I am a recent graduate of the Galvanize Data Science Immersive Bootcamp. In this Data Science Bootcamp we spent 3 months learning Statistics, Linear Algebra, Calculus, Machine Learning, SQL, and Python Programming. The San Francisco based program I attended was transferred from in-person to remote due to the COVID-19 pandemic. To say this experience was challenging would be an understatement. Based on my experience, here are 7 things I would do before attending a Data Science Bootcamp:
My official day at the Bootcamp started at 8:30 AM and ended at 8:30 PM Monday through Friday. I would then spend another 3 hours daily studying concepts taught that day. I would usually go to bed at midnight. The days are super long. So make sure that you get all your business in order before you start your bootcamp. Get childcare setup and your personal administrative issues in order. Make sure you also let friends and family know that you really won’t be available during your time in the Bootcamp.
Your bootcamp staff will assign you pre-work to do before you start the program. This is usually not mandatory, but highly recommended. You need to do this pre-work. When the bootcamp starts the information will be coming at you fast. You won’t have time to go over fundamentals. You will need to know those fundamentals so you can grasp the higher level concepts. For example, we spent two days on Linear Algebra. We were then expected to immediately use this knowledge to build vectors and matrices with Numpy. So make sure that you do this pre-work.
You will be training complex and resource-hungry Machine Learning Models. It’s important that you have a good computer. That Chromebook isn’t going to cut it for your course work. I recommend getting a Macbook Pro or a high spec Personal Computer.
At some early point in the Bootcamp you will need use these 3 technologies daily for your coursework.
You will use Python to write logic to build your models.
You will use Pandas to wrangle and clean data.
You will use Git for your group projects.
It will be highly beneficial to be proficient in each of these technologies
Between training models, managing Zoom, chatting on Slack, and researching on StackOverflow, your computer will become quickly overwhelmed. I highly recommend that you get a second computer or screen to help manage these tasks. This will make your life much easier.
Just because you go to a Data Science Immersive doesn’t mean you will or want to become a Data Scientist. It’s important to have an idea on what type of job you want to get so that you can effectively choose the type of Capstone projects you build. Here are the primary roles that you may be eligible for when you finish the program:
The Data Scientist is responsible for building and evaluating Machine Learning Models.
The Data Engineer is responsible for preparing the data and building data pipelines.
The Data Analyst extracts information from the data to make data driven decisions for the business.
You’re likely going to have great instructors in your Bootcamp. Howerver, it sometimes isn’t enough. You may need to go deeper into certain subjects or learn in a different way. I recommend you line up a few other resources to help you. I recommend the following:
Teamtreehouse.com teaches programming concepts in a very simple way. I found this to be very helpful.
DataCamp.com focuses on teaching complicated Data Science concepts. This program usually goes deeper than Bootcamp lectures.
FreeCodeCamp.org is a free resource that has detailed Machine Learning and Programming tutorials. It also has a great support community.
A Data Science Bootcamp will be one of the toughest challenges of your life. It’s important that you do everything you can to make the most of your experience. Good luck to you.