Class with Class - I joined a Bootcamp (1/2)
TL; DR
Fun experience learned a lot. But not sure I would personally spend so much money on it.
“There is only one success: to be able to spend your life in your own way.” - Christopher MorleyEnough with introductions. In January 2021, I started a 9 weeks Intensive Data Analytics Bootcamp. In this article, I would like to give an overview of the registration, the structure of the course, materials and projects we worked on, and my very personal review of the experience. In my grand master plan, two articles will follow this one *evil laugh*, not actually sure it will happen.
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| Meeting Arabella and Dina was definitely one of the highlights |
Choosing a Bootcamp and Registering
As soon as you type 'data Bootcamp' on Google, you will realize there is quite some choice out there. Luckily, I had some criteria that restrained my options to only 3 institutes.
My criteria:
- I wanted an institute that did not only offer the online version because my optimistic - clearly too optimistic - self, was hoping to be able to attend classes in person,
- Consequently, I searched only Berlin-based bootcamps, as with the current lockdown I did not want to move to another city,
- Finally, I wanted to have a Bootcamp recognized by the German institutions, to get some governmental sponsorship to cover the tuition.
Options (for me)
1. Le Wagon
3. Ironhack
Some more options, I looked at
4.CareerFoundry (only online)
5. BrainStation (based in London + others - over budget )
6. Wild Code School (many locations - 5 months required, too long)
7. Ubiqum (many locations - 5 months required, too long)
Comparing my top three options, Spiced Academy offers a slightly longer course (12 weeks vs. 9 weeks) and appeared to be more Data Science oriented. Also, it required some more previous experience, with many of its students holding a Ph.D. background.
And this is how Spiced got kicked out of my list.
On the other hand, I soon realized that LeWagon and Ironhack were virtually the same.
From the curriculum, LeWagon was promising more of a Data Science track, which seemed not very realistic in the span of only 9 weeks. However, the points listed in both schools' curricula were exactly the same.
For the final decision, I just decided to search for current students on LinkedIn and hear about their experiences.
Malon, a great dutchie who was attending the Berlin Full-Time cohort for Data fully convinced me. She was enthusiastic about the class, the teachers, and the whole experience.
I reached out to the admission team and had what was theoretically scheduled to be a call to just get some information (costs, admission criteria, and so on...). In fact, it turned out that the brief chat we have had already was valid as 'interview' - the first step of selection.
'The Interview'
Everything the admission team wants to see is just your motivation to attend. The selection for the Bootcamp does not appear to be particularly strict at any stage. As you will learn with the career team of Ironhack during your Bootcamp, it is always fundamental to create a good and reasonable narrative.
If you have got the answers to these three questions down, then you are good to go:
- Why does it make sense for you to attend the Bootcamp?
- How confident are you with numbers (or alternatively, how willing are you to learn and get your hands dirty even if you have no formal quant background)?
- Why Data vs Web Dev?
NB: It is important to start the application process well ahead, especially if you are aiming at getting the Bildungsgutschein, the amazing sponsorship from the German gov.
'The Technical Test'
After you have passed your interview, you will get a link from the admission team to a technical test. For the majority, the exercises are logical games. If you want to review some topics beforehand, watch some videos on probability and rate problems (basic GMAT videos can help).
You will have plenty of time to complete the test. And you just need to pass. Trust me, it is nothing to worry about.
Once you have completed these two steps, you are in. Yes, that is all. No crazy selection rounds as for University. In the end, you are paying (directly or indirectly) a LOT OF MONEY to attend, and if spots are available I do not think many people are turned down. Feel free to let me know if you have seen anything different.
The Bootcamp
Moving on to the juicy stuff. The Bootcamp experience is a very subjective experience, as it depends heavily on how lucky you get with teachers and cohorts.
Before starting the classes, you will be given some Prep material which is quite useful as a base. I would recommend taking some extra classes for Statistics and Python as the first week it will all just be A LOT. Furthermore, there is no way the classes can thoroughly present Statistics within the given time-frame, so it is best to start your studying early with some Coursera/Udemy.
You will be given access to your student portal which contains links, submissions, and some overview of each day's material.
Your Portal, with pre-work, Bootcamp material, and career services:
This is what one day looks like.
Daily Structure
Almost everyday the structure of the material was similar, and I really appreciated the good balance between classes and hands-on practical work.
Usually, the day would start with a quick stand-up meeting with updates about how the previous work went. These meetings are just there to replicate a working day, in my opinion, and they are not particularly useful in reality.
After morning and afternoon are two similar blocks, containing:
- lecture for the block, split into small chunks,
- after each little chunk, we would join our group in a breakout room and complete an activity on the material presented,
- at the end of the lecture-activity-lecture-activity dance, we would have to work on the lab. This could be completed solo or with the group. Finally, the lab has to be submitted to the portal.
Content
The main topics we covered were:
- Python
- SQL
- Tableau
- Statistics
Our curriculum was organized in a very hectic way and in the very first week, we went through the whole data cleaning, EDA, Modeling, etc. Of course, in the following weeks, we had to go back slowly and actually review each topic. I am not fully sure whether the curriculum person had this dream of a 'first we give them an overview and then they zoom in' kind of thing, but it was bad, very bad.
However, to Ironhack's defense, I do have to say that they have recently changed the curriculum, and they are still adjusting. Still surprising, considering they get feedback weekly from the students.
So as I said, the first week is hard-core Python:
- cleaning
- EDA
- pre-processing
- linear regression
This will be followed by 2 weeks on SQL. I enjoyed the work we did and appreciate the recent change of focus of the course to more SQL. After looking at job openings, it will definitely come in more useful.
For SQL we went from basic SELECT, GROUP BY, etc. to JOINS, VIEWS, RANKS, and database normalization
In week 4, we came back to Python for some Regular Expressions, Data Preprocessing, Models (as KNN), and Tableau
Week 5 is Mid Term Project, which was actually very fun. A whole week group project on either classification or regression.
Week 6 felt like a combination of all topics with Excel Macros on top, a lot. We also started scraping, just to avoid getting bored ;)
Week 7 was dedicated to a project on scraping and API. We created our own music recommenders! That was quite cool.
Week 8, statistics. That is enough to get an idea. right?
Week 9, the final project! Mine is here.
The order we followed did not work so well for me and I came up with one big table to have most things in an overview. You can access the overview by clicking here.
Goods & Bads
Goods:
- Personally, I believe the class group is one of the highlights of the Bootcamp, and that is why I was hoping to get the chance to attend IRL. I guess this will be for another life.
The variety of backgrounds of the classmates make the class fun and stimulating. It was inspiring to see how some people were really changing their life around and moving from fields that had NOTHING to do with data.
Additionally, a few classmates had previous experience and could push the class further by asking more relevant questions and introducing different perspectives.
- The experience itself: throwing oneself into such an intense learning challenge, especially after working for some time, is incredibly rewarding. I definitely enjoyed the adrenaline feeling when completing labs and projects, and the feeling of having my head full of new concepts. Finally, I was surprised and proud of myself when completing the final project on my own.
- The career services of the Bootcamp were definitely interesting. If you have ever thought about your cv and LinkedIn branding, some things may not sound new. However, the career week lead by Hang was well organized and supporting any level, with cool talks by professionals.
Bads:
- Our cohort had incredibly bad luck with the teaching situation, which I do not think happens that often. Our lead teacher was not available due to Corona, and we got moved from Substitute teacher to Substitute of the Substitute Teacher. IT WAS JUST BAD. People did not know what they were doing and new topics seemed more complicated than they should have been.
HOWEVER, when the lead teacher is there everything should be fine. Or at least, I can imagine.
- The content in the portal was not particularly well organized as it relied on the main teacher being there for explanation. So again, this is probably different in a normal situation.
- Lack of feedback. Your outcome is up to you. And nobody will check any of the submissions (ANY!). They are there more for accountability and discipline than anything else.
My Review
All in all, I was very lucky to get the chance to attend these classes after leaving my job, with the added benefit of getting support from the State. Despite my discipline, I would have never been able to get exposed to such a variety of materials and get such a good grasp (I hope it is good) of work as a Data Analyst.
The online version made it difficult to bond with the classmates, which was a downside to the otherwise great network we could have created.
Does it make sense to attend?
If you are aiming at doing a FULL career transition (from non-data, non-tech), be prepared to put a lot of extra work on top of the Bootcamp to create your portfolio and successfully land a job. Attending such a course is probably the best way to speed up such a transition. Unless you are a self-study machine.
If you are already connected to the field, be it through marketing, product, or controlling, the Bootcamp will be an invaluable addition for sure. But probably something that could have been reached with courses on the side of work.
Of course, getting the time off and fully committing to something new is pleasant and fun and makes the Bootcamp worthwhile. If you are learning languages, you can see the difference between those 2-evenings-per-week courses VS the intense language course where you are exposed for hours and hours to your target language.
Up to you what you prefer.
Is the price worth it?
I do find the price to be insanely high for what you get. At the end of the day, all the teacher assistants are former students and are clearly not yet experts. And when this is combined with the lack of a lead teacher, it is just felt like the institute was understaffed, which does not go well with the high attendance costs.
Personally, I would have not paid such an amount of money to attend the course, and I am very glad I got a sponsorship. If you are able to get some scholarships or discounts (check out scholarships for women in tech, or if you have a referral) then it may be worthwhile. Ironhack is one of the most convenient in-person Bootcamp price-wise. If you know you will attend online, there may be some cheaper options that make more sense.
I hope this helped somebody at least a bit.
print(ciao)
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