NYC Data Science Academy

The 12-week data science bootcamp is a highly useful experience both for people looking to transition into data science and those who seek to expand their skills set in their current field. A core dimension of the program is exposing and drilling you in a range of technologies that are very sought after on the market for data scientist/data analyst/quantitative analyst positions, spanning fields from tech, finance, healthcare, marketing, research etc. On this front, a distinguishing feature of the bootcamp is that you work in both either R and Python as primary languages, so that you become proficient in both languages by the end of the bootcamp, which is very valuable. Besides these languages, the bootcamp also teaches staples of database, file management and version control like bash, git, SQL (MySQL, SQLite) and MongoDB as well as in demand big data tools like Spark, Hive, Hadoop, AWS, etc. This is a very powerful set of tools to have under your belt. Certainly, the more familiar you are with these technologies before joining the bootcamp, and the more intense effort you are willing to put into practicing these skills, the more you will be able to get out of the experience, and you must be prepared to absorb new technologies very fast, but at the bootcamp, you get a structured and very supportive environment to help you achieve this. The TAs are excellent, very dedicated, and willing to assist you with any question or problem you may have.

A second core dimension of the program is anchoring you in the mechanics of statistical inference, machine learning algorithms, and data mining. The curriculum is grounded in canonical texts in machine learning and is organized such that you get to cover a lot of ground in a short time. The concepts are explained very clearly, first from a mathematical perspective and then implemented step by step in both R and Python. The instructors have various specialties in which they teach, are extremely knowledgeable and can answer questions at any level of depth.

Tying these first two dimensions together are mostly daily problem sets and five projects, where you get to use the skills you are learning. For the projects, you can even go beyond, learning and adding a technology or skill that may not have been directly taught, if it serves your project. You will have ample support from the TAs and instructors through all this, and your classmates will make a very useful learning community. For the projects, it is helpful to give yourself plenty of time in advance to come up with ideas, but here again your TAs, instructors, and classmates will be very helpful sounding boards.

The third core pillar of the program is job search assistance. During the bootcamp there is a series of job search preparation lectures that include resume review, search and interview tips, interview type quizzes, and industry guest speakers. You will be encouraged, given many useful tips, and get motivated to become very disciplined and efficient in your approach. At the end of the bootcamp, each cohort is invited to a career event focused exclusively on the newly graduated cohort, with hiring managers from a diverse set of companies. You won’t be handheld, and you must apply discipline and commitment to your search, applications and preparation for interviews after the boot camp ends, but the job search assistance from the bootcamp will continue until you find a job, with the opportunity to interview with companies that hold interviews at the bootcamp, referrals to positions you’re applying through the frequent advertisements sent to alumni or to positions you apply on your own, a bank of practice interview questions, interview performance review, and an alumni dedicated place to come work on your search at the bootcamp headquarters available to all alumni.

The bootcamp is a very intense experience and you have to commit yourself to it 120% percent, but you will leave with a skill set that will advance your career, a set of projects and a certification that, in my experience, will attract many recruiters, the drive and inspiration to push yourself to reach your maximum potential, and a support network that will be there for as you pursue your professional dreams post-bootcamp. In addition, in my experience and that of several of my cohort classmates, both during and after the bootcamp, you will become an independent learner in the field of data science who is capable to advance and add to their skill set on their own.  This is an invaluable skill in any data-related role you will hold. In sum, the bootcamp is a highly valuable experience that will leave a very positive impact on your professional life. I am very grateful I made this choice and I can only wholeheartedly recommend it to everyone else.

I was a postdoc at Duke University (Engineering) and my background is control and optimization. I participated NYCDSA Online Data Science Program (10/2016 - 02/2017).

NYCDSA online video lectures have a very high quality. I found that the well-organized class material and lecture notes very helpful to prepare for data scientist job interviews. I can review the material repeatedly until I am ready for the interviews. Also, almost everything I need to pass a data scientist job interview is covered in the program, which can certainly facilitate my interview preparation.

Finally, Vivian and the entire NYCDSA team are extremely helpful for data scientist job searching. From resume/cover letter revision, coding practice, to data scientist technical interview preparation, NYCDSA has enabled me to make a smooth transition from academia to industry.

I found a job at Citibank as a Fraud Data Scientist. Without NYCDSA online program, I would have to spend much more time to find the right direction to achieve what I have been able to accomplish through this online program.

I can’t begin to describe how inclusive, rigorous, and rewarding is New York City Data Science Academy’s Data Science Boot Camp. It is inclusive in the sense that those applicants it admits are not exclusively from among statisticians, mathematicians, and computer scientists. Professionals from other disciplines who recognize and appreciate the importance of a more structured, quantitative approach to business comprise a significant component of each boot camp cycle, providing context, breadth of experience, and real-world application to the data science discipline. In turn, they benefit from the experience and capabilities of their classmates specializing in more technical disciplines.   The boot camp program is rigorous in that it demands broad competence not just in a single language. While competing programs may focus exclusively on developing competence narrowly in R or Python, the NYCDSA boot camp demands that its recruits master both. This gives those who complete the program greater flexibility, as they can appreciate the strengths of each language and invoke one or the other as best suits the task at hand.   Apart from the new skills obtained, the NYCDSA boot camp is rewarding in other key respects. The curriculum is grounded in teamwork, giving participants a greater appreciation of how to build and manage teams in a business context. This team-based approach also fosters friendships among classmates who, as in a military boot camp, become battle buddies as they overcome the significant business and technical challenges they confront. The resulting camaraderie produces a very strong alumni support network that provides boot camp graduates with long-term opportunities for professional growth and advancement.   The NYCDSA boot camp provided me with the precise set of skills I sought, allowing me to continue my career on a higher plane and enrich the value I provide to my clients in their pursuit of market share and increased profits. I am incredibly grateful and appreciative of the opportunities which NYCDSA’s boot camp has afforded me, both personally and professionally.

I took the Part Time Into to Data Science with Python class as a means of hands on introduction to some of the more common and powerful Python libraries used for data science, and I found it to be perfect for that.  This is certainly not as rigorous as a bootcamp, but if what you're looking for is an introduction or even something to supplement learning on your own time, I highly recommend it.  I would definitely say I am now comfortably proficient with the basics of each library covered and I have a great foundation I can build upon.

I will strongly advice not to take up online for the 12 week data science bootcamp offered by NYC data science. It is not worth the money you pay. It is better to do an MS with the same amount. Reasons

1. Lectures are unprofessional. Just plain text and not much plots or anything to really explain things

2. Instructors are just there to read the slides aloud and nothing more. The machine learning lectures and slides are just terrible. It is better to take up interactive tutorials such as datacamp than to review this. There has been no change or improvement from the school having brought this up.

3. Teaching assistants provided are not very knowledgable. They are just there to review your project. You are really lost when you have to ask them a question

4. Online is a big mistake because you are not learning anything significant other than what is being taught as there is less interaction with other students.

5. Projects are just namesake. 

I will remind you - DO NOT TAKE UP ONLINE FOR THIS BOOTCAMP. 16K IS A HUGE AMOUNT

If only I could turn back time and run with my 16k. 

 

This is a highly intensive program with immediate returns. If you want to turbocharge your career progression in the world of data analytics, this is without a doubt the best decision you can make. However, this isn't a free pass into the field of data science; if you do not have the passion or are not willing to put in the work, it will be a waste of your time and money.

Prior to enrolling in this program, my major consideration was: If I skip the program and use the free resources online, would I be able to learn this stuff on my own?

Naturally, this was the path I initially pursued. But with a full time job, even if you put 2 hours aside each day to learn on your own, there will be days where you are too drained and lack motivation. Leaving my employer and investing in this program kept my accountability up and allowed me to gain new skills in 12 weeks that would have otherwise taken months or years of consecutive study. The content in the program is not secret sauce. Things you learn here can be found for free online. But in this generation, what can't be found for free online? Where this program shines is the extremely bright instructors and peers that you get to interact with on a daily basis. There were countless times during the lectures in machine learning where I was lost. If this was a MOOC, I would probably be replaying the video for the 7th time and then hopelessly closing the tab. At NYCDSA, you have access to some of the most talented and extremely patient resources (with the credentials to back it up) to help you until you understand what's going on.

The instructors are there for your to utilize, but you need to take action on your own. If you get the instructors engaged, their passion for data science is very contagious, and you will learn a lot just by bouncing ideas off each other and actively problem solving. This will be extremely advantageous for your projects. Please don't sit idle and let the instructors debug your code, you will learn nothing except how to press ctrl + enter.

In regards to job assistance, NYCDSA is a great way to expand and grow your network. Vivian and Chris both have deep connections to the data science employers in the NYC area. Although the company I am now employed at wasn't a result of the school's networking, I have gotten many interviews and employers reaching out to me solely due to Vivian and Chris. At the end of the day, getting a job requires putting in the work. Do not expect to come out of the program with employers throwing themselves at you for simply having NYCDSA on your resume.

Vivian and Chris provide great support to help you improve your job search experience, but they will not baby you. There are 40+ students they need to support. If you need help your best bet is to reach out instead of waiting around for Viv and Chris to ask you if you're okay.

My overall rating is 4 stars due to the course pacing. Whether this was an effect of too many/ too diverse of a class, or change in instructor(s), There were a handful of lectures that went too far over the scheduled time. For some of the later lectures in the program, there was a pattern of discontinuation of lectures. This was difficult to manage especially if it occured over a weekend. For example, if a Friday lecture ran over time, it would carry over to the next morning session on Monday. I would have much rather prefered a continued lecture in the afternoon while the material was fresh in my head. Although this was my personal experience, rest assured that Vivian and Chris are constantly improving the student experience and something like this is probably already being worked on.

TL;DR: come in with a passion, put in the effort, there is much to be gained

This course was a solid intro to using python for simple data analysis projects. Tony was a great instructor - he was very thorough with his explanations and made sure that we got through all of the materials necessary for us to progress through the curriculum. My main knock on the class was how short it was - if you're thinking about taking this class, keep in mind that there are only 5 classes, so all of the material that needs to be covered is jam packed into each session. While we did end up covering everything as displayed on the curriculum, it's harder to remember everything that is densely packed into each class.

I am Data Scientist at Anheuser Busch today and I am going to share my experience with finding the right school and struggle that I faced.

Search for Schools:

It was hard to choose the right school for Data Science just by being online, I had recently graduated as a robotics and automation engineer and all my programming skills were result of self-education, In late August I was selected for the Interview process at New York Data Science Academy and General Assembly.

                                          I first came to New York Data Science academy and I was interviewed by one instructor and one Business person, I never met them after that day so I don’t remember their names now, they asked me a series of programming questions, pretty basics some were based on the online application I filled and later some on my knowledge of statistics, it seemed to go well but at the end of the interview I was rejected.

                  The reason was I was not ready for the bootcamp, they had previously seen other student promise that they can learn quickly but what ended up happening was they left the bootcamp in middle, I was upset cause I really wanted to do it, but I also knew I was in a hurry, they suggested to take it slow and come for next cohort so I will not just be able to survive the bootcamp but also learn and really take something valuable from the camp. 

                 I later went to General Assembly and attended their interview and introductory session, they had a much larger location, also a big conference room, I really like the place, I was provided an instructor who gave me a brief understanding of the course and what it would feel like. A week later I had my interview with Lally M, I had filled and application online but I never answered any programming questions, Lally was very nice and asked me few general questions, and also gave me few advices but all and all she did not really bothered if I was ready for the cohert, at the end of the interview she said I can join this cohort. 

Prework:

                  It’s obvious what I did next,  I left the option of General Assembly and prepared on my own for next 3 months, I met Vivan personally In November she is the Co-founder of New York Data Science Academy, she gave me access to a online learning and testing platform which is called the prework for the bootcamp, it covered all the basics of Python and R.

During the Bootcamp:

My Bootcamp started on 09th January 2017, I felt very confident during the bootcamp, I remember Chris said on the very first day "There are very few things in life that will give you a chance to have absolute devotion", in the beginning we were introduced to all the subjects again for first week, so even if you did not do prework you would not suffer entirely but I would suggest do your prework well.

                             Things started to get serious as soon as second week finished and it did not stop after that, we had classes from 9:30 AM to 3:00-4:00 PM, after which there was homework at the end of each day, added to it we had to do our first project, also I had to study for the subjects I learnt in the class, also I had to keep my LinkedIn and resume up to date, also you better keep going to networking events, all in one day with you getting enough sleep and food to have the same energy the next day.

Curriculum:

1) Introduction to R and Python , Unix (which helps in big data part)

2) Machine Learning - (a) Importing Data (b) Foundation of statistical Methods (c) Missing value and Imputation (d) Simple Linear Regression (e) Multiple Linear Regression (f) Generalized Linear Model and kNN Model (g) Regularization and Cross Validation (e) Tree Models, Bagging , Boosting , Random Forest (f) SVM (g) Time Series Analysis (h) Cross-Validation (i) Bootstraping (j) Feature Selection (k) Regularizartion (l) Hyperperameter Tunning (m) SVM (n) Tree Models (o) Association Rule (p) Naive Bayes (q) Principal Component Analysis (r) Clustering (s) Unsupervised Learning (t) XGBOOST (u) Tensorflow (v) Netral Network (w) Concolutional Neural Nets.

3) Big Data - (a) Hadoop (b) pig (c) hive (d) nosql (e) Apache Spark (f) DATAiku(platform) (g) DataBricks(platform) (h) Virtual Environment - Docker.

Project:

1) Try to solve real life problems in your Projects, you will have the freedom to choose your projects, choose them wisely. I had a chance to do one of the Kaggle project, it helped me learn from some of the best Data Scientist in the world and if I did not understand something in any project, the teaching assistants came to rescue.

2) You will do 4 to 5 projects including Capstone, finish them well, do not leave any part mid way, submit your code on Github and you will be told to write blogs on the platform provided by the academy, write them well.

Job Assistence:

1) Mock Interview sessions - Coding Test, theory of Machine Learning Test.

2) Resume Writing Session - Resumen writing, cover letter, Job status sheets, email - cold warm, Meeting Letter, thank you notes.

3) General Prep Session - Photo Shoot, Linkedin, In house Meetups, In house video recording during project presentation.

4) Interviews - Hiring Event, Introduction to Employers, Referal.

The Bootcamp:

The bootcamp changed my life as I am no longer the same person I was before January, even though 50% students in my batch had a PhD, 46% had a Masters and many years of job experience, I was among the 4% Undergraduate category who luckily got here, but this played in my favour as I learnt a lot from my peers, I truly came out a Star in my own eyes, I would like to give the credit to Vivan and Chris as a host in my Ex Home, who were supportive at the end of each day, coming up to you and checking on  you if you are still doing okay, the reason I finished all my projects in Flying colours was my Teaching Assistants, who stayed back every day till 7:00PM sometimes and came back in at 8:30 AM, yet managed to stay active on Slack during the night during, I would also like to thank my peers with who I learned many Industry Skills and Best Practices, during my group projects I was led by a Math PhD Mr. Domingos, who now works at google, I had a chance to grow enormously on his team.

At the end of the cohort we all graduate in flying colours, it was very emotional day, thank fully we all are still in touch, I strongly suggest to make meaningful relationships during the cohort, after the school, you constantly have doubts and questions, like after job interviews, during your projects in the company, your colleagues will help you understand and overcome these doubts. 

After the cohort we had our official Hiring day just a week later on 5th April 2017, I managed to meet 12 - 15 different companies, out of which the one I had a heavy interest in was IBM (who would not). Later I got a referral from IBM and I am currently Interviewing as a Data Scientist for IBM advance Global Analytical Team. I was trained to crack these interviews and trained to speak and write during the bootcamp, so I would do pretty well. One more advice will be to take this week and go through all the lectures once again and not give in the temptation to rest or relax. 

I got my offer after 15 days of the bootcamp but for many it can take few months. At the end I would say 3 months of bootcamp can only prepare you to understand the science behind the scenes and provide capacity to be a more analytical person, but to be a good Data Scientist, I still study everyday, learn about ongoing research and connect with knowlegeable people.

The 12-week Data Science Bootcamp offered by NYC Data Science Academy is a very intense but also very rewarding experience. It is very demanding and forces everyone to keep up at all times. That being said, I can only recommend taking the program if you want to become a data scientist. Here you'll learn all the skills you'll ever need for working in the field.

The bootcamp starts with an introduction to Unix and Git, followed by two weeks each of introduction to R and then 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 such as Hive, Pig, and Yarn, database programming (SQL, NoSQL) and various useful jump-start sessions such as Shiny, Knitr, Geo/Maps. Every lessons covers both theory and practice, here in terms of R and Python code using basic and well known datasets. From time to time, industry professionals and alumni drop by for guest lectures in the afternoon.

For questions concerning assigned homework, project work or just better understanding of the material, great TAs are at hand throughout day to help out every single student to make sure everyone gets the best out of the bootcamp.

Every cohort is a very heterogeneous group consisting of people of all kinds of backgrounds, from fresh graduates to senior managers and PhDs from all kinds of fields, all interested in learning everything they need to know about data science.

To make sure everybody will be able to apply their newly-learned skills in the foreseeable future in the real world, they also have sessions on how to get the job you want, covering all aspects from resume writing to actually meeting people looking for candidates at one of their networking events. Hiring assistance continues even after the bootcamp is finished.

The 3-month study at NYC Data Science Academy was a wonderful experience. For me, I polished my R and Python skills, did 5 projects including web scraping and machine learning, and more importantly, developed strong connections with many great people. 3 month after graduation I was hired as a data scientist by a data research company in NYC. 

The curriculum is well organized. We learned R and Python programming, statistical analysis and machine learning. During the last few weeks, big data tools like Hadoop and Spark was also covered. As a student coming from an academic background, I feel the classes taught by NYCDSA are pretty good. The knowledge covered in this class are broad and the difficulty feels just right. You can't expect to learn everything in 3 months, but the courses give you the ability to further explore any data science topic on your own. Both instructors and students are awesome in my cohort and I really learned a lot from them.    The job assistance is good. In my opinion, the bootcamp have tried their best to help the students. There are network events, resume editing, and mock interview to help you prepare the job hunting. Vivian and Chris also arranged a few on-campus interviews, which were great chances for practice. It should be noted that the career transition into data science is not easy, and a 3-month study can't change your life. Only high-quality work, nonstop studying, and active networking can make this happen. 

Bottom line: the bootcamp is a swindle, cheat, and ripoff. Save yourself the frustration.

If I could turn back time, I would not have wasted $16,000+ on tuition and moving to NYC. My money would have been better spent at an accredited program. The whole operation seems glued together like a popsicle stick diorama...it was like a total free-for-all. No rules, structure, or guidance. The few rules in place were hardly ever enforced (homework deadlines? grading? feedback? none). We were left to fend for ourselves with barely any help. I learned more from other students who had previous experience than any of the instructors, most of whom listed on the website had nothing to do with the bootcamp at all. I agree with some of the other posters...Vivian will accept anyone to make a buck. Some people in my cohort had backgrounds so far from data science I wonder how they got accepted in the first place (fashion? what? ok...).