| | Anonymous | Summary: I quit my comfy job to do the Data Science Immersive (DSI) at Galvanize and I am so happy I did.
Background: Prior to the DSI I was a senior analyst (with an MS in epidemiology) for a research consulting firm doing quantitative research primarily in SAS. I had a strong foundation in study design and stats but never programmed in Python or had familiarity with big data tools or advanced machine learning algorithms. I thought being a quantitative researcher in this day and age without knowing Python was not good for my career so I started looking into programs. I went with Galvanize because it had the best reviews and a friend vouched for it. I saw this as more of an evolution than a career switch.
Pros:
- Purely doing the DSI allows you to focus solely on your own learning and devote yourself to applying for jobs. This is huge in itself. I never had the time or energy when working full-time. Interviewing these days, especially in tech, is a super involved process with multiple interviews, technical screens, and presentations.
- You get exposed to so many marketable tools (like AWS, Docker, Github, etc.) that you can add to your resume. Very important to get those keywords on the resume!
- You learn all of the important and relevant data science methods that are so cool like gradient boosting, neural nets and recommendation systems.
- You work on a capstone project that you can use on job talks. This is huge because it is sometimes hard to talk about a project from a previous employer because of IP or NDAs.
- You learn from you classmates and feel the buzz of being at Galvanize with the software engineering students. Everyone is working hard all day to try to better themselves. The atmosphere is motivating.
- Career services integration is pretty good although I felt like we could have been pushed more during the bootcamp.
Cons:
- It goes without saying but if the instructors aren’t good then the whole thing falls apart. Luckily the instructors I had in SF were great. Go to an open house and talk to previous students to get a feel.
- Everyone struggles but if you are weak in math, stats or coding you will definitely struggle and continue to do so if you aren’t putting in the time. It is ok to be weak in one area but if you are weak in all three then DSI may not be the best fit for you.
- This also goes without saying but the people that do the best already have some good experience. Probably because they are ambitious and quick learners, and also have some good stuff on their resume already.
- Some of the lectures were too fast to comprehend and some of the assignments were incredibly challenging or nonsensical (we have two assignments per day). Luckily the staff are constantly improving and updating the materials based on feedback. Galvanize was certainly better at responding to feedback than any of my college courses.
- The biggest con is probably the financial cost and the opportunity cost if you don’t find a well-paying job after the bootcamp. This is a calculated risk that you have to make for yourself. I suggest modeling it out. How much do you need to make and in what time frame? It is not unreasonable to be unemployed for 5 months after the bootcamp while you are looking for the right job.
Tips:
- This is not like college. You will be learning at least 10 hours a day non-stop, likely more if you are struggling with some topics. It’s not about studying for a test but always thinking about applying skills in real life and for a job interview. There is a lot of self-motivation and diligence needed to just plow through and not get bogged down.
- Be realistic: If you have no previous relevant experience it’ll be hard to land a data scientist job but I think the DSI might still be worth it since you’ll be well set up for an analyst role. My cohort had people with no experience to super skilled software engineers/math majors. What was great was that we were all looking to get something different out of our experiences and carved our own paths while helping each other. My suggestion is to think of a specific company and role you want and tailor your learning to landing that job.
- Schedule: The pre-course took me a month and a half to get through since I was still working full-time. Then interviews took two weeks. After the interviews there is some pre-course work that took a week to complete. I worked until the day before the program started so needless to say things were really busy for the two months before the bootcamp even started! Plan your schedule and timeline accordingly. I’d give yourself 4 months to do all of the pre-work (if you have no prior Python or stats experience), apply for any scholarships they have available, and get your life in order to go into the DSI head-on.
Overall: I had a great cohort and great instructors. I also think I had a good story and background and was strategic in my learning. All of this helped me land a job within 1.5 months of graduating. Three others in my cohort found jobs before me, a couple became teaching assistants, and the others are still actively looking two months out. There are so many factors that go into finding a job like previous experience, interview skills, role you are looking for (i.e. more senior). My suggestion is to just focus on yourself, be realistic and be diligent. If you do all of that then the DSI will be worth it. |
