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What it’s like to attend Le Wagon’s Data Science bootcamp

Do you wonder if attending Le Wagon’s bootcamp is the right path for you to break into data science? Our alumni, Amanda and Benoit, shared their experiences to help you make the decision.
After studying and working in the chemical engineering field, Amanda decided to change careers and learn Data Science. She now works in a fintech startup as a Data Scientist while teaching at Le Wagon.

Benoit has a Master’s in Finance and Economics and worked in a startup in Paris, France, right after his studies. At that time, he started writing his first lines of code and decided to join the Le Wagon Web Development program. Shortly after, he moved to Toronto and chose to continue his journey with Le Wagon by enrolling in the Data Science course held in Montreal and remotely. He graduated last March 2021.

Amanda, why did you choose to learn data science? 

My sister-in-law did the Le Wagon’s Web Development program and she always had many positive things to share about the course and how it prepares students for the job market by giving them the right tools.

I wasn’t that much interested in learning web development, but then I saw that Le Wagon Brazil launched a program in data science. I looked through the syllabus and, considering my background, it seemed to be the perfect fit for me. I also looked at the bootcamp outcomes, and the whole Le Wagon community convinced me that it was the right step to take.

Before starting the program, I had no experience in the field so I needed to practice. I followed Le Wagon free workshops, learned Python with Automate the boring stuff with Python, and did the whole prep-work. I was afraid that I wouldn’t be able to follow, so I did everything I could to prepare, and the experience was amazing.

NDLR: That’s why our first requirement to join the bootcamp is not about your skills, but your motivation!

And, what’s your job occupation?

I work in an early-stage FinTech startup. My job is to analyze data providers, but I’m also involved in the marketing and business side. That’s what working in a startup is; you get to do many different things!

Technically speaking, I do a lot of queries because I work with databases. I use SQL a lot, a tool that I learned during the bootcamp. There are many quick decisions to make, and the company encourages everyone to give their opinion. They really value the course I did and my background in engineering.

Benoit, what inspired you to make the switch from Web Development to Data Science? 

I always liked building stuff. After one year of learning web development, I wanted to go further into math. I found that Data Science is kind of magic as it outputs magical results. I joined the program because I wanted to understand this field better.

And, what are some data projects you worked on since you finished the bootcamp? 

I’m passionate about underwater diving, so I’m working on a learning application for diving enthusiasts. Since you can only speak with your hands underwater, the goal of my app is to learn and recognize all the signs of diving. The model works pretty well, and I should be able to deploy it live soon.

Also, at the end of bootcamp, my teammate and I worked on a project called Food to wine. Let’s say you invite friends for dinner and want to cook lasagna. You can upload a picture of your food in the app, and the machine learning model will display the recipe and the list of ingredients you need based on the image. It will also suggest wines to match your food. It was really fun to build it!

What was your favorite part of the bootcamp? 

The last two weeks of the program were my favorite! Building your own project is kind of amazing. The bootcamp goes really fast. Each week we see a different concept. During the project weeks, everything came together, and we were able to build something by ourselves.

The engineering week was what I enjoyed the most. We worked on Jupiter notebooks throughout the whole program, but we got out of it to go back to our text editor during the engineering week. That’s when we started building our packages, deployed them, and saw how everything is connected.

What did you find the most challenging? 

The first three weeks were the most challenging because I wasn’t used yet to the rhythm of the bootcamp. I also put a lot of pressure on myself because I was learning completely new concepts.

It was the same for me. The program is fast-paced, and you must realize that you’re exposed to a new way of learning. With time, you just have to accept that you can’t master everything.

 I really liked how the curriculum was designed in a way, so you never get lost. You learn a new topic every day, but if you’re stuck at some point, you can always come back to this concept and work on it during the weekend or simply ask teachers for guidance.

How was the transition from the bootcamp to real-life projects?

I think the fast-paced rhythm of the bootcamp prepares you well for the job market. You get used to achieving a lot in a short period of time.

But the best thing is that the bootcamp prepares you to know how to search for things you don’t know. And when you work in data science, this is an important skill to have!
For instance, during my job interview, the interviewer, who’s now my colleague, asked me many difficult questions. For some of them, I had to search for the answer because I simply didn’t know. For him, it was okay, he told me you’re not supposed to know it all, but you should know how to look for things.

I continue to apply the same methodology we had during the bootcamp. I code every day, and now it’s pretty smooth for me to learn new concepts. I feel I keep improving and that I have the proper basis to work on my own projects.

What are the main differences between the bootcamp and a university program? 

I studied Economics and Finance. I found that you don’t have the opportunity to get your hands dirty at the university because you don’t build so much.

The bootcamp is the totally opposite of that as you learn by building stuff and practicing every day. The lecture in the morning is only one or two hours, and the rest of the day is dedicated to solving challenges.


The bootcamp prepares you for working and dealing with issues. That’s something the university doesn’t do.

As you start working in data science, you’ll encounter issues, and you might not be able to solve them right away. The bootcamp prepares you well for this kind of situation, to be able to search for things by yourself. And that’s the fun part! I don’t remember doing this during my university program.

Are there any particular memories that stood out from your experience? 

What stood out the most for me were the conversations I had with my team and the friendships I made.

Because of the remote format, I had the chance to join a cross-campus bootcamp. It was super fun to connect with people from Argentina and Mexico. We had these virtual rooms where we could meet and discuss the challenges. Of course, we also laughed a lot, and on Friday nights, we would have beers with everyone. Today, we still talk and help each other.

For me, it was the community as well! I made a lot of friendships.

With the remote format, I was able to communicate smoothly with my batch mates and had the opportunity to get to know them well.

Also, the staff and teachers were always available to help us. When we had a question, we would be able to connect with a teacher right away to get some answers, that was great!

Thank you Amanda and Benoit for sharing your experience with us!

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