NYC Data Science Academy

I chose NYCDSA over similiar bootcamps because they seemed to have largest breadth of content and also seemed to be the most challenging, and I believe they delievered in both those aspects. You will learn a lot, and you will be challenged, even if you come into the bootcamp with some experience in data science.

The lectures themselves are very enganging, and the intstructors are very knowledgable. The course content (slides, lecture code, homework, etc) are not only excellent for learning the matieral, but I think they will also be valuable references going forward.

I feel the bootcamp has prepared me well for my job search. I had several interviews set up before the bootcamp had ended, and my first offer a few weeks after that. I'm confident that if I want to interview with more companies that NYCDSA can help to make this happen.  Employers are interested in the projects I've done with the bootcamp, so I can get their attention, and the course material has trained me in the areas they are likely to test me on during interviews.

My time at the Nyc Data Science Academy was some of the best three months I've ever spent. This is an intense bootcamp but it the instructors are absolutely amazing and push you to excel. Christopher (the main statistics and R instructor) is one of the best people I've ever met and you are guaranteed to be inspired by him. The TA's are some of the most hard-working people you will ever meet and are always available to help (most days until 11pm - not sure if they even go home!). 

All my peers in the cohort were positively affected by their experience and you should attend without hesitation if you're accepted! Vivian, the academy founder, is personally vested in helping her students find jobs and she is extremely well connected and caring. We are fortunate to be on the cusp of this new and exciting field and have the opportunity to attend such a bootcamp. 

The program offers a very good course for building foundational data science skills.  It is very evident how motivated the faculty and instructors are in helping their students achieve their initial career goals in data science. The curriculum covers topics and subject matter that is considered mandatory for any entry-mid level data scientist and the program does a good job preparing students for data science oriented interviews.  Data Science is a large field that cannot fully be appreciated in 12 weeks.  In spite of this the NYCDSA does a great job designing both the breadth and depth of their curriculum, which they are always improving and expanding.  
Overall, I had a very successful experience and had multiple interviews both during and after the program, which eventually led me to my present dream data scientist job.  

Overall Pros
- Talented and very bright staff and instructors.
- Very good network with NYC companies
- Growing company
- Available staff at all (or most) times
- NYC Location 
- Homework is reasonable, challenging, and yet fun
- Curriculum covers many basics that are important for data science interviews. 

Overall Cons
- Growing pains, which should be expected for any growing startup in a hectic and driven environment such as NYC.  
- Hiring network is fairly limited to the east coast (from when I attended), however last time I checked they are making successful efforts in branching out to other regions.

My Advice:
The program is a goldmine of learning potential for any student who is willing to put in the hours both inside and outside of the classroom.  In order to yield the most benefits from the program, students should be flexible and nimble.  Data science is a constantly growing and changing field, thus the curriculum must also constantly change.  Furthermore, students should constantly engage with the instructors and TA's.  The curriculum goes at a face pace and it is their (the faculty) mission to ensure that all students maximize their learning.  From my personal experience, 30% of what I learned came from the lectures while the other 70% of what I learned came through working on projects and problems after class with my peers and TA's.  

Conclusion:
I would highly recommend this program to any person who are willing to work hard and put in the hours to learn and reinforce the material.  

I attended the inaugural bootcamp in from Jan 2015 to May 2015 and loved it.  I came into the program with a programming (java, matlab) and math background and some data analysis experience and was quickly met with tons of new material and challeneges.  I loved the fast pace, yet detailed lectures.  They provide a thorough introduction to R and Python followed by lectures on machine learning, statistics, and other data science technologies.  The best part of bootcamp is working on projects of your own design under the guidance and expertise of the lecturers. Everything I learned and created directly helped me get a great internship and later a great job.  I would recommend this botcamp to anyone looking to fully immerse themselves in the field of data science in order to better themselves or land a interesting job

I attened 2015 Summer Data Science Boot Camp with NYC Data Science Academy. It was a positive experience and I would recommend it to anyone who doesn't have data science background and wants to step in this area. Especially if you are in the middle of job searching, and have great motivation and determination to learn. The advantage of being in a full-time boot camp is that the immersive learning makes time go faster without you realizing it. You can easily spent a whole day focusing on one data problem without any distraction. Just note that this bootcamp is for people who wants to learn basics and fundamentals, not for who wants to be a machine learning expert!

Before I enrolled in the Data Science Academy's 12-week data science program, I had spent nearly a year exploring data science with almost nothing to show for it. Coursera, books, Kaggle, you name it. A bit discouraged and overwhelmed, I began the data science program with high hopes for strong teachers, a great community, and a rigorous crash course on all things data science.

I got all that and more. Proof: I recently began a new job, and was able to hit the ground running on literally every front the company threw at me. Statistics and algorithms? Check. R programming? NYCDSA took us through almost all the packages my new company uses regularly. Python? Same deal as R. Infrastructure, AWS, distributed computing, visualizations, SQL? All check. And the NYCDSA enabled all of this - brilliant, helpful professors, well-designed homeworks / lectures, and great connections to the real data science world.

Make no mistake - you'll be working unbelievably hard. Dozens of homeworks, ~5 projects, tons of slides and material to learn. But that's what you want, right? If you're serious about boosting your career, NYCDSA is the perfect place for you.

I took the Machine Learning with Python class to get a fast and quick intro on how to code machine learning algorithms in python. 
Our instructor, Shu, was very good and accommodated fully the needs of the class. He knows both the theory and the coding parts. 
I think the course strikes a good balance between over-viewing techniques  and offering hands on specific knowledge so that you
can go away and code on your own after the class is done. 
I would recommend this course to anyone who wants to get started as quickly as possible with Machine Learning in Python. 

I attended the Big Data with Hadoop and Spark course, hosted and led by NYC Data Science Academy. My objective was two-fold: first, to gain a deeper and practical understanding on emerging 'Big Data' technologies, more so than what academic publications or industry white papers currently provide; and, second, to familiarize myself with the skill set and experience to expect from the new generation statisticians, or Data Scientists. With a background in Business Intelligence, Architecture, Risk Management and Governance on Wall Street, I find that foundational skills remain the same: mathematics and statistics. However, with the commoditizing of data storage and massively parallel computing, Data Scientist today are capable of solving problems reserved for an exclusive few in decades past. The course did not cover configuration of the Hadoop environment, but thanks to the engaging and knowledgeable instructor, clues on challenges and potential pitfalls were generously shared. I highly recommend this course not only to professionals or recent graduates looking to hone data analysis skills, but also to anyone with an interest or stake in Big Data.

Three months ago I had no idea what I had signed up for. I wasn't even sure I had made the right choice--not just with NYCDSA, but data science in general. I didn't know how to code and all my statistics experience came from an academic setting. Three months later and I can hardly comprehend how I got to where I am now, but I know for certain I wouldn't have gotten here without NYCDSA.   On the first day it was clear that I was a bit of a minority. It seemed that everyone had more experience than I did--I had been a classroom teacher for 6 years, and an English teacher at that--but this wasn't a time for excuses. No matter what level you arrive at, you can't survive the program without being all-in, and that might be its greatest strength. I (and the rest of my cohort) kissed goodbye to our social lives and fought through three of the most challenging, stressful months of our lives. Suddenly I'm a proficient coder in two languages, I understand the statistical nuance behind complicated machine learning algorithms, and most importantly, I landed a job that is wildly better than what I imagined I could get. Seriously. I took the screening interview just for the practice. And then I got another interview. And then another. And then a job offer. And throughout, I knew the answer the virtually every question they threw at me. And for that, I have to thank NYCDSA.

I had a great experience at the NYC Data Science Academy.

To give you a little background, I have a PhD in Biochemistry and did a Post-Doc in computational biology and bioinformatics and then worked in industry for a couple of years in both technical and non-technical roles. With the recent advent of data science, I made a decision to make a transition to data science and wanted to get up to speed in data science, Python and R, as well as machine learniing, in a rapid but focused manner. The NYC Data Science Academy provided the perfect oppotunity to do so.

The things that stand out about the Boot Camp were:

• Quality and enthusiasm of the instructors - Given the broad range of the participants, the instructors really knew how to challenge us.
• The Teaching Assistants - The TAs were patient and provided great guidance and instruction.
• Quality of the participants - It was a great experience to go through the boot camp with a really talented group of people. 
• Projects - The individual and team projects really gave me the opportunity to challlenge myself and stretch my abilities. It also provided with a nice portfolio which I can show potential employers.
• Vivian and Janet - The heads of the Boot Camp really showed that they cared about the participants and challenged us to work hard and remain engaged.
• Guest speakers - The quality of the guest speakers was really outstanding.

A word of caution about participating in the Boot Camp. Be prepared to work like crazy. I worked 12 to 14 hours a day, 7 days a week for three months straight. 

 

I though the bootcamp was an amazing experience.  It's helped me build a stronger statistical and programming foundation to start a career in Data Science.  It taught me the most widely used statistical learning methods in both R and Python.  We also covered topics employers look for like SQL and Hadoop.  The bootcamp involved daily lecture  and homework and was punctuated by projects to apply what we were learning.  We then had the opportunity to present our work to our peers and at monthly Data Science Meetups. The brought in weekly data science speakers to give us a sense of what being a data scientist in the real world is like.  These speakers included Owen Zhang one of the top ranked Kagglers, and Kirk Borne the head of Data Science for Booz Allen Hamilton.  The last two weeks of the bootcamp involved resume review, interview prep, and final projects.  They also helped us find jobs by actually bring data science recruiters and HR people to the bootcamp.  This program will LEFT JOIN your current life with a career in Data Science.

I attended the data-science bootcamp offered in NYC and had a great experience! I learned a lot on every aspects of data-science and machine learning:

• the theory
• the tools
• coding
• and a lot of practice through homeworks, in-class labs and projects

It is very intensive, you will work ~12h+/day and on weekends, but you will leave the bootcamp with so much knowledge, coding experience, practice, 5 projects added to your linked-in/resume, 5 blog posts, a github account to be proud of  and even, if you want to, a participation in a Kaggle competition.

The team is amazing. Vivian will do everything she can to improve your experience and has a huuuuge network:

• This week, for example, she organized drinks with 20+ companies who came to meet with us (ranging from Guggenheim Investments, Two sigma, Goldman to Medivo, Draft Kings, About.com and many startups too).
• Last week, she got Spotify to bring in 3 speakers who then individually interviewed 15 people the rest of the afternoon!

Janet, also will be in charge of continuously improving the program. That girl does not need to sleep. There were nights were I would leave at 11pm+ and she would still be there. A few weekends/sundays, I came to the bootcamp to work on projects with team-mates and she was there. She is incredible and really dedicated. She organises "Therapy sessions" every Friday to make sure we address and confront every problem we have encountered during the week which is really useful.

The instructors are friendly, professional and knowledgeable. Every class has slides and code. I saved everything. What a resource this is! I have all the theory and code right there on my computer, no more looking on google's 20th page of results to find something somewhat relevant, or reading un-understable wiki pages about all this machine learning. Here, the way we learn is:

1. theory briefely (no proofs) but complete.
2. focus on the different parameters, what they do, how they affect the model etc...
3. then code and actually show how to use all this
4. then homework to let us try to replicate what we just learned
5. then projects to make sure it sinks in!

rather than everything you will typically find on-line which is: theory and then more theory.

If this was not enough, on top of all the team and instructors, you'll have access to TAs too! They are very nice, smart and competent... and especially they are veeeeery... patient with us and our questions!

Additionally, you have projects that you have to present to the class. So you get valuable practice both in presenting and also in collaborating with peers that no amount of sitting behind your screen can bring! Everything is recorded and edited by a pro. All the classes and your presentations too!

Finally, they will regularly bring presenters to teach us about their projects, the real-world problems they face at work etc... Our class mentor (yes we also have a mentor/sponsor) is also amazing and very helpful.

And lastly, (I promise that's the last comment!) they will bring professionals in to help you optimze your resume, your linked-in etc... and prepare you for interviews etc...

Overall I am really happy with the program and glad they covered both Python AND R. I know some bootcamps do not teach R and the reality is that most companies use R and R is must. I am very grateful to everyone involved and working so hard to make this bootcamp a true success.