I can tell you from experience that entering a coding bootcamp can be very intimidating, especially if you have basically no technical background. A sensible step to take to alleviate some of this anxiety is to familiarize yourself with the basic layout of your program’s syllabus.
You could use this to study ahead of time, but even if you don’t, just knowing what to expect can go a long way towards making the transition as smooth as possible.
In this piece, I’m focusing on web development and data science bootcamps. There’s quite a lot of diversity in bootcamp offerings, but there’s enough of a common structure for us to make general comments.
You should also be aware of the fact that any good bootcamp is going to be updating its syllabus pretty regularly in response to industry feedback. The Galvanize Data Science Immersive I attended has so far undertaken two major reshufflings of their curriculum in the half year since I graduated.
Still, I think the comments below will be helpful.
Web Development Coding Bootcamp Syllabus
Web development bootcamps come in three basic varieties: front end, backend, and full stack. There’s considerable overlap in what they teach, but they do each have different focuses.
Front end web development is client-focused. If you’ve ever seen a really beautiful website, or used a web application and thought ‘well that was really easy to figure out’, it’s because some front end developer did their job correctly.
Backend development is server-focused. The code of a website lives on a server somewhere, and backend developers have to understand how to effectively interface with them. Websites also use, transform, and generate data, which lives in a database.
Backend development programs will teach you to work with PHP, Node.js, and SQL/MySQL for working with relational databases, among other things. With these you can make sure your projects run smoothly and efficiently.
Full stack programs, of course, combine front end and backend subjects to give you a full overview of the web development pipeline.
I would encourage you to supplement this overview by Googling the syllabus of your specific program. Sometimes that information isn’t made publicly available, but it often is.
Data Science Coding Bootcamp Syllabus
Data science is one of the hottest careers today, a fact attested to by the rapid increase of bootcamps aimed at teaching this particular skill.
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But ‘data science’ is also an umbrella term which covers a lot of ground, and for this reason data science bootcamps inevitably provide only a rough overview of the field.
The Galvanize Data Science Immersive was divided into three modules. One was focused on probability and statistics (especially Bayesian analysis), another provided a foundation in machine learning, and the last introduced us to big data, cloud and distributed computing.
Since then, my understanding is that they’ve been introducing the cloud/distributed computing content earlier in the course and giving it more time. This change has come about as a result of what Galvanize’s contacts in industry have told them they’d like to see in graduates.
Given the overall direction of the data science field, most data science bootcamps follow a similar outline. As with web development, it never hurts to check to see if the bootcamp you like has their syllabus published online.
There’s no way around the fact that bootcamps are intimidating. But if it’s true that knowledge is power, I hope this information arms you with the confidence you need to succeed.
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