Is the Data Science bootcamp right for you?
Sharing a personal story that may help you make a decision
These days a lot of people are exploring the option of joining a coding bootcamp if they what to break into tech. More and more people realize that being ‘nerdy’ and ‘geeky’ is a good thing, working with technologies is cool, and knowing how to code is the new kind of literacy. However, not everyone is ready to go back to school for another four-five-seven years to get a traditional degree. Enter the bootcamps. In just a few months they promise to give you all necessary skills and knowledge to become a developer, or a data scientist, or a UX designer, or a cyber security professional. What’s that catch, right?
I’d like to share my personal story that will hopefully help you make a decision.
Background
As many people who want to join a bootcamp, I’m a career changer. My first degree was in journalism (BA and MA from Moscow State University), and I have been working in science journalism for several years when I lived in Moscow. My special skill was to read a science paper, understand what the researchers did, and translate it into a ‘human’ language. After some time of writing about the heroes, I wanted to become one.
I moved to New York and I remember studying math for several hours every day as a hobby. I was really passionate about it, but didn’t even hope that my hobby would change my future. Until I decided to test my luck and apply to Columbia University. I know, this story is supposed to be about the bootcamp, not the traditional education, but bear with me.
After graduating with a degree in applied mathematics, I didn’t even know what to do with it. I wanted to do research and analytics, but there was one big problem: I didn’t have any marketable skills. Honestly, who would pay a woman for solving differential equations by hand?
That’s when my friend told me about coding bootcamps. I knew that I didn’t want to study software engineering, I wanted to study something a little more heavy on math. So I picked data science.
Application Process
There are several bootcamps in New York city that teach data science. Some only accept applicants with a PhD in technical discipline, some are more competitive, some a less, but in my experience that application process is similar across all of them. First, it’s a good idea to book a campus tour and actually breath the same air as the students breath. Watch them work, interact with the instructors, feel the atmosphere, ask as many questions as possible. After all, you also need to understand what your daily commute would be like once you get in.
Next, you need to fill a form, where you talk about yourself, your background, and your experience with coding. And yes, you do need some experience with coding, or at least a burning desire to learn how to code. I recommend starting with free or very affordable courses, such as youtube tutorials or Codecademy. If you are like me and interested in data science, you need to know the fundamentals of Python and SQL.
After that, you need to complete the first part of the pre-work that will be sent to you after you apply. There will be some programming, some linear algebra, some calculus. You guessed, the math part was pretty easy for me, but I promise, there is nothing you can’t learn with some passion and determination. Then come the interviews.
There will be two interviews — cultural and technical. Cultural interview is the chance for you to show that you are interested, share your story, ask questions, and demonstrate determination and eagerness to learn. This is important: bootcamps are called bootcamps for a reason, you are expected to learn and do a lot of work by yourself, without people ‘spoon-feeding’ you the skills. Technical interview is the stressful part (at least it was for me). For data science program, there will be two parts: programming and math. You will be asked to share your screen with the interviewer and complete some fairly simple challenges (they will be simple if you honestly did the pre-work). The important part here is not to panic: they are not trying to trick you, don’t overthink the questions.
If you passed both interviews, you’re in. If not, they will ask you to level up your skills and try again in three to four months. Once you’re in, you need to complete the second part of the pre-work, it will get you ready for day one. There will be more coding, learning how to use the command line, and other fun and exciting stuff.
Structure of the course
The bootcamp where I studied data science offered a fifteen-week full time program. What does it mean? There were 12 weeks of studying and 3 final weeks of working on your most important final project. Those 12 weeks were roughly divided into 7 modules, each of those modules covered a specific data science topic: Python programming, SQL programming, statistics, regression, classification, natural language processing, time series analysis, deep learning, and many more.
The first few weeks are mostly introductory, so it is important to pay attention. There will be lectures — make notes and ask questions. There will be working alone on so-called labs, and there will also be pair programming. You are expected to learn how to work on your own and with a partner.
Starting with Mod 4, your routine will be divided into two parts: lecture weeks and project weeks. During the lecture weeks you will learn from the instructors and do daily coding challenges with a partner. Project weeks are when you work on a topic of your choosing, but using the skills and technologies that you just covered: you can classify the pokemons for your classification project, predict the quality of wine for your regression project, analyze The New York Times articles for your natural language processing — anything you want. But keep in mind that these projects will later be on your resume, so don’t pick anything too wild.
A day as a bootcamp student
If you chose a full-time in-person program, you are expected to be on campus between 9 AM and 6 PM. It will be like your new full-time job. Attendance will be taken, so don’t make it a habit of running late or leaving early: if you’re present on campus less than 95% of the time, you won’t graduate.
Typically I would come to campus at 8:45–8:50 AM, get some coffee and get ready for the day. Almost every day at 9 AM sharp there will be a coding challenge. Our coaches would pair us up and send us to the lecture room. They will also send us a coding challenge (typically from Hackerrank or Leetcode) and we would have 15–20 minutes to figure it out. The first pair to send the solution to the slack channel will explain it to the rest of the class. No grades, just practice.
Next, we would go back to our seats and work individually. You can do the labs and practice new skills, watch tutorials, research a new topic. Or, if it’s a project week, you are expected to be working on your project. Coaches and instructors are almost always there. And they’re there to help. You can pick their brains with your data science related questions at any time.
You have one hour to go get lunch in the afternoon, so you can choose between actually going out or just buying something to go and coming back to campus, because you are too excited about what you’re working on and don’t mind eating at the desk.
In the afternoon there will be lectures, typically one or two per day. This is your chance to gain as much knowledge as possible. Practicing your skills is extremely important, but these lectures are you chance to learn the fundamentals, and what’s happening under the hood, when you’re typing those two lines of code.
After lectures you’ll have a couple of hours to continue your individual work until you go home at 6 PM. Sometimes you’ll leave even later, but nobody will force you to stay after 6.
You are not expected to work at home in your free time, or do extra over the weekend. It is important to take care of yourself, and your coaches and instructors know it. But at least do some reading: new publications on Medium may be your inspiration for the next project.
People
The best part of being a full-time bootcamp student is people. All these amazing people that you get to know. There will be instructors who give lectures — these guys have real professional experience, and you should really pay attention to what they say. There are coaches, who are happy to help and answer any questions that you have (they give lectures sometimes too). There are students from the cohort start started before you, you can learn from their experience, there are students from the cohort that started after you, you can share your experience with them. Students from other programs, such as software engineers and UX designers, and finally, students from your cohort. These are your best friends and your family. You will work with most of them on the morning coding challenges, and with some of them you will spend an entire week working on a project, and later presenting it together to the entire class.
Challenges
Almost every student and former student that I personally talked to would describe this program as a roller coaster. There will be moments when you are absolutely amazed by what you just learned or did, there will be moments of complete frustration, when you don’t understand anything and the future seems hopeless. Sometimes these moments can be back to back. It is important to understand that even the best students don’t get some of the topics, but you need to make an effort and ask questions, talk to the instructors, do some research. You will get it eventually.
There were times when it seemed that I bit off more than I could chew. I remember panicking and figuring out the plan B, bugging the instructors and other students, trying to figure out things on my own. But looking back I’d say I did a pretty good job. I finished every project that I planned (not without help, of course).
So is it right for you?
It is if you:
- Are absolutely sure that programming should be a big part of your job and your life
- Are not scared of math. Maybe a little scared, but you will never again say the words ‘I hate math’
- Are ready to work hard
- Need practical, marketable skills
- Tried all the free programs and courses and need a more structured, and organized one
- Are looking for connections in tech, and are open to making new friends
It is NOT for you if:
- You were just casually browsing and asked yourself ‘why not join a bootcamp?’. Trust me, you’ll just lose your money, time, and every little bit of motivation
- You have absolutely no idea what data science is, you just heard that it is ‘the sexiest profession of the century’ and decided to try
- You are expecting to be ‘spoon-fed’ the information and skills
- You are not a social creature. Not necessarily a 100% pure-bred extrovert, but you need to be comfortable working with people, asking questions, presenting in front of the class, etc.
- The only thing that speaks to you in the bootcamp ad is the job placement rate. Bootcamps do work with excellent career coaches and employer partnership teams, but nobody will ‘get’ you a job the day after you graduate. Heck, I myself am still job hunting, three months after graduation. Their goal is to equip you with skills, knowledge, and resources to break into the field. The rest is up to you.
I hope my story helps you make a decision. If you have any questions, I’d be happy to help. Connect with me on LinkedIn, and feel free to shoot me a message.
