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The Path to Data Scientist

Before entering the world of code, Xin Er Chong was working as a quality control technician. Her main task was performing chemical testing on contact lens and its related products. It was a comfortable job, but at the time, Xin Er was looking for growth and development, and that led her on her journey to become a data scientist.
Why Le Wagon?

Once I decided to take that first step towards data science, I started my research and was overwhelmed with the bootcamp options available. I reviewed all the syllabi as well as reviews and ratings, and it was obvious that Le Wagon was the right choice. Apart from having a comprehensive syllabus, it had the highest rating among all the bootcamps.

What is the enrolment process?

To get started at Le Wagon, I visited their website and scheduled a call with Liana, the admissions manager. She explained everything about the bootcamp and the enrollment process. I had to do some preparation work before the start of the course as well as take an assessment on basic Python programming, statistics and calculus computation. This assessment is to ensure that you’re equipped with the foundations to start and thrive in the bootcamp. If you’re not able to pass the assessment, it would be a challenge to keep up during the course. Thankfully there are online resources to help you prepare for the exam and Liana provided support and advice as well.

How was your experience at Le Wagon?

My classmates will agree with me that the Le Wagon data science bootcamp was a very intensive but satisfying experience. A typical day in Le Wagon started with a 1.5 hour lecture where the trainer explained the theoretical concepts of the codes we use and demonstrated how to use it to do different things.

Next, we were assigned to our buddies through a buddy pairing system and tasked to complete the challenges of the day together. When we were stuck at certain challenges, we would ask for help from the teacher or teaching assistant through a ticketing system.

At the end of each day, we would have a recap session where we could practise live coding together to revise the codes and concepts which we learned. However, the day did not end there. At 8pm, we would receive a reminder on Slack to complete the flashcards as revision of the key concepts learned that day.

What did you learn during the bootcamp?

Some of the skills that were taught include data sourcing such as SQL, API and web scraping, data preparation and exploration such as data cleaning using Pandas, data visualisation using matplotlib and seaborn, machine learning such as linear regression and logistic regression, classification and decision trees, as well as ARIMA for time series data, deep learning for image and natural language processing, as well as data engineering using bash, MLFlow and deployment using Google Cloud Platform.

Le Wagon spends an entire week teaching deployment because they discovered that data engineering and deployment skills are increasingly required from data scientists. It was assuring to know that what we learn in the bootcamp is relevant to the current market. We also learned how to build simple websites using Streamlit to showcase our projects.

What do you like about Le Wagon?

There are many things that I like about Le Wagon. The lecturers are very knowledgeable and approachable. They go beyond what is required to ensure we understand the topics fully. The buddy pairing system was great as it helped us cover each other’s blind spots when we complete the challenges together. Towards the end of the bootcamp, we were required to complete a team project. This enabled me to piece together all the different parts of the bootcamp and apply it to practical use. The project that my team came up with was DDI, which uses machine learning to predict the possible side effects that two drugs may interact and cause to our body.

What I really appreciated was the career week that Le Wagon organized at the end of the bootcamp to give us a head start in our job search. During this week, alumni and top management of tech companies were invited to talk to us about the job market and the skills that are in demand. There were also workshops to guide us in crafting our CVs/cover letters/Linkedin/Github and portfolio pages. In addition, Le Wagon organized networking sessions with hiring partners to give us an edge in the job market over graduate of other bootcamps.

Beyond the practical skills that we learnt and the support in our job search, I think the most valuable thing I gained from Le Wagon is the network of students and teachers, as well as the learning resources that are available to us even after we complete the bootcamp. The school has over 15,000 alumni from all over the world that we can reach out to for career consulting and job opportunities.

What next?

After a successful completion of the data science bootcamp, I would say this is just the start of my journey. There is still a lot for me to learn but I’m so thankful that Le Wagon has given me a solid foundation to get started. I am now looking at career switch to become a data analyst/scientist.
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