Why I have decided to join Le Wagon and what they have to offer
If you want to become a Data Scientist, then, at some point, you have asked yourself whether it is worth joining a bootcamp. How do I know that? I have asked myself that very question multiple times. Honestly, there are plenty of reasons why you should not join a bootcamp: it’s expensive, you can find almost everything online, there are many free e-books, you can enrol in a Coursera degree for free and so on. However, there are a few good reasons that convinced me to join a bootcamp. But there are even better reasons why I’m joining the best Data Science bootcamp in the world: The Le Wagon bootcamp.
Why a bootcamp and not a master’s degree?
That is a fair question. Indeed, it would be fantastic to take a year off and study at one of the best universities for learning Data Science in the world. However, in my case, applying for a master’s is just unrealistic.
In the UK, most application deadlines for master’s degrees are in December. The begin of the course is, usually, either late September or early October. Realistically speaking, I would have to wait at least 18 months for the next intake. If I were 20 years old, that would be ok; I could get an internship, live with my parents, and not pay for rent/mortgage or groceries. However, I am nearly 40 years, in a career change, and I do split the expenses with my wife.
There are so many alternatives to taking your first step in Data Science, that it would be a waste of time waiting around for the perfect career path. A bootcamps is one of them. Also, I should consider the cost of being outside the market, waiting for a master’s degree to begin. At the same time, many people are studying independently and doing exceptional work without a degree.
While many readers would disagree with my perspective, I believe we are in a transition period that no longer requires a certificate on your wall to get a job. Tech companies will gradually prioritise innovation over a traditional degree, demonstrating your ability to follow the rules and replicate what academics have done. Students can rarely innovate while studying. There is a massive competition to become a 1st class student, rather than collaborate to innovate. Perhaps one way to thrive is the combination of guidance, access to information and like-minded people. This is what I am looking for.
college “is ‘basically for fun and not for learning” — Elon Musk [1]
Why Le Wagon?
Le Wagon offers a 9-week full-time bootcamp and consistently receives positive reviews on Switch up. Le Wagon has over 1875 reviews with an average grade of 4.98 out of 5. These results make it the most acclaimed bootcamp in the world. Also, I have spoken with several alumni from different bootcamps, and only Le Wagon’s students said it was worth the money they invested without any regret.
Their programme is oriented towards building a startup. Their alumni have launched more 130 startups, in which 66 of those raised a total of €103,674,300 (approximately $124 million). Some examples include:
- Matera connects lawyers, accountants and web developers to enable co-owners to manage their building.
- Travelsify is a travel agency that uses natural language processing to make customers discover local hidden gem destinations, hotels, and restaurants.
- Implicity improves clinic operations and the standard of care using data. They transform cardiology practices and design predictive solutions using machine learning.
In the last weeks of the program, students develop and pitch their startups to an audience, called Demo Day. Le wagon manages to replicate a similar environment as that of Y Combinator. So, it is not only about programming and learning technical skills, but there is also an entrepreneurial mindset underlying everything they do during the bootcamp.
It’s more than just coding
You will meet many entrepreneurs, recruiters and like-minded people with different backgrounds but with similar goals. They replicate a modern yet realistic professional environment using a Basecamp/Github way of working. Students work hard around 9 am to 8 pm with some time-off for lunch and at the end of the day and yoga classes. Due to the nature of a bootcamp, you get to work on tight deadlines whilst having fun with colleagues.
For many professionals, especially those in a career change, who have worked in a traditional office setup and routine, Le Wagon presents a new view of working in a modern and innovative environment. These changes are significant because they raise the bar as to what work should look like. Once you have experienced an informal and startup way of working, it is unlikely that you will want to go back to the traditional management and endless PowerPoint presentations, writing hundreds of emails and joining numerous calls to say a few words. So, it is not just code; the way of working is part of the bootcamp experience.
“Yet don’t be fooled, it’s coding six to eight hours a day. Everything else is a bonus… If you are there to get a startup holiday or look cool with a MacBook, you’ll spend a disappointing amount of time scratching your head in front of a terminal” [2]
Prep-work
It sounds like anyone can do it, right? Wrong, be careful with that. Le Wagon’s team is aware that you can find pretty much everything online, so their bootcamp is a step up to what you can find online. There is a steep increase in quantitative background knowledge already in your first week. So, it would be best to start reasonably comfortable with linear algebra and calculus as from day one.
There is a mandatory prep-work consisting of 40 hours of training to ensure all students arrive with minimum background knowledge in coding and math. I have listed below a section of each prep-work area (and its links). These could be used as a rough guide to people interested in getting familiar with Data Science without spending any money.
Python & SQL
Python for Data science — Intermediate
Pandas and Numpy — Fundamentals
Intermediate SQL for Data Analysis
Math
It is highly recommended to go through the full course on Linear Algebra on Khan Academy. But also, you could read the Essential Math for Data Science and Machine Learning (this book is paid, but going forward, it is totally worth the investment).
Terminal & Git/GitHub
Linux/Mac Terminal Tutorial: Navigating your Filesystem
Git and GitHub for Beginners (video below)
Machine Learning
It is helpful to get started with some Machine Learning background. Le Wagon recommends signing up for and watching Andrew Ng’s videos on Machine Learning on Coursera. Although the course is a bit theoretical, it gives you a taste of what is covered on the third and fourth week.
I have been applying a bit of Machine Learning on simple datasets, so feel free to check out what I have done so far:
Conclusion
The field of Data Science is changing and growing rapidly. Waiting a few months can mean losing some opportunities. Waiting a year and a half to start a master’s degree in your late thirties might not be the optimal solution, so that is when bootcamps come in. Look for bootcamps that not only offer what you seek (working at a major tech company or launching a startup) but also have like-minded people. There is plenty of free information to get started before investing your money in a bootcamp (or a master’s degree), so be sure to do your homework.
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