Galvanize

My experience at Hack Reactor @ Galvanize will be one that I will never forget. From the instructors to the course material, supporting staff members to the campus, every aspect of this program came together to offer a supportive, learning environvment... Read More essential to building the skills needed to code and become future developers.

On top of learning how to build apps, I've made life-long friendships/mentors, and developed soft skills that will help me in my journey. I am very grateful I was offered the opportunity to learn thru this program.

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... Read More 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.

I personally found the Galvanize Data Science Immersive program to be a very rewarding experience. My prior background was in biotech, and after studying and working in that space for a bit, I felt I wanted to make a change. I found the program to be... Read More very interesting, filled with engaging instructors who were very knowledgeable about the material. The curriculum covered a great breadth of data science topics, but we still went into the depth of the math behind algorithms which I felt gave us good grounding on the justification of what we were learning. I also enjoyed the collaborative atmosphere of the daily assignments and group projects. Most importantly though, I really appreciated the career services they offered throughout the program, up to the final weeks, and even past graduation. I felt they really prepared me for navigating the job search and connecting with people. I'm glad I did the program.

I attended the Galvanize DSI in Seattle from September 2018 - December 2018 and am extremely happy with my decision. I now work for as a Data Scientist at a local consulting company. Before enrolling in the DSI, I also partook in the Galvanize Intro to... Read More Python course which helped get my Python skills up-to-speed before the immersive. Pros - Student/Instructor Ratio. When I attended, there were three instructors and one resident (essentially a TA) for the 20 students in the program. This ensured that each student received ample attention and a wide gamut of perspective/expertise. - Cohort members. The admissions team did a really good job of selecting students into the program. Each one of my classmates was not only extremely sharp, they were empathetic and easy to get along with. I consider many of my fellow classmates as close friends. We were also lucky to have a good balance of guys/girls. - Curriculum. Although we covered a ton of topics in a short amount of time, we had the opportunity to cement our skills through realistic case-studies and a capstone project. - Network/Job Support. One of the best aspects of Galvanize is its deep well-connected network. Many Galvanize alums work at the top tech companies, ensuring you have ample resources during your job hunt. The new Galvanize capstone set up (science-fair style) also provides the opportunity to speak to tons of prospective employers right as your job search begins. - Location. Pioneer Square is awesome. Cons (Not really negatives) - Length. You learn a ton in the 13-week program, but it would be nice to have a longer period to let the information sink in. That's the nature of boot camps though. - Job Hunt. Galvanize has a really helpful network and a great support staff but ultimately getting a job is a single player game where the responsibility is up to you to hustle, network, and make things happen. Data Science is also maturing as an industry so it probably gets slightly harder to land the ideal first job each passing year. However, there is still a huge demand for DS talent. Overall I'm very happy with my decision. I have nothing but good things to say about the Galvanize staff, my cohort members, and the program.

As somebody that never finished my degree but had a few of the required tools to be a data scientist, being a part of the Galvanize program in NYC was the most incredible 3 months of my life. Before I went to Galvanize, I was managing a pool store. I... Read More loved it but the pay just wasn't there and I always found myself too far from the technology I desperately wanted to work with. In 3 months (and then another 1-2 months of practice and job searching), I was able to get a job at a fortune 50 company as a data analyst, and then was promptly poached to a startup to be the first data scientist on the payroll reporting directly to the head of analytics and CEO only a few months later. All because one of my best friends (someone who did a Galvanize program a few months before me) told me I had to do it and would not take no for an answer until I went and interviewed for the program. At this point, I'm a year and 3 months out of graduation and have also taken up being a teaching assistant at a similar bootcamp because I loved the experience at my bootcamp so much. Free time is hard to come by at this point, but I get to do what I love every single day and it's all because of 3 short months of hard work... My instructor was an incredible and patient woman with a bioinformatics background and my classmates (who are all data scientists or engineers now) were some of the best and brightest people I've ever had the opportunity to meet. The person who ran career services spent nearly 20 years in the recruiting business and knew all of the tricks to help us get hired. He was the first person I formally met on campus, told me to lighten up when I was visibly terrified before my on-campus interview, helped me navigate my exit from my first employer after Galvanize, and we still call each-other to check in sometimes. The teaching staff, (even instructors I had no classes with) were infinitely more approachable than the professors I came across during my years in undergrad, and the support staff kept our moods high even when stress levels were up. Everybody on that campus was there to help or listen, everybody understood how tough it was, and everybody knew that it was for the best and that you should just keep pushing. This program will give you everything you need to go out there and get a data science job if you make the best of it, no matter how scared you are on the way in, or how impossible of a task some things feel like when you're there. You will leave with every skill you need in your quiver to start a job as a data scientist or engineer and you will find yourself thinking about how much fun you had the entire way many months down the road. I know this because I think about my time at Galvanize NYC every day and am doing my absolute best to replicate that with the students I work with now. If you have any doubts about this, go to campus, meet these people, and never look back. I couldn't say enough about my time at Galvanize.

This course includes the most topics that would be used in the actual job as a Data Scientist. There are a lot of learning due to the short period of time and the large amount of information to be discussed. The instructors are very accessible to the... Read More students and the career service will prep the students step by step which I found very useful. There were not many projects in my cohort but I heard they have changed their curriculum to include more projects recently.

I had a successful career as an actuary and consultant and was looking for a change into a more technical field. I chose Galvanize for the combination of in-person instruction and the promise of career services assistance throughout and after the program... Read More ended. I ended up attending the Galvanize Data Science immersive in Austin under the instruction of Joe and Dan. The first part of the combination worked out very well. Joe and Dan are a great team of instructors with vast knowledge in the field of data science. I felt there was a good balance of breadth and depth in terms of the material presented throughout the course. I have a strong math background so was able to focus on the implantation of many techniques as I already had a good handle on the theory. I know some students struggled with this. The second part of the combination - career services - did not pan out. Our cohort in particular was caught in the middle of a regime change within Galvanize and as a direct effect, we received what I could consider inconsistent assistance in career services. I ended up landing a job with one of the companies Galvanize teamed up with for an onsite visit but I understand many of my classmates struggled in finding jobs after the cohort ended. All that to say, much like any field, the job search can be difficult and is highly dependent on individual characteristics. At the end of the day, I felt well prepared on day 1 of my new career as a data scientist and was able to leverage everything I learned in 3 months to immediately begin making an impact. I recommend this program for people who have a solid math / statistics background (or study well ahead of time) so that you can focus on the practice and implementation of the algorithms and techniques you learn in class. The program is certainly fast paced but doable and is jam packed with a ton of valid information that is presented in a usable and digestible way.

I was part of the January Cohort for Data Science in Galvanize NY for 2019.

During my time at Galvanize, I found the program itself to be intensive. Everyday, I learned lots of applicable ML models for production. For our assignments, we would have to... Read More write out how the algorithm really works. Even though most of the time I didn't end up finishing the assignment, the struggle was what made my experience worth it. The fact that I didn't know the answer, made me want to learn more. Depending on how good your coding skills, you might fall behind, but the pair programming experience does help.

In terms of job prospects, I was able to speak to my career services manager every week until I found a job. The journey, like any other bootcamp experience, is extremely hard. You will be applying and networking as a full time job. At some points, you wish that you went for that master's degree, but at the end of the day, you do receive many opportunities to get that data scientist job. Companies and recruiters do take a look at your resume loaded with real world projects.

Let's break this down into categories

Pre-Galvanize:
I went into Galvanize with both undergraduate and graduate degrees in Engineering. I was working in general tech but wanted to switch over to Data Science and figured my 2 options were either to go back... Read More to grad school or the bootcamp/immersive approach. Galvanize was the cheaper and quicker option between the 2 so I gave it a shot. I wasn't coding regularly at the time and my overall job function hand very little in common with Data Science but I was relatively confident that I could make the switch with enough time/effort.

Galvanize:
The program itself is pretty well setup and covers the basics of most applicable ML models. Its very fast paced, and I'm pretty sure that my engineering background (coding experience as well as math) helped in quickly absorbing the material. Topics change day-to-day so you definitely need to keep pace to make it through. Every day is slightly different but was structured very similarly. The first part of the day introduces some new concept (lecture/theory), followed by an individual assignment that tests that mornings concepts. The second half of the day continues the lecture a bit further and is capped off by a paired programming assignment which again reflects the days material. Neither of these assignments are graded but I found them to be really helpful in actually understanding the material.

Post-Galavnize:
I slowly began applying for jobs after the program ended and the overall support I got via Galvanize (James Van) was pretty helpful. I occasionally made the trip back to campus to chat with a few other cohort mates and also to bounce some ideas and leads around. James also helped me restructure my resume which also helped greatly.