Should You Attend a Data Science Bootcamp? My recommendations.

3 min readJul 13, 2020

I have spent the last twelve weeks of my life participating in a Data Science Immersive with General Assembly. Whenever I enter a new program I do so with a certain set of expectations, we all do. Well now that I am two days from completing the GA-DSI program, I have a few thoughts I’d like to share.

My Experience

I am a Mechanical Engineer with a Masters Degree. I’ve specialized in numerical analysis for most of my career, albeit numerical analysis as applied to Mechanical Engineering. I entered the GA-DSI with a strong math and programming background. I did not know python, but I had lived for quite a number of years using other codes. I felt in a good place to do this course, well prepared with a good idea of what I was getting myself into.

Having said that, the course was not easy. The first two weeks of learning pandas was especially difficult. After getting past the initial code learning, the class was very enjoyable. The topics we covered were:

Working with datasets, SQL
Statistics, A/B Testing, Monte Carlo
Generalized Linear Regression
Classification Modeling
Time Series Modeling
Natural Language Processing (NLP)
Neural Networks

Each of these topics were taught well enough such that I now have a strong basis for using each of the methods. Of all the topics we covered, Natural Language Processing turned out to be what fascinates me the most. After learning the basics of NLP in the course, I was able to teach myself the advanced NLP library spaCy and have used it to do advanced NLP.

I came to the GA-DSI program seeking instruction for skills I wanted to learn, General Assembly delivered on providing the instruction needed to gain those skills. At this point I feel confident I have the needed background to pursue any of the topics the course covered.

Should You Attend a Similar Data Science Program?

I felt well prepared and ready to go upon entering the GA-DSI program, but not all participants found themselves in that position and as a result struggled quite a bit. The following are my recommendations regarding how well prepared a participant should be for this course.

The Maths

Data Science is fundamentally applied math. A lot of this math takes place under the hood, but it’s pretty much all math. If you once took Linear Algebra and understood it then you will be well prepared for this course. If you took Calculus once upon a time and understood it, you will most likely also be fine. If the above doesn’t describe you, then I hope you are prepared to learn some maths!

Coding

Although Data Science is fundamentally math, computers are what we use to solve our math problems. I would recommend knowing at least one programming language reasonably well. Data Science is pretty much all about python, but python is not hard to learn. If you can write a function and a for loop, you’ll be fine.

Conclusions

I enjoy Data Science and felt the program I took part in provided the education I was looking for.

There is one final thing I’d like to add: Data Science is like any other field. Often stories are told regarding how in-demand Data Scientists are and this is true. But regardless of how in-demand Data Scientists are, in order to succeed as one you must be good at what you do. You should enjoy using math to solve problems and you should definitely enjoy programming.