General Assembly

Through my experience at General Assembly (note, when I started, it was still Bitmaker, but in effect, the content was General Assembly approved), I was able to land my first data science role.

While the industry is hiring Sr. Data Scientist engineers, and Sr. Data Scientists, breaking in is difficult for more entry-level Data Analyst/Scientists. However, I do like how there are Data Scientists who come from a variety of backgrounds, from social sciences, cognitive sciences, to mathematics.

On this journey, I’ve had a lot of support from my General Assembly instructor (Max is one of smartest, and also most effective teachers), career coaches and classmates.

Note, your mileage may vary based on your instructor, or peers (to drive discussion and helping each other). I was lucky to have one of the best. Our instructor worked at two local start-ups before joining General Assembly, so he had real experience. Additionally, he often presented at conferences like Pycon and abroad. This is the by far the reason why I am rating General Assembly so high, it’s because you gain access to an instructor who can teach the material better than online materials. Anyone can find a Jupyter notebook on Random Forests, or youtube video on Neural Networks, but to get insights from an Engineer who has written production code, and has advice about ‘flex’ topics like why Docker, cloud computing, and a better way of approaching a problem is invaluable.

Choose your boot camp based on your instructor. That’s the differentiating piece. Go to an info session, and ask him/her questions.

Coming from the software industry previously, the inclusiveness and culture were great, but not a differentiator for me. I’d imagine Brainstation being similar. But those guys were way too sales-y while recruiting, which is why Brainstation turned me off. The syllabus was a bit less relevant too.

To close I’d like to highlight two areas of improvement.
- It’s a jam-packed 12 weeks, but if there was a way to embed more data engineering, software engineering by removing some of the less relevant algorithms, I think that would be better time spent.
- Career support is great, but let’s raise the bar for those who have already worked in the industry. The general advice is table stakes (geared towards interns and university students), so it would be more valuable to have real data scientists, and data engineers provide advice on how they recruit, and perform whiteboard interviews. The network of alumni is growing, but the corporate partnerships engagement is weak as far as student employment is concerned. The career coach is working hard on early conversations with Telus Digital and MaRS, but at this point, there’s no real pipeline to feed students into those programs. Bet on yourself to find jobs rather than rely on employers knocking on your door on demo day. Set your expectations appropriately.

Loved this program! Three months of hard work won't make you a data scientist, but it will give you way more than you expect. This course taught me exactly what I want to do with my career and what to do after graduation. The instructors are there for you 12 hours a day. When I fell behind in one section, my instructor spent an entire evening helping me catch up. At the end of it all, I got a job offer through an on-site interview at General Assembly. The community is extremely supportive and I'm very grateful. This was no doubt time and effort well spent.

This course distills the core fundamentals of user experience design into a comprehensive ten-week curriculum and pairs it with the extensive network of professionals, fellow alum, and instructors.

Lectures were information dense, instructors were highly knowledgeable, projects were hands on and relevant, the support staff were helpful with ramping up towards the course, and providing assistance with networking, interviewing strategies, applications and the like. Overall this course was a fantastic experience that ultimately kickstarted my career as a product designer.