General Assembly’s data science immersive course - is it worth the hype?

I graduated on 11th September 2020 from General Assembly’s Data Science Intensive course, and what a journey it was!

The course was a 12 week long, full time course that covered a variety of topics including data cleaning, exploratory data analysis, supervised and unsupervised machine learning techniques, neural net (Tensorflow), SQl, and natural language processing.

In week 1, we were shown a graph similar to the one below, and told with very kind words that we will experience this, possibly multiple times throughout this course, and that it happens to everyone.

We all laughed it off.

“That’s not going to happen”, I thought. Mount Stupid was not for me, I know that I know nothing.

Looking back on it now, I think I actually started out on Mount Stupid and stayed there for far too long before crashing right into the valley of despair around week 6 of the course, right on schedule as predicted by Lay who showed us the picture in the first week.

My point is, this course will absolutely take everything out of you. Learning to code, to build machine learning models, to understand what you’ve built, is not easy. That being said, I think the course is very much worth the time, effort and money, as I have learnt so much about data science and myself in this time.

Positives

I think the real value of this course is that the instructors (who were amazing! Much love to Sri, Mas and Arnab!) took us from the beginnings of sourcing data and conceptualisation all the way to building the model into a web app and deploying it, enabling us to learn by doing and to create usable and scalable projects instead of just learning the theories behind machine learning and data science.

Although I am currently still looking for a role at the point of writing this post (have not achieved an “outcome” yet), I’d like to also mention that I really love the career coaching aspect of the course. This is something that adds so much value to the course in my opinion, and something similar should really be more of a focus in traditional university degrees. I’ve learnt so many things from the outcomes sessions that I otherwise probably would’ve taken years to figure out by myself, if ever. I would definitely recommend the course over similar bootcamps just based on this point alone. This is one of the major reasons I decided to do the course in the first place, and it has not let me down so far.

Improvements

I think the capstone project could have actually been introduced much later in the progression of the course, because some key concepts such as NLP, neural net, and recommender systems were not introduced until after we had already started on our capstone projects, which was a little disappointing because I don’t know that I would’ve chosen the project I chose (initially, I ended up changing my project which was another story) if I was further along in the curriculum when we had to decide on a capstone.

Final thoughts

Despite being such a highly intensive and demanding course, and despite the growing pains that came with being the first DSI cohort to study entirely online in COVID-19 times, I feel that overall the course was a success for all involved. I also feel that this is can largely be attributed to a wealth of support from Lay, the instructors, and the career coaches, and for that I am very grateful.