NYC Data Science Academy

Someone said this earlier. Vivian accepts anyone and everyone. This really hurt the bootcamp because we spent the first month learning how to code! That's insane!! This bootcamp was more of an introduction to coding than anything. There was a bootcamp employee who wasn't accepting unqualified people, but she either quit or was fired.

Vivian is all talk. She barely remembers most of the things she says, and the things she says are conflicting. In the first week, she promised everyone would be "senior data scientist" and shouldn't accept anything less. At the end, she said the opposite. I'm a month into job searching after the bootcamp, and I haven't been able to get interviews. I'll have to go back to what I was doing before the bootcamp, same as other people. Even most people from the last few cohorts are still looking for jobs.

Please don't join this bootcamp. It was a waste of $16000. I can't believe I paid that. I'm furious. I feel cheated. Give me my money back...going to have to report Vivian and this bootcamp.

I started working in the financial industry in 1998 and have had roles in IT spanning development and production support. I attended the NYC Data Science Academy bootcamp during a three month sabbatical from work and it was a worthwhile investment. I have gone back to work to a new and challenging role that allows me to apply my new found skills (such as data exploration, visualization, and analysis for decision making) as a production support manager for an ultra low latency and algorithmic trading platform at a top financial institution.

 

What did it take for me to achieve success at the bootcamp?

 

My three months at the academy was intense. I had a strong support system at home and at the school. My instructors and TAs were smart, caring and invested in my development every step of the way. Delivering on five different projects that stretch your knowledge of Data Science and Machine Learning fundamentals, Python and R programming, through daily classroom and homework practice was exhausting yet rewarding because you were not alone through the journey. As an early riser, the academy facilities were available to me starting at 7AM daily.

 

My advice for a strong finish.

I strongly advise that you complete the prep work provided by the academy by the time you start the bootcamp. The amount of work expected to be completed during the three-month journey is not an easy feat; however, the projects you are exposed to, the knowledge you gain and the practical experience you collect through individual and team projects is indispensable and can be quickly applied upon your return to work. Going into the bootcamp I felt uncomfortable thinking of myself as a potential Data Scientist. Leaving the bootcamp I am comfortable with the fundamentals of Data Science and the application of hypothesis testing to data problems. I am not a Data Science unicorn, hence, I rely on my new found strengths and maximize the talents within my team to investigate and find solutions to technical problems.

I studied mechanical engineering and physics for my undergrad at a top university and work in product management with a focus on search. I took this class to satisfy a personal interest in the subject matter and familiarize myself enough with the fundamentals of machine learning to be able to explore the field more deeply on my own. I was also motivated by a career interest: the subject matter is highly relevant to my domain, and I feel that developing an understanding of the concepts and how to deploy them myself will make me better at my job long-term. Prior to enrolling in the class, I spent roughly 8-10 hours learning R and felt sufficiently prepared (I had some previous programming experience).   In the end I was extremely happy with this class (Machine Learning in R on Saturdays, 8 hrs at a time). The curriculum and content were excellent, the instructor, Luke, was fantastic and the assignments were challenging and informative.    I felt the course did a really great job of driving home the core fundamentals of each subject with a focus on statistics, mathematical theory, derivations and best practices. We covered a LOT of material, yet the material had a lot of depth. I thought the sequencing of the subject matter was very well thought out as well. The class was demanding and had the caliber of a graduate-level course.   The course also struck a very nice balance between theory and implementation. After learning about a new model, we would immediately implement it in class using R on our own machines. Luke did a particularly great job at relating the implementation back to the concepts and teaching us how to interpret outcomes of our analyses (I can’t stress enough how important this latter point was for me). He has a really strong grasp of the subject matter, he’s very patient and responsive to questions, offers a lot of insightful commentary on the theory, implementations and best practices, and he cares about his students a lot. The homework assignments complement the class nicely as well, helping to drive home the methods taught in class and how to interpret your work.   If you’re interested in developing a strong understanding of the fundamentals of machine learning in a rigorous format, this class is for you. I also couldn’t recommend Luke as an instructor more. He’s awesome! I was also was very pleased with my choice of the R class. R reduces a lot of the friction in model implementation, which allowed me to focus on developing an understanding of the concepts and interpreting results. 

1.12 weeks' course with machine learning, spark, hadoop helped me solve almost technical interview questions. Also introduce several latest and popular topic, such as NLP, Deeplearning (CNN) and tensor flow. 

2. This bootcamp faces people with different backgrounds, who can choose between "how to use machine learning" and "how to implement the machine learning(more math). TAs helped a lot if you wanna learn more advanced level.

3. Chris and Vivian helped prepare resume and the interview practice, and the hiring partner event was very helpful to present myself to the hiring managers directly. 

Great appreciate!

Overall:

I will recommend this bootcamp to anyone who is eager to learn and have great passion towards data science. Before I attended the bootcamp, I received my master degree in marketing from school. I did not have a lot of math and coding background back then. With my passion towards data science, I decided to take a deep dive and applied for the NYCDSA’s 12 weeks bootcamp. Due to my limited coding background, they did not accept me at the beginning, instead, they provided one month prep course for me to get prepared for the bootcamp. I attended the September cohort after the prep course. It was one of the best decisions I have ever made. With the extensive knowledge and training, and great support in job assistance, I am able to land my dream job in 2 months after bootcamp.

Curriculum:

The curriculum is very well designed. I did a lot of research before I applied for this bootcamp. NYCDSA is the only program that covered data science in both R and python, big data processing tools such as Hadoop, Spark at once. I am really glad that I started my journey in data science with them, so my foundation in data science is much stronger now than I was when taking online classes by myself before. The curriculum will also help you to develop a portfolio for job hunting, however, you are the one who decide how much effort you want to put in and how far you want to go. 

Instructors:

The instructors and TAs are the best part of the bootcamp. You will never receive this kind of learning experience through online courses. They are all very knowledgeable in computer science, statistics, and machine learning. They are so passionate, and so willing to help each student. There were so many times that they stayed after 7pm, came in during weekends, answered slacks questions at 11pm to provide extra helps. They are far more than just instructors and TAs, but also supportive friends after I finished the program.

Job assistance:

I got hired by a major ad agency as a data scientist within two months of completing the bootcamp.

The hiring team put the best effort to help their students. They hosted awesome hiring partners event, which the students got to make connections and talk to some great companies, such as IBM, citi bank, Mindshare, Publicis and so on. During my job hunting process, Vivian tried her best to provide any connections with the companies that I really wanted to get in. I also received a lot of helps and mentorship from Chris. The way he helped me to prepare for net-working and interviews are very strategic, systematic, and effective. I learned so much and I won’t get this far without him. You can learn all the hard skills anywhere else, but this kind of support and mentorship is hard to find even if you have a lot of money.

They provide as many helps as they can, but you have to be proactive and eager to learn to take everything in! 

This bootcamp is no longer the great place it used to be. Vivian Zhang (the crazy CEO) has made the curriculum into a joke, and you waste a lot of time on nonsense apps like shiny, blog posts because she thinks that's what employers want. It is not. No one in the industry pays attention to the things she believes they do, which is 1 reason why it has been so difficult to place all candidates in a job. Do not believe for 1 minute she will help you get a job. Only your true qualifications will help with that. 

Her TAs are wonderful and brilliant. It is not their fault that she bulldozes their efforts. But she has complete control of the camp. 

It is very difficult to watch her cheapen the brand of what started out so great, and single-handedly destroy the hard work of everyone who works for her.

She let in people to the camp who were completely unqualified to be there, including non-STEM bachelors, or MBAs with no technical background whatsoever, who were a huge burden on the class. If you are a STEM phd, you had better go to Insight or Ivy Data Science if you want an intensive course in ML and statistics. "Data science" is a marketing phrase for analytics. If you do not have a technical background, you should know that the 16,000$ package Vivian is selling you is too good to be true. You cannot be made a data scientist in 3 months, and there is no way she will be able to place you in a data science job. Most people from cohorts 5 and above are still looking for jobs months afterwards. The ones that do find jobs 6 months-1 year afterwards, do so without any help from Vivian.

I work for a media company that is transitioning to Python. They were made aware of Vivians reputation and decided to send all their data analysts for corporate training in Metis. I was asked for my recommendation and I have to agree that the quality of teaching is better at Metis, since Vivian has fired most of her good teachers, and the median quality of students can be terrible, since she lets in who ever applies, regardless of their technical skills. I also spoke to several prospective students who told me they pulled out of DSA because they heard that Vivian was letting in anybody who wanted to become a data scientist, even business analysts, and was unable to get most people a permanent job. She lists "internships" as permanent jobs, and cannot support the candidate when those internships terminate. The people in my office who know Vivian do not think that DSA looks good on my resume mainly because they think "she is trying to industrialize data scientists like a factory".

She also expanded the bootcamp from 20 students to 80 students, which should be a good indication of the quality you can expect.

Some things Vivian has done:

1. Lied by saying her acceptance rate for students is 10%. It is 100%. Maybe even 200%, if you consider all the people she tries to recruit. Do you know someone who want to be a data scientist? Tell them to send their 5000$ deposit!!
2. Fired her main lecturer and dedicated TAs, but not before working them like slaves.
3. Turned shiny app, visualization, web development and A/B testing into parts of the curriculum because she heard from 1 employer that they like it. It has nothing to do with "data science". She will just throw everything at a wall and see what sticks
4. Focus first on the jobs for chinese, american, or PHD students to improve her job ratio. The way she makes ''tailored recommendations'' is to put all 100 students CVs into a ZIP file, email this zip file to HR/the HIRING MANAGER and ask if there are any jobs for people in the 'awesome' 5GB of cvs she is sending. With many exclamation points!!! 
5. is so aggressive with employers and contacts that she scares them away. See 4.
6. If you want to work in finance she will tell you that finance is dead in New york and no one is hiring in there anymore. You should work for a start up instead, preferably one on her list
7. If you are coming from outside New York she will send you back there and let you find a job on your own
8. Her main advice is: send your CV to 10 companies every day on linkedin and hope someone replies. This advice costs approx. $16,000. Do you want a mock interview from someone not from the same company you applied for? That will cost $50.
9. If you do get a job, be prepared for an awkward phone call about how you should hire data scientists from her when you join your company
10. Even if you are not interested in the job, she will sign you up to interview with everyone in Manhattan that she knows. Do you know this self employed guy Ben Reid or Snakes and ladders? Let them interview you for a job you don't want just for fun. Ben loves interviewing! 
11. If you are a scientist, this is probably the worst one of all. The way Vivian prepares students for interviews is by having them memorize thousands of interview questions, categorized by company. This does two things: hide a lack of deep understanding with shallow memorization, and fool interviewers into thinking that a candidate who has memorized the entire interviewbook is more qualified than one who hasnt. It is as close to cheating as you can get, and the most obvious manifestation of the data science mass industrialization and over saturation: forget about understanding deep scientific concepts, just make sure you know what your interviewer will ask you before the interview. She is a shameless cheater.
12. This is related to 11. If you are Chinese, Vivian will prep you before and after for the interviews. If not, she will tell you that giving you answers to interview questions is "unfair to other students."

I graduated summa cum laude from a top college and attend a top Economics PhD program. I attended a boot camp at this institution to boost my empirical research skills. To be honest, even though I've been receiving America's best education, I was still really amazed by the high quality of the education it provided.

The coursework is highly organized with crystal clear logic flow. The faculty here are super competent and very approachable. At this program, you will learn TONS of very interesting and practical skills, build an impressive resume and open many doors in industry.

The job placement support here is fantastic. I attended this boot camp to gain empirical research skills for academia and thus did not actively look for industry jobs, but I saw that my classmates have benefited tremendously on job search from this program. Starting from week 3, the program prepares you for professional development. Many HR's from different industries are invited for talks/info sessions/networking events. Students have many opportunities to build connections and to prove themselves. 

You will have to work hard as the boot camp is very intensive, but that's exactly why it can give you so much and prepare you so well for your future.  

I would highly recommend this program to anyone!

Preface:

I attended the July cohort and was then a Data Science in Residence at the NYCDSA prior to accepting an offer for a Data Scientist role at a consulting firm based in NYC. I will do my best in this review to be as straightforward about my experience and address a lot of questions I had prior to the program and have understood a lot of incoming students to have had through prepping them for the program. 

My Overall Opinion:

Lets start with this: get over your hesitation, take a leap of faith, and you surely will not regret your decision to attend the NYC Data Science Academy 12 Week Bootcamp. Whatever reservations you have, you are not alone; almost all graduates have felt that prior to attending the program. You may be wondering about if this program will really teach me the necessary skills to get a job, am I prepared enough for this, will the program be rigorous enough, and most pivotally; is this the right decision for me? I cannot speak for you, but I can attest to my own experience and I graduated this program with no regrets, soak in a waterfall of new knowledge and skills, and have walked away a smarter, more capable, more confident professional now employed Data Scientist in field. The program is amazing, and the instructors are passionate, and you will learn a lot, but that also being said, you get as much as you put in and the first step is trusting in yourself to join and commit to the three rigorous and insightful months ahead of you. 

My Background:

Prior to attending NYCDSA, I was a software engineer at a large shipping company for almost 2 years focusing primarily on front end development. Before that I attending another bootcamp called Hack Reactor, similar to NYCDSA, to study software engineering and javascript. It was growing interest in machine learning, the success of my experience at Hack Reactor and the thirst for that similar immersive and intensive program that led to me to the NYC Data Science Academy. In another life, I graduated from NYU with a degree in Music Business.

Common Questions:

Do you need a masters or a background in a quantitative field?

The answer is no. No, you do not need a masters degree or professional experience in a quantitative field. During my cohort, I thought some of the best and most creative presentations and chosen topics by students were from some that had no prior coding or heavy math experience. That being said, coming in with a math or software engineering background will definitely allow you to vamp up your projects flashiness and you may have an easier time understanding some of the formulas associated with the advanced machine learning algorithms. 

Will I get a job from this program? What are the job stats? etc.. 

Although I can't attest to job stats, I received my first offer less than 6 weeks after the program ended. I met the firm at the Career Day at the end of the program. Vivian, the CEO of NYCDSA, is the job placement tsar and wizard and without her and her relationships with so many great firms there would not be as many companies at the career day as there are: Spotify, JP Morgan Chase, MindShare, etc.. Vivian will do every in her power to connect you with your dream job. That being said, getting an offer is entirely on you. You must have great visual and complex projects, you must interview well, and you must be actively job seeking and cultivating relationships on your own. Vivian and the team will do everything they can to prepare you and connect you with your dream job, but you need to show up with the bus fair to ride the bus. I cannot stress this enough. 

How does this compare to other bootcamps?

I am actually in a unique position to answer this question. A few years prior to graduating NYCDSA, I graduated Hack Reactor, which is a similar 12 week bootcamp, but for software engineering. Prior to that I took web development course at General Assembly, Coursera Machine Learning courses, Harvard Extension School’s Intro to Data Science class to name a few. Needless to say, I’m hungry for knowledge and a challenge. I can’t speak to the other Data Science bootcamps out there like Metis or Galvanize, but I can say that there is nothing like 3 months of learning something at a such a rapid pace. The sum of its parts is greater than the whole and you can spend years learning on your own secondary to whatever else you are doing or you can jump in the deep end. I did before with Hack Reactor and walked away amazed and the same held true for NYCDSA. 

Inside Tips:

Pick good project topics. Your projects will be portfolio to potential employers and if your project outshines the other students, employers will take notice. 

Pick good project team mates. I didn't have a poor experience with anyone I worked with, but it goes without saying that if you pick bright, easy to work with project partners, you'll be able to build a better end product.

If you don’t know how to code in R or Python and have no prior experience code - Learn now. Codeschool.com is an excellent introductory resource. 

DO NOT think you will have a social life. This is only 3 months of your life, but 3 very important months, so give it your all and don't expect to get as much out of it if you don't.

Comments to the Academy:

Scaling the program will require more job assistance personnel.

Increasing the amount of coding done in the program may be beneficial as most jobs now require coding every day and are rarely purely theoretically

Additional content on computer vision would be fun

More TAs and one on one knowledge quizzes (like done as a group at the end of the course)

*MY BACKGROUND:
I had a Master in Business Analytics before joining NYCDSA, with a knowledge of programming and data science/machine learning. Though I knew how to make graphs and build models with R and Python, and knew some concepts learned from the online course on EDX and Coursera, this bootcamp was still truly helpful for me.

My goal was to explore more deeply the big data techniques including Hadoop and Spark and get a chance to review data science and machine learning stuff in a systemic way. This bootcamp gave me almost everything I desired, with so many unexpected benefits.

It was seriously life-changing for me. I achieved something that would otherwise never be possible had I just stuck with online courses. Read on for more detail.

*COURSES:
All the courses were well-designed. They covered everything I needed in my data science journey. Some might wonder why I chose to spend money on this bootcamp to learn something that seems available online. The reason for me was that I feel my time is quite valuable. For me, the efficiency really matters. Rather than spending an hour searching for the right function or parameter and ending up being confused, I wanted to have professionals help me going through the relevant resources systemically. I also found that when confused by problems after the fact, I would open the slides, code, and my repo for that topic instead of having to jump online and wade through Stack Overflow. 

What’s more, the curriculum covered topics such as Unix, Bash, Git and version control, which seem necessary for a data scientist/programmer but which I never paid attention to when I was teaching myself.

*INSTRUCTORS AND TEAM:
They are so great. Everyone is kind and willing to help you and share their experience and approach with you. In my humble opinion, there is a huge difference between teaching yourself programming or machine learning and learning with instructors and advice. Especially when you are putting things into practice. I saved tons of time.  The NYC Data team is really curious and love to try new techniques with the students.  

They are a caring bunch, and it was great to become friends with the people who participated in and ran the program.

*JOB PLACEMENT:
I got hired by Aetna as a data science analyst within three months of completing the Bootcamp.

The job search is intense but Vivian and the hiring team were always there trying their best to help us. There is a room set aside for graduates to work in when on the job hunt, which made for easy access to staff.   During the Bootcamp, we had several courses about how to sell yourself which was especially important for people who are new to the U.S. job market. From teaching you how to impress your interviewer to helping research relevant details about a target company, the hiring team was very dedicated to providing the necessary support to help me succeed. Also, Vivian seemed to have a contact at almost every company I wanted to apply to, which was a real plus.

I’m glad I made the decision to do this, it was worth it for me.