during that time, although my specific research wasn’t about exploiting the power of genomics, it was clear that genomics was moving towards big data.

For example, DNA is just a sequence of information – A, T, C, and G. But it’s the way that those nucleotides are strung together, the sequencing, grouping, and aggregation of those nucleotides, it’s kinda like a playbook in terms of how genes come together and then become proteins, and then how those proteins create functions in organisms. Cancer and diseases also have a lot to do with the collection of genes and that information. So it’s all about the information.

You can use big data and data science tools for this! Exciting times for information and technology. Overlaps with many fields (biomed, pharmaceutical, astrophysics, etc) there’s no field that isn’t affected by big data and data science.

What Made Me Want to Pursue a Career in Data Science

I always loved tech and coding; I was doing those things as a hobby. I focused more on Linux and sysadmin for fun. At that time – back then people were just starting to realize how much data there was out there and how much raw data goes unused (there’s lots of potential to process it into something meaningful!)

Raw data by itself is just gibberish. You can’t do much with it like that. It’s like minerals – you gotta process the minerals into something meaningful. Same thing with data. There’s lots of raw, untapped potential for it. Using traditional methods or brute-forcing your way through to try to make sense of the data just doesn’t make sense anymore – especially when data is growing by the petabytes. You need the right tools to make sure you’re processing the data in the right way!

So going back to the question: Data holds the key to modern enterprises and business – no matter what field you’re in, everything is powered by data-driven decisions. So you need data-driven decision-making if you want to:

  1. Make an impact,
  2. Deliver value to your customers, and
  3. Stay competitive

I don’t think it’s a coincidence that successful/modern companies like Facebook, Apple, Twitter invest so much in data. It’s because data is what’s powering their revenue-generating machines globally every year. It allows them to be ahead of the competition or know when it’s time to explore mergers and acquisitions, when to pounce, etc. All these things – from the outside, we don’t know what’s going on. But that’s because we don’t have their data. They have data we don’t know about that they use to keep their company a well-oiled machine and ahead of the curve. So from my perspective, it’s a no-brainer that if you want to stay competitive and make an impact in this day and age, you must leverage data somehow. And because of the size, the speed it’s growing at, and the scale, you need the right tools and the data science field gives you the right toolsets/kit to harness the power in data.

My Overall Data Journey & Adjusting to the Pandemic

After graduation, I wanted to continue working in biomed field. However, in 2017, an opportunity came around to work at an IT consulting firm. It was a great opportunity for me to get my hands and feet wet in the IT space. But also one thing that I definitely saw that I was lacking despite coming from a STEM background was a gaping hole in the business side in general. My technical skills were there but understanding why businesses do what they do or how businesses function from the inside was what drew me to this opportunity to work with my friend at the IT consulting firm.

Although I definitely was considering DS jobs (having graduated from a DS program), that opportunity would give me the business knowledge and so I took it on. That led to me to getting my MBA which furthered my understanding of businesses and I gained more understanding of how organizations function from a strategic perspective.

In Dec 2020, I took a step back and thought about my career again. My son was very young and based on everything that was happening in my life (and with the pandemic) I decided it would be a good time to take a break from work and go back to school to reskill/upskill for after the pandemic. I think we’re all still reeling from the effects of the pandemic.

As the world emerges from the pandemic, remote work/hybrid workplaces will continue to be a huge trend. And with that comes the need for big data, data science, technology, etc. These skill sets are going to be even more in demand. I thought about what I enjoyed (technology, coding, building tech solutions, etc.) and decided it was time to swing back to the technical side – after gaining much-needed experiences and exposure to business & strategy.

Between DS and Data Engineering (DE), it’s all becoming intertwined. In Dec when I made the move, it made sense to join WCD again since I already knew the quality of the program. So it wasn’t a hard decision. The DE skillset was something I could leverage. It also provided me with the opportunity to stay home and have more time to spend with my son and help take care of him.

What I Enjoyed the Most About WeCloudData’s Programs

The people you meet and the relationships you build are important! I know that doesn’t have much to do with the actual curriculum/program but it made me enjoy what I was doing more. I like to think I came for the knowledge but stayed for the community. If there’s no community there, you’d probably move on. It’s important to have communities that you stay rooted in – for life and work – and it’s equally important that you contribute back to those communities so they thrive. It’s a two-way street.

I only chose WeCloudData so it’s hard to compare but with traditional programs (e.g. university/college/online platforms), traditional modes of learning are typically heavier on the theory whereas WeCloudData is focused more on outcomes-based and hands-on learning. So I guess WeCloudData is kind of like a trade school in the sense that by the end of the trade school curriculum and apprenticeship you’re ready for work because you’ve already practiced and applied the skills required to get the job done.

For example, if you go to school to be a car mechanic, you can sit and read about a car all day through a textbook but that’s not really useful. To become a good car mechanic you need to break down the car, look at the engine under the hood, playing around with the wheels, etc.

WeCloudData gives you that opportunity through the curriculum and projects (where you do the majority of your learning), and working through the code with the instructors during live coding – that’s where you’ll definitely want to pay attention. Especially if they happen to make mistakes, you can see how they troubleshoot and you can see the logical way they debug. This is where a lot of the learning happens. You want to also think about how you would solve these problems when it comes up. The analytical thinking, problem-solving-based approaches stick with you and this is what you want to leverage and take away from the program.

My Tips on How to Be Successful With Online Classes + General Advice

Try to mimic the environment of an in-person classroom at home. WeCloudData will provide you with a schedule anyway so you don’t have to do that yourself. Get into a routine of what you would normally do when you go into the classroom; it helps get you into a learning mindset. Make sure you have that procedure and rigour built into your routine.

Bootcamps are meant to be intense – you must bring that focus and commitment. Be interactive – turn on your webcam (you’ll feel less inclined to play around and it brings more focus). Or whatever works for you! (e.g. Going for a jog before class)

Keep yourself engaged and message other students! Give yourself some break time too. If you need help, make sure to reach out! Don’t be shy (instructors, TAs, classmates) there’s a support network.

You’re making a great choice! I’ve been telling people DS/DE are both great. You want to think of it from the angle of the cloud. There weren’t many people who could afford cars when they were starting to be made in the early 20th century – so there were few car mechanics. But as car manufacturing exploded and cars became a household item, the need for skilled mechanics and technicians also grew along with the automobile industry, and that brought about even more new professions and paths. Today, organizations are already working in the cloud or moving there soon, and so people who understand cloud technologies are needed today and will be in demand for decades just like how car mechanics are needed almost a century after the first commercial automobiles were available to the layman. You can apply very specific tools to cloud to get objectives done. Learning the skills and tools leveraged by cloud engineers and architects is extremely valuable. The cloud is here to stay. That bodes well for those who learn DS/DE – both of which leverage cloud skills and deploy workloads to the cloud.

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