NYC Data Science Academy

I highly recommend NYC Data Science Academy to folks driven to pursue a data science, analysis, or engineering career. I participated in the 12-week onsite bootcamp with the Spring 2018 cohort and can attest to NYCDSA helping graduates land roles in each of these areas.

There are two reasons that NYCDSA was the right fit for me to jumpstart my career.

First, I was attracted to the academy’s strong regional network and job placement support. Vivian and the NYCDSA staff are responsive to your career interests and will put you in touch with relevant folks in the field. In addition, the NYCDSA curriculum is continuously re-evaluated for relevance. While NYCDSA helps bridge a career transition, the challenging task of skill acquisition and evaluation is on you!

Second, I wanted to participate in a program with diverse learners. Bootcamp attendees range from STEM PhDs like myself to folks with BA/BS with professional experience in analytical fields. It was an exciting process to learn from each other as we worked on group projects or talked about homework challenges. Exposure to working on teams with divergent backgrounds is extremely valuable in a practical sense and reflects how some data science teams are structured.

Overall, NYCDSA has established a process that works and is committed to continuous improvement. It was a pleasure to participate in this program with friendly students and supportive staff. NYCDSA helped me expand my technical skillset and secure a full-time data scientist role.

I was part of the full-time spring 2018 cohort, coming with a BA in social sciences and a previous business analyst role. I had down prior intro python/R/maching learning classes on Coursera and they proved a good starting point.

The bootcamp mainly involves buidling a portfolio of projects, each utilizing a new skill taught through the weeks, using mainly first R followed by Python. Also time is spend on SQL in the beginning and intro neural networks and big data architecture. 

The program is legit and skills gained are real.

While instructors and management were always friendly and making efforts to assist when asked, everyone was very busy and there was not an intense structure. As a bootcamp, the progam focuses more on flexibilty and less on structure than a traditional graduate program and thus you must be humble, self-motivated, and vocal to succeed. There is a good broad strategy in the cirriculem but the various instructors could be better in tune with eachother in this goal. Management always asked our feedback and have itineratively improved the bootcamp each cohort.

Students were from a variety of backgrounds, all well-educated and friendly. Many international students. 

From early on, management was focused on helping us gain employment after the bootcamp and have remained so after the program ended.

Now 2 months later, I just recently received a full time entry-level data science consulting position. I am very excited and credit my time at the bootcamp in opening up the new opportunity. 

I appreciate all the hands-on projects/assignments opportunities which I did during the data science boot camp. It really gives me chances to apply the machine learning theories to real-world problems. Also, the team is supportive. The teachers, teaching assistants, career coaches are very helpful and experienced. I greatly enjoy joining the boot camp at the NYC Data Science Academy.

I attended the 12 week in-person immersive bootcamp and am very happy I did.  I have a PhD in pure math (no computers, no numbers, so my coding experience was limited to "having fun" with Python) and spent my first 2 years post graduate school working at a hedge fund (in a non-technology role) and wanted to get into data science and engineering.  I genuinely believe that with enough personal motivation and drive a bootcamp is the most effective and efficient way to go from 0 to 60 in this field (note that "attending" and "absorbing" at the bootcamp alone is not enough - the drive, time, and energy ultimately must come from you - they can only set you up for success).

At the bootcamp I learned the essentials of SQL, R, and Python - not just the important packages like Numpy, SKL, etc. but how to pick up a new package and learn how to use it (a more important skill than learning any particular package).  The project work was also extremely valuable. The scopes of the projects (there's 4 of them) get wider as the program progresses (from basic visualization and RShiny app construction to open-ended real-life consulting for companies at the end of the course).

During my interviews after the bootcamp I was certainly tested on my coding and ML knowledge, but I spent a lot of time discussing my project work and results - again, the bootcamp presents you with opportunities and resources, it can't do it all for you.

If you plan on enrolling (which you should think seriously about, it's a large investment of both your time and money) I would say you should prepare as much as possible as you'll leave the bootcamp with what you bring to the table (in terms of skills, abilities, drive, and preparation) - I've seen people who leave the bootcamp ready to be "senior data scientists" as well as people who leave knowing how to code and how to use some ML packages (a big difference).

If you're looking for a bootcamp, I highly recommend NYCDSA as they truly care about the students, have a LOT to offer curriculum-wise, project-wise, and importantly their network in NYC data science jobs is EXTENSIVE (and very valuable).

The curriculum of NYCDSA bootcamp is great and well-designed. In the first four weeks, you will learn Python, R and SQL which will lay a solid foundation for your data science learning. In the next four weeks, you will learn a variety of machine learning models. In addition, they will teach big data tools and deep learning.

The instructors at NYCDSA bootcamp are excellent as they all have deep knowledge and significant experience in data science. They make complex concepts and skills easy to understand and master. The instructors teach classes in a good pace and often pause to answer any questions that students ask in class. After class, if you have any questions, they will also try their best to answer them.

During NYCDSA bootcamp, four projects will be offered not only to improve your data science skills but also to enrich your resume. The projects are really interesting and challenging. When you are working on the projects, you will be able to learn and apply data visualization, web scraping, machine learning theories and skills, big data tools and deep learning. For the capstone project, various corporations and non-profit organizations will come to the bootcamp and pitched their real data science problems to the students, which will gave the students the experience of solving real data science problems.

For the job assistance, the hiring team at NYCDSA will work very hard to get you jobs. During the bootcamp, job placement lectures will be given to teach you how to prepare for interviews. In addition, they will have several guest speakers and alumni give lectures about the current job market and suggestions on how to get a data scientist position. Before you graduate, they will help you polish your resumes to make them stand out. Right after the bootcamp ends, they will hold a hiring partner event where you will be able to network with employers from a lot of companies.

The bootcamp at NYCDSA offered us an opportunity not only to obtain significant experience and expertise in data science but also to expand our career options. After going through the bootcamp, people with various backgrounds can apply the skills they learned from the bootcamp and their domain knowledge to start their new career and explore their interest in the field of data science, which I think is the most important benefit NYCDSA bootcamp offers

I am extremely happy with my decision to attend this boot camp. Before this, I was very uncertain about what I wanted to do as a career path and never thought I would want a job that involved coding. With the excellent teaching, support, and guidance of NYCDSA staff and teachers, I found my passion. Within 3 months I gained skills in Python, R, Github, and SQL. Not many boot camps teach both R and Python, therefore this gave me a leg up against other people in the job market.

I graduated college with my Bachelors of Science in May of 2017, while many of my cohort-mates had a Master's or Ph.D. and had been working for numerous years. For this reason, I did not believe the boot camp was for me. It is not an easy course, but with hard work and dedication, it can definitely be done. I felt prepared for the job market once the bootcamp ended and really appreciated the job support provided by NYCDSA staff. They are extremely committed to getting you a job and do everything they can to help you and guide you. Because of the tools and knowledge I've gained from this boot camp, I've landed my dream job as a Data Analyst for MoveOn.org.

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 attended the 12-week data science bootcamp right after graduating from college with an engineering degree. I highly, highly recommend this course for anyone with some coding/stats background looking to work in data science or machine learning. I'll note what I believe are the most important features of the program with bullet points so it's easy to read:

• The course is rigorous but not overwhelming -- if you put it a lot of work you will get a lot out of it, and there are a lot of TA's, classmates and teachers to help if you need it.
• The coursework is oriented towards practical application in the real world. This is what stood out the most to me in contrast to my undergraduate education. The teachers at NYCDSA do a great job of teaching the theory and then explaining how concepts tend to actually be applied in the real world.
• All the class content is still accessible after the course is done -- it is EXTREMELY valuable to have all this stuff permanantly saved on your computer.
• They help you get a job after you graduate. 

My career before NYCDSA was one without numbers or Excel spreadsheets; past me wouldn't have dreamed of touching complex data modeling algorithms or cloud computing infrastructure. If you're like me, you probably are expressing some hesitation at how much a 3 month bootcamp can give you, especially when you're competing against graduates in STEM fields for a quant position.

No fear, though! NYCDSA gives you precisely what you need to succeed in today's competitive data science job market. During the bootcamp, you'll become well versed in almost all the standard tools and methodologies that data scientists use to do their jobs. While the curriculum isn't perfect (I definitely thought some days and sessions were on superfluous material, e.g. too many days spent on web scraping, and way too much focus on R as most companies are transitioning towards Python), it is more than sufficient to prepare you to compete with others.

Six months ago I was a journalist. Now I'm doing cutting edge data science at my new firm. Couldn't have asked for a better outcome.

Since 2002, I had served as a wireless communication system design engineer for Samsung Electronics, where I have developed optimal solutions based on the analysis, simulation and modeling of filed data and system features. One of my latest works was finding adaptive solution for fast tree search avoiding local minima and maxima. 

To boost up my skills and map into diverse field, recently finished an immersive data science boot camp where I completed four projects including machine-learning projects where I deployed predictive models using extreme gradient boosting, random forests, support vector machines, and logistic regression. Work experience on a data science project - Capstone project - for a big CPG company was a huge benefit as a data scientist. As a team, we analyzed product trends, competitor's products and its reviews, customer satisfaction ratio by using NLP such as TF-IDF(term freq/inverse Document freq), Topic modeling(LDA; Latent Dirichlet Allocation), Sentimental analysis and then we delivered comparative analysis results, analysis tool to the client company. Through this project, I got convinced that customer reviews and analysis of competitors tell a lot information not only for the current problems but also the next business opportunities.

Throughout this boot camp, I could have an experience on the very projects which are closely related to the data science industry, and make portfolios which could demonstrate qualification for related industry requirements. Eventually, I could get a job which requires data science such as machine learning and natural language processing by connecting my previous work exprience to portfolios in NYC data science academy.

If you want to be a actual data scientist, NYC Data Science Academy could be a best choice ever.

NYCDSA's curriculum covers everything you need to succeed in the data science industry.  The boot camp was hard, but this prepared us well to what the job market expects from a data scientist.  They also mentored us on how to deal with potential employers, giving us an edge versus other job applicants.

The boot camp also gave the opportunity to make friends with people with the same level of interest and passion in data science.  I think this will eventually develop into real life friendships and will prove to be valuable connections as you go through your career as a data scientist.

I attended the Winter 2018 immersive data science boot camp at NYC Data Science Academy, and I highly recommend this academy.

I come from a mathematics background with nearly zero experience with data science, and prior to the boot camp I only know how to program with MATLAB. (MATLAB is a registered trademark of The MathWorks, Inc., i.e., it is a serious commercial software not to be treated lightly.) I studied partial differential equations of mathematical physics, a subject intense in theory and numerical computations but very little to do with data business. Upon finishing the boot camp, how do I feel? At least now I will not embarrass myself when handling data/coding challenges with R and Python, answering machine learning questions, etc. for job interviews. Yes, I did get job placement within one month upon finishing the boot camp, and I owe that opportunity to the Academy too. It connected me with my employer at the hiring event hosted at the end of the boot camp, which alone is worth at least half of the tuition!

Now let me briefly reflect on how/why the immersive boot camp at NYC Data Science Academy is excellent, especially if your background is similar to mine:

1. Curriculum-wise and teaching style-wise, it is highly similar to a traditional university program. For folks who are fresh out of academia (i.e., newly graduated), you will feel comfortably familiar in the boot camp's setting; for folks who are not, you will also feel comfortable since the training progress is incremental (meaning that it is not difficult to keep up), and FORMAL (very important; without which the training would be shallow).                                 There are enough teaching assistants stationed all day to help you. More important, the instructors are always willing to help, who are accomplished data science experts. They really write great course materials!                   Frankly I am a laid-back person and did not work as crazy as others in the cohort (some are said to work 12 hours per day), but I did not over-relax either: I just make sure I keep up with boot camp training progress. But that (keeping up with the course progress) is enough to make you a qualified data scientist candidate in the end. The boot camp is well measured so that you do not have to be overwhelmed or burnt-out but still can achieve enough to live long and prosper.
2. From the lady who ensures there is always coffee and hot tea, to the career advisors who know how to best tailor you for job search and interviews, the academy provides great support in learning and career advising. That is to be expected: as mentioned, the program at NYC Data Science Academy is very formal (I cannot emphasize this word enough). Let us don’t forget to thank Vivian Zhang who is behind all these and who is very caring for the students.
3. You will work on actual business projects (including your Capstone project). By doing thus you know how your knowledge/skill levels are aligned with the industry standards. No less important: when you mention them in the resume or talk about them to hiring employers, the projects are not like cute school projects, but are actual, real business projects with very substantial stuff.
4. It is a pleasure to meet with the people in the cohort: people (students or instructors or TAs or supporting staff) of different backgrounds and personalities. You will always remember those cozy lunch times at the academy, when students sit around the dinner table talking about issues of the day (not limited to data science stuff). For example, at one conversation, we started from the fashionable Beats earphones, then moved on to the Bose earphones as comparison; we then argued about how to correctly pronounce the name "Bose", which naturally led to talking about the great physicist Bose (as in the Einstein-Bose condensation), and that naturally led onto various topics in quantum mechanics… Such is a "picture" of the dinner-table at the academy. The 12-week training would not be less enjoyable without the company of all those fantastic people around you.   
5. Last but not least, the highlight of highlights: the hiring events organized by the academy! As mentioned, suffice to say itself is worth at least half the tuition!

I am very satisfied with my decision to attend NYCDSA 12 week boot camp. I just graduated with a bachelor’s degree in Bionengineering and minor in Computer Science. During my last year of undergrad, I found data science to be a challenging and interesting career path to get into but I did not have much hands-on experience.

I researched a number of data science bootcamps but I chose New York Data Science Academy because of the rigorous curriculum taught in Python and R as well as the impressive credentials of the instructors.

The program is challenging, incredibly fast-paced, but very rewarding. There is pre-work material before attending the bootcamp, which helps to solidify coding fundamentals.  The beginning of the program reviews those coding fundamentals and then dives straight into the heavy machine learning concepts and mathematical basis of the theories. Although it could be quite challenging to absorb most of the material at first, the program is excellent in providing resources and exposing concepts that will be important for a data science career and job interviews.

In addition, there are 4 projects, which focus on different aspects of data science: data visualization, web scraping, machine learning, and finally a capstone, which incorporates everything you have learned. It is a good idea to join the bootcamp just to complete these projects because you can showcase these projects to future employers.

In regards to job assistance, Vivian and Chris offers job presentations which covers how to write your resume, how to position yourself for an interview, etc . There are also guest lectures that come and describe their role and how they leverage data science in their work.  At the end of the bootcamp, NYCDSA hosts a hiring event where you can meet future employers and be exposed to the data science job market.

I highly recommend this bootcamp for people who are looking to transition into a career of data science. It has been a very rewarding 3 months; I have no regrets.

NYC Data Science Academy has been a wonderful resource for aquiring the data science tools required in the workplace.

NYCDSA's greatest strength is their commitment to matching graduates with Data Science positions. Every step of the process was geared towards that goal: including practical projects with real-life company data, extensive job-hunting coaching, and seminars, and continued job assistance after graduation. 

I completed the deep learning course offered by NYDS in April 2018. Course curriculum provides a solid understanding of core theoretical concepts and their practical applications. Best part about the course was that latest papers/ research work (as resent as Jan 2018) were discussed by Jon who also shared his experience and best practices. Would strongly recommend the course for anyone who has some background in data/programming related work and wants to break into deep learning.

[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.

I am very happy to have had the opportunity at attend NYCDSA’s 12-week data science bootcamp. Overall it was a great experience and I would highly recommend the program to anyone looking to transition to a career in data science or develop skills necessary to succeed in a data driven field.

Prior to joining the bootcamp, I studied math and economics in college before working in quantitative finance for more than five years. I was looking for a program that would provide a strong foundation in coding with an emphasis on the tools and methods used in Data Science. I was excited to get a comprehensive introduction to a number of machine learning methods and theory. When comparing to other programs, I liked NYCDSA’s commitment to teaching in two languages (R and Python) through the program and for using all 12 weeks for instruction - the curriculum was able to cover so much more as a result. As the bootcamp progressed, I chose to focus more on Python, and the program was structured well so it was possible to focus more on the language I preferred to get more experience with.

The learning environment and instructors were incredible and far exceeded any expectations I had coming into the program. The classmates in my cohort were exceptionally smart and motivated individuals - everyone was a pleasure to work with and learn from, and they were a motivating force for me every week. A substantial number of the students had advanced degrees, with more than a handful having completed a PhD program. I loved the diversity of the students’ academic and professional backgrounds - this contributed so much to the learning environment.

All the instructors were excellent - they are expert in their fields, passionate about sharing their knowledge, and great teachers. A huge draw for me to this program was the diversity of instructors, with at least 5-6 instructors covering various parts of the curriculum. While all of them were always available and happy to discuss and answer any questions, this structure allowed for each teacher to cover topics they are more expert in, so the quality of instruction was strong throughout the 12 weeks. Other programs had just one teacher for the full program - for such a big field that’s changing rapidly each year, the benefit to having multiple instructors to learn from and interact with was huge.

The TA’s were also a great resource - these were generally previous bootcamp students who led homework reviews and discussions, and were available for questions each day and during the lectures. I found the homework to be generally very well thought out, not feeling like busy work or any longer or more tedious than necessary to reinforce the lessons. The workload was intense but manageable, and I always felt challenged with the opportunity to study or practice the skills more each week. I appreciated that we continue to have access to the course resources at the end of the 12 weeks - there are some topics I chose to focus less of my time on during the program that I’m excited to review in more detail now that the bootcamp is over.

The projects also provided amazing experience - I was really impressed at the academy’s level of engagement with outside firms and institutions, which gave students the opportunity to get hands on experience working on a real data science problem. We also had the option to choose our own capstone projects, but the corporate partnerships presented a number of interesting and challenging projects in a really wide range of industries and non profit organizations.

I did not make full use of the academy’s career and job placement tools, but their team has a wealth of knowledge and experience that they bend over backwards to share with the students. The team has a number of seminars and lectures in the second half of the program discussing data science jobs and interviews, and they bring interesting alumni back to share their experiences and candid advice with the students. Their team has incredible connections across all major industries, and they work hard to leverage their professional experience and network while helping each student navigate the challenges of job hunting and interviewing.

I’m excited to continue using and building on these skills in my next professional role, and I hope sharing my experience will be helpful to other prospective bootcamp students.

I am a career changer with an eductional background in the humanities, and the academy was crucial to getting that important first job in a new field. The academy provided me the training and guidance build a small portfolio of data science projects, so that I was able to secure a job as a Senior Data Analyst at a great company. 

One thing that differentiates this academy from other bootcamps is that they teach both R and Python. I really appreciated this because understanding how the same techniques can be implemented in different languages is important - since there are so many languages out there. The machine learning concepts are reinforced the second time around in the new language. Also, learning R allows you to connect with the R community, which is very strong in NYC. I, personally, am currently doing most of my work in R even though I knew python better before entering the program.

I am extremely happy with my decision to attend NYCDSA’s 12-week data science bootcamp.

I had recently completed my PhD in evolutionary biology and was looking for alternative career options. I found that data science satisfied both my intellectual curiosity and my desire for a challenging career, but I needed to find an avenue through which I could quickly make the change.

I researched the different bootcamps in the NYC area and chose NYCDSA because the curriculum offered was unique, being taught in both R and Python, and the instructors had excellent academic and data science credentials.

The program itself was fast-paced, in-depth, and admittedly, quite challenging. It began with coding fundamentals in both languages, and then progressed into the conceptual and mathematical foundations of machine learning theory. Along the way, we applied what we learned by completing four projects.

Over the course of the bootcamp, the CTO and COO gave seminars on how best to prepare for the job interview process, and several alumni and other guest speakers gave us insight into their respective experiences in data science.

At the end of the bootcamp, NYCDSA coordinates a hiring event where students are given the opportunity to speak with dozens of employers looking to hire data professionals. This was a great opportunity to get immediate exposure to potential job opportunities.

Overall, while the bootcamp is quite demanding of your time and effort during the 12 weeks, it is absolutely worth it. I went from having almost no coding experience to a data scientist in a short period of time. I highly recommend NYCDSA’s boot camp.

I took the class with Jon Krohn and could not be more pleased. Jon has a rare ability to take a complicated subject and reduce it to its fundamental elements. Instead of approaching the problems with math alone, Jon spends time crafting examples and analogies to make sure students understand the actual building blocks conceptually. That produces an epiphanic experience where we were able to visualize what is happening behind the scenes. The concepts I’ve learned in this class is something I plan to apply to real-world problems and therefore highly recommend this class to anyone who wants to learn about this field.