2 Weeks  Down. 13 To Go
Tags: codenewbie, devjournal, datascience, motivation
Published: 2021-12-05 19:25:45

##The Story So Far##

Nine months ago I decided to actively pursue my long time objective of changing careers and study something in the Computer Science field.
Eight months ago I learn a little about Html and Css.
Seven months ago I learn a little about how JavaScript works.
Six months ago I started learning Python, and really enjoyed it.
Between then and 2 months ago I learned all I could about data types, functions, loops, object oriented programming, databases, Big-O notation, SQL, and a few other things.
All of this was being done while I was still working a full time job in hospitality, something that took a huge chunk of my time and energy. Also, this whole time I've been studying by myself. Took a lot of time to filter and went through a whole bunch of amazing resources as Edx, Codecademy, Coursera, FreeCodeCamp, Codewars, Leetcode, and many others. That might sound great, but I'm not telling you the amount of effort it is to sieve through all that information, try to come up with a plan that work for you, and keep yourself motivated to keep going even if you have no idea what you're doing. I seriously aplaude people that can go on like that and continue to improve by themselves. In the long run though, that wasn't me. I felt stuck.

####Focus####

Back when my parents went to university in Brazil, there were fewer options. One could go for the medicine path, the exact science path, the human science path, and apart from a few outliers, that was pretty much it. And those paths didn't have nearly as many branches as they have nowadays. 
That may seem like a bad thing, since as a 18 something year old thinking that what you do at university is gonna dictate what you do for the rest of your life (which is complete nonsense by the way), you are not given the options to everything you could be doing with your life. Nowadays, the number of subjects you can chose for university is much larger, and those options have further options that didn't exist before - If you go into Computer Science, you can become a Full-Stack Developer, a Software Engineer, a Mobile Application Developer, a System Architect, a Machine Learning Engineer, a Data Scientist, and many other careers that I'm sure I have no idea exist, much less what they do.
There are also other options rather than going to university. Self-thought professionals are not rare in a variety of fields. The data available online for one to self-educate in Data Science for instance, is extremely rich. It is, and I found this for myself after registering to all those websites I mentioned, 'too rich' for me. I'm not saying abundance of resources is bad, not at all. I'm saying that, for someone trying to get in to a field by themselves, being bombarded with information from a multitude of sources can be extremely overwhelming, and can lead into a state of unhappiness, uncertainty or paralysis with your choice that, had you not had all those choices in the first place, you'd never feel. That thought process is an extreme oversimplification of Barry Schwartz book *The Paradox of Choice*, which is not really the topic of this post, but it's a factor one should be aware when thinking about how to pursue their education. I'll leave his [Ted Talk](https://www.ted.com/talks/barry_schwartz_the_paradox_of_choice?language=en#t-32400) from 2005 there if anyone is interested. 
Getting back on topic, what can you do if you don't want to spend 4+ Years in gaining an (or a second) university degree, but you feel paralyzed by the amount of choices the self-thought way gives?

####In comes Bootcamp####

If you google what is a data science bootcamp you'll get that they are *"short-term, intensive training programs that equip students with in-demand industry knowledge via project-based learning."*. That sounds exactly like what I was looking for, so I went and started to look for one. Surprise surprise, there are a **ton** of them! After considering some of the ones here in the UK, I was informed by a friend to one given by Flatiron School in the USA (which is really funny to me, since my last job here was working for a Flat Iron restaurant), and their Data Science syllabus looked much more in line with what I wanted to learn. A few phonecalls, some tests and some financing later, I'm in. A sneeze later, and we finished our second week! 
The course is fast paced. It is for beginners, but if you don't grasp things quickly, there really isn't a lot of time to keep reviewing a topic. In the first two weeks, we set up our environment using the Bash shell, Git, started interacting with GitHub, configured for Conda and VS Code, learned about Jupyter Notebooks, learned about csv and json, and how to interact with the schemas using Python, learned about data types, loops and functions, were introduced to Pandas and how to import and access data, made statistical methods with numpy, visualized data with Pandas, Matplotlib and Seaborn, grouped and cleaned data, and started on sql. All that while taking a test a day, and a big one at the end of the second week.
That might seem not much for someone who knows how to do these things already, but for someone that comes with little experience to this, it's been hard. Hard, but it's also been extremely satisfying. The bootcamp provided me with a tool that I found lacking during my self-study path: structure. Right now, I have to focus on these things. I have to do them. Not only that, but this was my choice, so instead of going about how I have to do this things, my mindset is: **I chose to do this**. And I'm happy with this choice. Confident that, even if this is not the single best path in the whole world for me (or the best jeans I could get, if you've seen that Barry Schwartz Ted Talk), I am learning a lot and focused in what I chose to study. I am meeting a lot of interesting new people that are adding to my experience, and positive that this is one of the best decisions I made in the last few years regarding my career.
2 weeks down, 13 to go.