NYC Data Science Academy

Attending the NYCDSA 12-week bootcamp is the best career decision I've ever made. I came to it after finishing my PhD in math and working for a year in academia. I wanted to get into data science for lots of reasons (leveraging my background, interesting problems, ample job opportunities, interest in coding, good pay, etc.) but after spending six years in graduate school, the last thing I wanted to do was go back to school for two years to learn basic data science skills.

This program allowed me to do this career change quickly without compromising the quality of the material I learned. The program emphasizes sound foundations in coding in R and Python and in both the theory and application of machine learning. The pace is very fast but you learn and do an incredible amount in those 12 weeks. Even when full absorption of the material isn't possible, the bootcamp does a great job of exposing you to tools and concepts you'll need to be familiar with later. 

The projects are incredibly valuable for building skills and exposing future employers to your work. You would be spending your money wisely just to come and complete the projects.

The bootcamp students and the TAs/instructors have varied backgrounds, which also makes for a great environment because you can learn from everyone. The entire company - from fellow students to TAs to instructors to the CTO and COO - is filled with smart, hardworking people who are pushing to help you reach your potential. 

WHY Data Science and WHY NYCDSA: I had no idea about data science until 2016 Feb when Alphago defeated Li Shishi and it was the first time for me to get to know what is Artificial Intelligence and what is machine learning. Bringing my huge curiosity, I self-learnt an online Machine Learning course on Coursera and was able utilize the skill , for the first time, in my working project and had a positive outcome. Being proud of my achievement, I also realized there was still a long way down the road.  This is actually the reason why I decided to join bootcamp -  fully armed myself with comprehensive data science skillset and then shifting my career towards a new page. NYCDSA is a perfect choice for me as it teaches anything you need to know to work as junior data scientist and allows you to keep full time job as the same time.

Experience: Even though it is an part-time online bootcamp, I was investing 40+ hours / week on studying slides, having office hour with TA and doing projects with current full time students. The bootcamp starts with an introduction Toolkits (Unix,Git,SQL,etc.), followed by introduction to R/Python, then followed by statistics and machine learning immediately applied using R and Python. The comprehensive curriculum is completed by an introduction to Big Data tools. I was able to finish a strong portfolio with 4 projects in Shiny App, Web Scraping, Kaggle and Capstone. I learned a lot especially by collaborating with full time students and TAs, so I would strongly recommend those online students who are physically in NYC, walk in the classroom and collaborate with full-time students on your last two projects.

In terms of job assistance, NYCDSA can provide tremendous assistance on your job hunting after your graduation. Vivian and Chris know what you need to have on your resume to catch HR’s eye and get an interview, and they have a strong network which can expose you to much more opportunities.

Outcome: I finally received offer from 2 Top insurance companies, 2 Top hospitals, and 2 boutique consulting companies. I feel my investment of 7 months of study and $16K totally worth as it allows me to finally launch my dream job. Thank you New York City Data Science Academy and I would recommend it to anyone who has same dream to be a data scientist.

I came to New York City Data Science Academy because I wanted to become a better coder, to  become more knowledgeable about machine learning, and to get a better job. Having completed the bootcamp in the Spring of 2017, I can say that through the Data Science Academy, I was able to accomplish all three.

Before the bootcamp

Previous to the bootcamp, I had a job as a data analyst which gave me the exposure SQL, Linux, Hadoop, and some Python - all tools that are taught in the academy. I knew I wanted to improve my overall problem solving approach, specifically using Python and R. After a few years as an analyst, and many months of debating if enrolling in a machine learning bootcamp was worth the time and money, I decided to go for it. Although I do not have a masters degree like many of my fellow cohort members, I knew that I could use my work experience to my advantage in preparing for the bootcamp. Like many others have stated, giving yourself enough time to go over the 100+ hours of prep work before the bootcamp is highly advised - being able to perform the basics of Python and R will set you up for success.

Preparing before the bootcamp is also crucial in another way. As you spend more time studying, you spend less time doing all the other normal things you’re used to doing in your life. In order to make the most out of the bootcamp, sacrifices must be made, from your social life, to your eating and sleeping habits, and to the amount of coffee you normally drink. If you don’t get used to it before, adjusting to these changes midway through the bootcamp can be a challenge.

During the bootcamp.

If you spend enough time preparing before the start of the bootcamp, then the first month or so should not be too challenging (but still very useful). Many of my fellow cohorts actually became nervous, thinking that our investment in the bootcamp might not have been worth it. Don’t fret. After going over the basics again, the fun truly begins.

After the first month, you will spend every day learning machine learning concepts, applications, statistics, and then applying these techniques in both Python and R. This is no easy task in a few short months, which is why the instructors, teaching assistants, and Vivian, deserve so much credit in churning out so many qualified data scientists in such short time. The instructors are always, at all times, helping and guiding you in the right direction. On top of that, you have the additional resource of working with your fellow cohort members, all who have unique backgrounds and always willing to help.

In the end, the journey would not be worth it without days of extreme struggle and frustration. Some days I felt really confident in the material, other days I did not think I had what it takes to be successful. What I believe the instructors are best at is instilling the confidence in each and every student, spending as much time with you as needed to successfully complete the projects.

The last few weeks are spent on tidying up your resume, github, blog posts, and interview skills. Aside from learning both R and Python in the bootcamp, one of the reasons why I chose the Data Science Academy was because of the strong professional connections that Vivian and the team have developed over time. The final day is dedicated to a networking event, where the ratio of companies to students is almost 1 to 1. Although it can be a bit nerve wracking, Vivian and the team do a good job of preparing you on what to expect.

After the bootcamp

I was lucky enough to land an internship at a startup as a data science intern from one of the participating companies at our networking event. I have to give my experience to the bootcamp all the credit for this. Had I not had relevant experience and projects to speak of, I would not have been able to land the job. As my internship was coming to an end, I spent more time with Vivian and the team doing mock interviews, going over practice questions, asking for help on take home assignments, and constantly reviewing. Without a doubt, I can say that the three months of the bootcamp was the second hardest thing I’ve ever done - the first hardest thing was getting a job afterwards.

Vivian and the instructors have the uncanny ability of knowing what specific skills you need to improve on, based on constant back and forth communication based off of past interviews, as well as the interviews you eventually take. You will fail, and fail a lot. Most data science interviews are designed to test you on the very limit of your knowledge on data science subjects. With practice, you will answer the questions confidently, and even if you are unsure of a question, you will be able to communicate a thorough data science process on how you think the question could be answered. If you fail an interview, it’s another lesson on how to improve for your next interview, which Vivian will most likely have helped you set up already.

After months and months of dedicating my life to all data science related activities, I have landed a job as a data lead at a media company, and have the entire NYC Data Science Academy program to thank for it. If you are seriously considering a future career in data science, then I can 100% vouch for the academy, so long as you are ready to work harder than you have ever worked in your entire life. At the end of the day, it’s all worth it.

Machine Learning is transforming the world at an incredible pace and I felt it was imperative for me to acquire new skills in order to be professionally relevant. The summer bootcamp fit my schedule perfectly and I decided to enroll to better understand this exciting new field. With a PhD in Engineering from a top-five ranked school and significant background in Computational Materials Science, I felt that I had sufficient background to be successful in the bootcamp. Due to my hectic schedule, I was unable to complete all the pre-work prior to the bootcamp and I believe that this had an impact in my learning experience at the later stages of the bootcamp. In my opinion, pre-work is analogous to binary decision trees—you are trained to be independent weak learners ahead of the bootcamp. The actual bootcamp is more like a random forest where individual students work alongside other students as well as Teaching Assistants and Course Instructors to significantly contribute on a variety of real world projects related to Data Visualization, Web Scraping, Machine Learning and Big Data. The course is fast paced and students are exposed to a variety of technologies relevant to Data Science. The instructors are knowledgeable and fellow students in the cohort are sharp. It is not surprising that NYC Data Science Academy is one of SwitchUp’s Top Bootcamps of 2017. I strongly recommend this bootcamp to individuals who are seriously interested to pursue a full-time career in Data Science.

Going to NYCDSA is one of the best decisions I’ve ever made. Data science was completely new to me and I didn’t have a vey good programming background.  At NYCDSA, i was able to master both my data science and programming skills with the help of ever-present instructors, TA’s and friendly classmates. The curriculum was well balanced with all important data science topics, lab practices and mandatory individual projects included. In addition, they also had weekly coding challenges and professional development courses which teaches you how to  deal with interviews and present your self in the real world. The three months program was intense but is doable if you put in effort and dedication.  After the course, the academy also help you with your resumes and get interviews with companies within their connection. I highly recommend NYCDSA to all aspiring Data Scientist as this program helped me achieve my dream of becoming Data Scientist within 3 months after graduating.

Cheers NYCDSA

I am a recent NYCDSA graduate. Before the retrospect. The outcomes first:  Know myself better, made great friends, landed a great job within 3 months, came back to the dream land……

My story is a little different. The pre-DSA career is not bad at all.  I have had worked for a couple of top companies in the pharma and health industry for several years after getting my PhD. For some reasons, I am always thinking of expanding and tuning my fields. Life is quite dynamic that I recently moved to the east coast and happened to get stresses from various parts of the life. Rather than hanging there, I decided to challenge myself and make changes. I have thought of schools but it is not realistic for my situation.  I have studied some bootcamps and visited NYCDSA last year. The people there were very kind and down to the earth. I was not too confident at first but I would like to give a try. Therefore I gave up what I was doing, which was pretty risky and got a lot of doubts from people around me.

But I always know very well and anyone should keep in mind that 3 months can hardly make one totally expert in data science, otherwise I will be willing to pay 10 times more. We should always keep learning; the effort will pay back.

The course designs are up to date. They focus on practical data science skills.  The first month is about coding and analysis in R and python, which I found helpful in my case. After that, machine learnings have been emphasized on both python and R, then the big data part. Most of us are not directly from cs or math backgrounds. We had to work very hard for the classes in the morning, the homework at night and most importantly, the 4 projects with different emphases. We were pushed by the deadlines and harsh schedules, like the real world, have to come out the results before knowing everything.  I was the humblest guy during the 3 months in my entire life J. The instructors are very kind, helpful and always there to help. During the process, I have made some great friends, knowing people from such diverse backgrounds and also know myself better. Although I got my job on my own search according to my specialized interests and desires. The NYCDSA tried its very best to connect alumni and companies for the hiring. They have great connections. There are many alumni get jobs from the network.

Suggestions and lessons: Once you have made the decision to attend the bootcamp, forget the past and dedicate yourself.  Always focus, do not doubt your decision for one second or look back.

Skill is very important, but that’s not everything. Try to communicate, make friends and find out your strength well during the bootcamp. Design at least 2 of your 4 projects well, you know yourself the best, interact with the instructors frequently but do not solely rely on their ideas.  Do not live far, I burned myself out on the long trip every day. For the projects, try to team up with members most accountable, fair and those with high integrity and work ethics. If you share the common interest, that’s even better.  Do not judge others only by the technical or coding skills, it’s a teamwork, cultural fit is critical.  Last but not the least, we do pay a lot and might give up what we already have for the bootcamp. But when you get the quick reward in life, these pains with hope are abosultely worth it.

I came to the NYCDSA after having spent several fruitless years on the academic job market with a Ph.D. in English.  I was depressed and didn't really know where to redirect my career.  I had a background in math and a strong enough interest in data, but I knew that I needed to skill up, because that no one was going to take me seriously without another credential. 

Despite my unusual background, the NYCDSA was very welcoming and helped me get unstuck.  I'm in a new, fulfilling career, and I couldn't have done it without this program.  By the end of the first year in my current job, I'll recoup the investment with respect to my prior earning power.

The Good:

1. The cohort my term (and, I suspect, for most) is a really excellent mix of people.  You have ex-academics, mid-career folks who are trying to reskill, fresh B.A.s who need to weaponize their math/CS skills; you have people from the sciences, from finance, from advertising; you have representatives of over half a dozen countries.  They bring a variety of talents, and you learn a lot from seeing what problems they want to approach and how to approach them.

2. I've been in my current job about ten weeks, and I've already used most of the curriculum.  I use R every day, Python frequently, and a fair amount of SQL and Mongo. Good BI visualization can really set you apart, so the early part of the course has been most valuable. I've already done a fair amount of scraping, too, and occasionally contributed on some machine learning.  The only thing that would be useful for my job that the program didn't cover was JavaScript, but that's really more relevant to my field (advertising) than data science.

The Solid:

3. The instructors are all very committed.  There's a lot to learn, and they work hard to see that you get it absorbed.  I'm not wild about the setup pedagogically--three-hour lecture blocks make it easy to lose focus--and sometimes the instructors are not the easiest to follow as lecturers, but they put tons of work in, and it's appreciated.

Could Be Improved:

4. I know they try on job assistance--there's some work with resumes and interview prep, and they set up some interiews for you with their assorted hiring partners--but they don't seem to have the staff they need (at least as of my job run) to supervise it as well as they could.  To give an example, they didn't have a dedicated placement officer when I was there.  Job hunting is always terrible and unpredictable, but my impression is that some of the other camps (e.g., Insight) do a better job of minimizing the aimlessness and frustration it can incur. 

Still, after three months in the program and three and half on the market, I got a job, and I wouldn't have done it without the academy.  It was an important stage in my life, and I'm happy I made the decision to go in.  It's let me move on with my life.

What impressed me most about my experience at NYCDSA was that it exceeded all of the expectations I had from speaking with the instructors and researching the program online. The entire team truly went above and beyond and I have only positive things to say about the instructors, the curriculum, and the way the experience changed me personally.

I found the instructors at NYCDSA to be not only incredibly knowledgeable, but approachable, thoughtful teachers. They seemed to really care about each student’s development and regularly stayed late in the evenings to offer help. If they could not be present in person, the instructors were always an e-mail/Slack message away and made it a point to check in with students and offer additional resources. I also liked that they not only taught the theory behind machine learning algorithms, but explained their most common applications and pitfalls to watch out for.

The curriculum at NYCDSA is constantly updated to reflect the most valuable skills for the real world. I found during interviews that whenever I was asked whether I had experience with a certain data science technique or language, I could either say “yes” or show a project to demonstrate my skills directly. What I was taught always matched up with what was requested of me in the interviewing or working world. Even after the end of the bootcamp, I kept my slides and materials for review, and was provided with hundreds of interview questions to help me succeed going forward.

Most importantly, the NYCDSA provided an amazing support group and helped me transform myself during a critical point in time. The other students were dedicated, kind, and came from all different backgrounds. I learned a huge amount from them and the instructors about the process of learning a skill like data science/programming and collaborating successfully. Apart from teaching the curriculum, instructors also provided resume reviews, listened to elevator pitches, and made themselves available to discuss interview experiences. I felt as though I had a whole village behind me, rooting for my success.

I would without a doubt recommend NYCDSA to any friends or colleagues looking to learn data science. It was an exceptional experience and I feel grateful to have found it.

I would highly recommend anyone who wants to switch career to data science or strengthen data science knowledge to apply NYC Data Science Academy.

Before I joined the Boot camp, two of my close friends already graduated from the program and landed their dream jobs. So unlike most of people who don’t know too much about this program and have to do some research before applying it, I applied the program without a hesitation and also had a high expectation as well.

The curriculum design was excellent and really taught you how to learn new tech skills, frameworks quickly. It could be hard for people who are not exposed to programming or statistics to keep up the pace. Make sure to go through all the pre work and learn basic statistics before attending the boot camp. Once you started to work on your final project, you will notice that you’ve learned so much.

All the instructors are very talented and very patient to students.  

Vivian and Chris work hard to help you to find a good job once you’ve graduated. After you graduate, NYCDSA sticks with you.  Vivian and Claire emailed us frequently with new job opportunities and openings.

It’s not going to be easy. You will have nights you have to stay up to finish the project, missed parties that you don’t have time to attend to. But it will be worth it! The knowledge that I’ve learned in 3 months are way more than my two years master degree and I got my dream job too.

I’ve never regretted to attend NYC Data Science Academy. I’ve met so many amazing friends in the boot camp. It’s a very valuable experience to me in terms of career development and personal growth as well.

If you are passionate about data science and big data and you are willing to put hard work to achieve the goal in a short time of period, there is no better place than NYC Data Science Academy to learn data science skills.

I went into the bootcamp with little more than a liberal arts B.A. and some online self-training. Within 6 months of finishing the bootcamp, I received multiple job offers and landed a dream job on the strength of my data science skills. The employer found me through the NYC Data Sceince Academy job network-- in that sense, the Academy continued paying dividends well after I had finished. 

It is hard. When I read reviews that speak negatively the program, I suspect that they are from students who didn't put in the work themselves to take the many learning and job opportunities that NYC DSA provides. If you are willing to devote your time and effort to developing a new skill, you will be rewarded by this program. 

The NYC Data Science Academy 12 week in-person DS bootcamp will give you quality instructional resources, project experience, and beneficial job support. In 12 weeks I was able to learn a vast amount about the field, and gain the momentum necessary to secure a position 2 months after I finished. I greatly enjoyed the intense intellectual environment, as well as the comradery with my fellow students. The instructors, TA’s, and management are approachable and receptive to your needs, as long as you pester them. The bootcamp was not perfect, but I was highly satisfied with my experience, and it was worth the cost. It definitely accelerated my skill set and allowed me to gain experience, while making friends in the process.

The curriculum has great breadth ranging from fundamental statistics, to carrying out end-to-end analyses in both Python and R, to covering big data tools. The breadth and 12 week time constraint meant that depth was sometimes lacking, but this was reasonable. It just means that you pay more attention to the subjects you're interested in or where your time would be well spent. For example, I am not very interested in NLP, so I didn't devote much energy there, and instead focused on time-series analyses.

The instructors are all very knowledgeable, and passionate in their respective sub-areas of expertise. They were the real deal. The only drawback was that some of the lectures were hard to follow, but it was not hard to get clarification from the instructor or a fellow student.

The bootcamp structure is open and approachable. Everyone is on the same floor in midtown Manhattan. Feedback is encouraged, and I really appreciated the opportunity to talk to the people who were in control of things, and who could help guide me in the right direction. This openness was a huge plus in my experience.

The job support was pretty solid and consistent. I got some interviews from the hiring event, and the door was open for any job-seeking advice I had along the way. New opportunities were pushed in my direction, and I was frequently reminded to stay sharp with my skills. To help with this post-program training material was provided.

A drawback of the program is that seeking out the help you need was harder than it should have been. As a student you were expected to seek out the help you need. This is fair, but it would have been nice to be challenged a bit more in the curriculum, for example with more mini-DS case studies. Another issue was that It was difficult to get feedback on projects. I think support with projects over the whole process could have been better. On the other hand, you get to choose your own project topics, and you will learn by doing. Also, there is continuing support after the bootcamp has ended until you find a job at the least. You also have a place to come sutdy even after the bootcamp is done.

All in all, go down and talk to them if you have any doubts. Talk to the students, teachers, and anyone else you can find. I think if you love to learn, and you are proactive about seeking out the help you need, then this bootcamp will help you learn a ton in a short amount of time.

How I started

When I started getting interested in data science, I was looking for any online courses/ bootcamp to help me get into the data science world. And I found out NYC Data Science Academy was the best out of all the data science bootcamps in terms of curriculum, and after talked to Claire and Vivian about how they helped students to locate job after the bootcamp, I decided to apply for the full-time bootcamp.

Preapre for the full-time bootcamp-Prework

After I got admitted, I got access to the online prework courses (Python and R introductory courses). I really love how they organized each video and there are exercises following with each part in the video. I didn't know anything about R and Python before, and the pre-work assignments are overlaped with the content of the first 4 weeks of bootcamp, so it helped me to adapt to the speed of the class in the bootcamp.

12-Week Full-Time BOOTCMAP

The bootcamp was very intense, the curriculum was comprehensive, which covered from data anlysis, machine learning in both Python and R, and introduction to Big Data tools. We also did 4 different projects, which was important especially when it comes to job hunting. 

I didn't look for full-time data science jobs after the bootcamp because I got admission to the master program at Columbia University, and thanks to my experience at NYC Data Science Academy, I can handle the programming and data work in my current courses and projects. 

And I still receive ongoing career support from the team and chat with instructors and students time from time now. It was so nice to work with all these hard-working and passinate people in the data science world.  100% RECOMMENDED