Alumni Spotlight


From Mechanical Engineering to Data Analytics with University of Toronto SCS Boot Camps

By Jess Feldman
Last Updated September 7, 2022

Working at a startup as a mechanical engineer, Akinsola “Sola” Salami quickly learned he would rather be manipulating data to help drive business and product decisions. With University of Toronto School of Continuing Studies (UofT SCS) Boot Camps, Sola was able to gain foundational knowledge in data analytics as well as build a professional project portfolio. And with support from his career advisor, Sola landed a Data Analyst role at Mammoth Growth right after graduating! Sola shares how he made the most of his online boot camp experience, and what future students should keep in mind while on the data analytics job hunt. 

What inspired you to pivot from mechanical engineering to data analysis?

Work is always going to be a big part of my life. I know a lot of people look at it as a necessity, but I try to take a different approach to it. At this phase of my life, it’s where I can be the most impactful. 

After university, I joined a startup. I discovered a lot about myself at the job, like the soft and hard skills that were in abundance and lacking. You get put through the wringer working for a startup! I found that problem-solving was my ultimate calling. The ability to problem solve with quick returns was my calling to mechanical engineering as well, but data is my much-preferred method.

In many different industries, you have to work for 20-30 years before you’re the go-to problem solver. In data, it’s an equal playing field. By manipulating data, I can grab more insights from it and come in as a junior-, mid-, or senior-level professional and affect decisions. I can put a project back on course and hopefully not derail it while affecting real change.

Why did you choose UofT SCS Boot Camps?

There’s no shortage of boot camps out there, the tough choice is which one to pick. Familiarity was important for me. My decision came down to the way the boot camp was structured, the fact that it was attached to University of Toronto, the scheduling, and the length of the program.

When I was looking at boot camps, I was still working full-time at the startup and I needed the independence to set my own schedule. I also needed structure with classes and office hours. UofT SCS Boot Camp office hours catered towards the weekend.

Another factor was being able to easily message people from the program on Slack. They would get back to me when they could. All of that helped and these were conversations I had with admissions before signing up.

Was there a technical challenge in the admissions process?

There was an assessment, but it wasn’t daunting. I knew a lot of the answers immediately and the rest only took a little more thinking. I took down what I didn’t know and did a bit more research later. There were a couple of questions on Oracle that I didn’t know, so I wrote those down and did research later on. If anything, it made me more excited for the program.

Do you feel like a complete beginner could succeed in this boot camp?

Definitely. Looking at the challenges of a boot camp, the only identity trait you need is curiosity. The issue for any data scientist is how curious you can get; your work is focused on answering a bunch of questions. 

You start from the very basics at the boot camp. The first two weeks were Excel and VBA. I had used Excel my whole life as the accountant for my mom’s bookstore, so even though I considered myself an expert in Excel, I still had to do a bit of research. 

What did a typical week look like in the online Data Analytics Boot Camp?

Every day, I started by prioritizing what I needed to do and that includes both work and boot camp stuff. I worked during the day and took a break before working on boot camp stuff later in the evening. For the boot camp, you only need to commit about 10-15 hours a week, but some concepts are a bit harder and you might have longer weeks. Attending class reveals what you might find challenging for the week. Setting aside time to study was helpful.

What were your boot camp instructors like?

Our instructors were hired through the boot camp and they were all very smart. They had extensive experience in data. The quality of experience they had spoke to how they troubleshooted our problems. I could always get an answer from my instructors and I felt comfortable with the suggestions they made. Toward the end of class, my instructor gave us a bunch of resources and I appreciate that she did that.

Every time a student asked a question, the instructors would ask what the real-world application was to show how it was overcomplicating a simple problem. I’m happy I was in his cohort because it’s not about a crazy machine learning model — it’s about solving a problem in an efficient way. 

What did you actually learn in the boot camp?

Boot camps aren’t a silver bullet; the goal is to build a foundation. We covered Excel, VBA, Python, NumPy, SciPy, Pandas libraries, ETL, R, Tableau, and statistics. Within those tools, we covered so many packages. You don’t feel like a beginner anymore when you graduate! 

Note: The material covered in the boot camp is subject to change. The boot camp academic team adjusts to the market demand.

Did you feel connected to your cohort and instructors since this was an online boot camp?

Even though it was virtual, I made a few good friends at the boot camp. I got comfortable enough to ask what everyone was working on and we would discuss it. Sometimes I would sit during office hours and listen to what other people were thinking which was also useful. 

What kind of projects did you work on in the boot camp?

Every week we would focus on a different subject, even if we were using the same tool. The project would always be a scenario that felt like real life. One of my favorites was Sam who wants to open a surf shop and he needs information from his competitors. We’d pull information from different websites and that was our web-scraping project. 

Another good project was using JavaScript to build maps and plot things like heat maps. When I learned that, I had a Zoom call with dad and gave him a little demo. I built a website that plotted a map of the world and showed temperatures.

What did you build for your final project?

The final project was my favorite! I worked with a bunch of guys that were all passionate about climate change. It’s a well-done topic in the analytics community, but we hadn’t found anyone that did the link between climate change and mental well-being. That project took us through a journey of the tools we covered as well as our skills in determining good data from bad data.

How did the boot camp prepare you for the job hunt?

My career advisor, Colin, was my savior! I realized after graduation how lucky I was to land a job two days after graduation. I didn’t realize how tough the job hunt could be and how sad you could feel after putting out so many applications. Colin and I discussed how to apply for jobs and figured out what works for me. I worked with him for about four months and it was fantastic how he had an understanding of who I was and what direction to give me. I didn’t want to be a LinkedIn warrior but that’s what ended up happening and it was fantastic. I got LinkedIn Premium for a few months through the boot camp, which was great. 

Just remember that as a boot camp student, you have to make those first steps by showing up regularly to your career services sessions, having questions, doing the work, and communicating what works and what doesn’t. 

What tech roles did you feel qualified to apply for after graduating?

I originally wanted to become a data scientist but over the course of the boot camp, I realized data science wasn’t the career for me. I still wanted to get my hands dirty and find things out. The idea of AI making predictions is cool, but we have a lot of problems that need answers and that’s why data analyst roles were important for me. I felt prepared to apply for analyst roles and I just needed to get an interview so I could prove myself.

How did you land your role at Mammoth Growth?

I got my current job through reaching out on LinkedIn. One of the things my career advisor asked me to do was challenge my network. He gave me an assignment to go through my LinkedIn to see what people in my network were doing. I reached out to someone I haven’t talked to in a while and we established communication. They linked me to another person and we talked for a couple of days before she internally referred me at Mammoth Growth since I was a good fit. It all started by challenging my network! 

What kinds of projects are you working on Mammoth Growth?

It’s consulting, so every day is different. My task is to answer business questions for many different types of companies, so we have between 3-5 projects at any given time. I answer business questions about product performance, marketing performance, return on ad spend, and things like that. These are just buzzwords and it can sound daunting, but I go into these calls excited. I can tell our clients are much older than I am with more career experience, and I’m there with my laptop to give them the best hour of their week with my insights. It’s fantastic!

Do you use what you learned at the boot camp now on the job?

Definitely! I also use a lot more of the soft skills. You learn so many tools and jobs don’t generally require you to use every skill you learned at a boot camp. For soft skills, you learn with experience how to troubleshoot your own problems and break down large goals into smaller tasks. 

The tools you use depend on the company. There’s often a challenge of adjusting to a different tech stack. If you have the foundational knowledge, that’s fantastic and most jobs will give you room to grow and learn.

At this point in your data career, was the UofT SCS Boot Camps worth it for you?

Yes, for sure. Personally and professionally, six months is a long time to dedicate to anything. I made a lot of self-sacrifices and as a result, I have a high level of self-respect. I’m able to do things for my family that I couldn’t do before and I’m more relaxed with what I do. Now that I work in data analytics, I get a certain sense of achievement every week with what I do. 

From a professional standpoint, I’m grateful because I’ve found my ultimate calling and I realized what a career could look like. I can do things now with Python immediately that I would have had to do manually before. Once you’re in the industry, it’s a great industry to be in. I’m curious about what the future holds — I have a good foundation and I’m building on it.

Find out more and read University of Toronto SCS Boot Camps reviews on Course Report. This article was produced by the Course Report team in partnership with University of Toronto School of Continuing Studies (UofT SCS) Boot Camps.

About The Author

Jess is the Content Manager for Course Report as well as a writer and poet. As a lifelong learner, Jess is passionate about education, and loves learning and sharing content about tech bootcamps. Jess received a M.F.A. in Writing from the University of New Hampshire, and now lives in Brooklyn, NY.

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