NYC Data Science Academy

After 18 years of specialist experience, I was starting to develop a FOMO with Data Science. After some research and recommendation from a friend who completed this program I decided to enroll. No doubt, this will change my life. It was liberating and the 6-month investment was well worth the tuition fees. The instructors were experienced and curriculum was cutting edge and the program 'forced' me to keep pace with my learning and successfully complete it. It was hard, because I have a demanding job on an xVA trading desk at an investment bank but this was a necessary investment in the skills for the future. There is no limit to the applications of Data Science and I encourage more executive-level candidates with strong business experience and some STEM experience to challenge themselves. You will not regret this and I suspect that it will open up many doors for your future endeavours.

I graduated from the NYC Data Science Academy in September 2019. Though I lived in Austin, TX - home of many data science schools -, after vetting the success of past graduates and the credentials of the instructors at the Academy, I made the decision to temporarily move to New  York to attend this school. 
The requirements and coursework was very intimidating, but certainly appropriate given the requirements to be an effective data scientist. The typical student spent at least 12 hours a day at the classroom to meet homework and project deadlines, but those hours were well-spent. Even though the difficulty in the material ramped up, the quality of the students' projects and in-class discussions definitely became much more substantive and impressive. The devotion of the students definitely rubbed off on each other, but the expertise of the instructors definitely helped foster that growth as well. It is also worth mentioning that the close alumni network also played a part in student growth.
Beyond the hard skills learned (Git, Docker, SQL, Python, R, ML, etc ), the program required a lot of soft-skill development as well. Between developing effective presentation skills for our projects, and collaborating with our peers, teaching assistants and instructors, you truly learn what it means to become a data scientist amongst data scientists.
It is also worth mentioning that they play a big role in your professional development as well. They devote a lot of time to your resume building, interview preparation, and student networking, and, personally,  I found the alumni presentations they prepared were some of the most insightful presentations I've had.
If you are serious about becoming a data scientist, you go to this school. 

I needed the shortest path to pivot from a research position in physics to a career in data science.  I considered grad school, but I have a family, and I need to be there for my kids during their developmental years.  NYC Data Science Academy offered an effective restructuring of skills over the course of three months.  Not only did I learn skills in data sctructures, statistics, coding, and machine learning, but I also learned skills necessary in the job-hunting process.  The support that was given to me during my time at NYCDSA was instrumental in receiving a job offer from a well-stablished company in financial services.

I took the intensive 12-weeks bootcamp at NYC Data Science Academy. I am a postdoc in India. I had been writing graph algorithms for social network analysis, analyzing data using MS-Excel and mining data using graph theory. I decided to make a transition to industry. 

I researched for about six months to choose a proper academy to learn data science. I came up with a decision to join NYC Data Science Academy so that I could learn both R and Python within three months. But, I learnt more than I thought. I gained hands-on experience in Python, R, SQL, Spark, deep learning, Hadoop and Hive.

The materials are technically sound for job interviews. Many experienced professors and industry professionals design and teach the materials. The course laid a solid foundation in data science. The people in the academy show keen interest in every student to understand the concept, in resume writing and above all, to get a job.

With their continuous guidance, I got hired as a data scientist in New Delhi, India. My decision to join the academy to learn both R and Python simultaneously, has been proved to be a wise decision. I wanted to 'eat, live and breathe' data science and I do it today because of the academy. Thanks to the academy.

[I did the 3 month immersive bootcamp]

Before I came to the bootcamp, I spoke with one of their instructors on a video call and he described the bootcamp as an amplifier of the skills and energy that you bring to the bootcamp. In my own words, it will not make you something that you are not. It will (probably) not flip your entire career 180 degrees. 

To be honest I was extremely skeptical of a 3 month bootcamp and then going to get jobs in the applicable field. I wanted proof so I read pages of reviews. 98% of them were highly positive. I talked to friends that went to similar bootcamps. I considered the pros and cons of getting an advanced degree in data science or machine learning. Ultimately, I chose this bootcamp because based on everything, it looked like this bootcamp would put me in a strong position to get a job in the applicable field within months rather than years.

And it has. I will be starting work as a machine learning engineer starting in 2 weeks (it is currently a little over a month since I graduated). I came in with an engineering background, specifically focusing in robotics and spaceflight for a master's degree so I had a strong quantitative background. Before I came to the bootcamp, I studied in the evenings writing a couple machine learning projects in my free time for about 1.5 years prior to arrival. So, I may have studied a little more before arriving than the average student. However, many students I know are interviewing with multiple companies at this point so I can certainly vouch for the results of this program (as can the job placement percentage numbers given).

In addition to the results, the bootcamp is a fantastic learning experience. You will be writing code in the evenings and often weekends. But I learned more at this bootcamp than I did in one semester of college by a significant margin. Like many things, you get out what you put in. I dedicated 10-12 hours daily studying and now have job options! The bootcamps topics are fast and many. I highly recommend reviewing most/all topics before arriving so that you can absorb as much as possible in such a short time period. Next, everyone is a pleasure to work with and the instructors are incredible. They each have a very strong grasp of their course material and can often relate the material well to the outside world. Homework drives home the points from lecture while projects are extremely instructive. Again, do hard work and you will have great projects.

Finally, the hiring team will work as hard as they can to help you get a job and the right job. They are passionate about us getting jobs and have a lot of connections in the city. 25% of the worth of this bootcamp at least is in the hiring help and the support structure of the fellow students in my opinion. That brings me to my last point, I moved here from California, and after 3 months I now have lasting friendships with some very smart, hard working future data scientists.

Disclaimer: I was not paid or coerced to write this review. I think this bootcamp is one of the best you will find. I considered many, and this was my top choice.

This class touched upon the basic to more sophisticated application of R programming through use of available and popular packages.  Amy has been a very caring and responsive instructor.  She is always willing to help and offer insights in selecting appropriate approach to gain efficiency.    The materials covered  were vast and familiarity requires a lot of practice.  The classroom work and homework gave the students the push to get more involved and provide the hands-on experience. This class was engaging. 

NYC Data Science Academy is a great choice for anyone looking for a bootcamp.  They look for students who have a science / engineering/ math background, but they don't require a PhD (though scholarships are easier to get for PhDs).  This school really distinguishes itself partly because of the emphasis on R.  People skilled in R command the highest salaries - and for a reason.  It is the gold standard for data manipulation and for all the most cutting edge algorithms.  I looked all over for a program that taught R (as well as Python) and NYC Data Science Academy is the only one I found!  Bootcamps are 12-weeks long and cover everything a data scientist needs to know to be up and running upon graduation, included R, Python, Hadoop, Raspberry, and much much more.  Vivian Zhang, the primary teacher and founder, is a great data scientiest, statistician, programmner and teacher.  She's also a great person.  Much of the emphasis is on preparing people to get jobs in data science and there is a lot of support in recruiting - including relationships with  firms Vivian has done corporate training for and partnerships with several recruiting firms.

I was a member of the January-April 2016 cohort, and I have fond memories of the experience, difficult and stressful as it was. The instructors and TAs are overqualified and brilliant, and Christopher Makris gives the broadest and deepest lectures that time affords. Zeyu is a magician. I would call it comparable to a master's program in machine learning, if the student puts the necessary additional time for self learning and independent study. The bootcamp was one of the most informative, rich and interesting experiences of my life, but it comes with several caveats. For one, this isn't grade school, so you are expected to learn from trial and error on your own and be comfortable with mastering theory as well as execution. The staff are there as a complementary resource, and shouldn't be relied upon 24/7 as a crutch for lack of ability to work independently. In other words, you get out of the bootcamp exactly what effort you put in, and you should be able to figure out the gaps on your own.

This brings me to my next point, probably the only complaint I have with the bootcamp--the lack of selectiveness in admissions. Management is responsible for choosing a group of students that befits the brand exclusivity, and in my view admissions is not selective enough. This may hurt the camp in the long term. Several people came from non-technical disciplines and were very much able to learn quickly, but there were a couple who saw the instructors are their own personal tutors and significantly slowed the lecture process for others. If you have to ask a question every 10 minutes that interrupts the class schedule, or spend hours with TAs only to forget everything and have to repeat repeat the personal tutor process again, you should not apply here. It's not fair to other students. You will monopolize instructors' valuable time. There is no magic fix for becoming a data scientist, and after school age you should be able to learn on your own.  In the age of the internet, there is no excuse for not being able to use Google. What I noticed from our cohort was the less someone knows, the more they talk. This is more a problem of the admissions officers/CEO than of the students who do not fit in; they should foresee these kinds of problems in the interview process and make sure that whoever gets in is technically competent. People who see this as a quick entry to becoming a data scientist should also be aware that not everyone who learns to program will be a good data scientist, and you won't simply be offered a job afterwards. What is instrumental in your career post-bootcamp are your original skills and experience. It is not a way to expedite the job search if you have recently become unemployed. 

The interview process post-bootcamp is also autonomous, and you shouldn't expect to be given many interviews automatically unless you manage to find contacts on your own. Your projects are your own personal portfolio, and being self reliant on your ability will serve you better in the long run.

To summarize, the main lecturer is brilliant, an amazing teacher, who covers as much as possible in the limited time. You will learn more than you ever expected. The TAs are a major resource, but the main weakness is the admissions process. And lastly, if you can't learn things on your own, don't sour the bootcamp for others. There are many online courses, such as Coursera, which will be better for you.