NYC Data Science Academy

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.

I am really enjoying taking the NYC Data Science Academy data science bootcamp remotely. I find their online classroom and materials very effective for learning the fundamentals of data science. The videos are very informative and the material well communicated and taught by the lecturer. The accompanying slides are clearly written and mostly self contained and you can learn a lot, just by reading them. The course is a nice blend of theory and practical programming experience using R and Python and other tools.

The learning process is aided by doing and submitting the homeworks for the lecture materials, as well as completing project assignments.
I interact frequently with the TA assigned to me. We often have Google hangout sessions where he helps set up my environment on my laptop like Git, R and Python. We also review my project assignments through Google hangouts where he provides valuable feedback and suggestions. The TA is very helpful, competent and knowledgable.

I would definitely recommend the online version of this bootcamp.

I attended the 12-week bootcamp this past summer and had a great experience overall. I was able to build a solid portfolio of data science projects and got a lot of job search support. The curriculum assumes a basic level of statistics knowledge so for someone like me whose background didn't include any it could be frustrating at times. However, they are serious about student feedback so I believe the course will only continue to get better. You can expect to put in a lot of work but as always what you get out depends on what you put in. Ultimately I landed a job I'm very excited about, and I had a positive experience with the course, instructors, and fellow students so I would definitely recommend it to anyone interested in a career in data science.

Now I am going to start my new career as a data scientist.  I would like to share my 2 cents for this bootcamp and hope it would be helpful for the coming students.  Also I hope through those suggestions, you can have an idea about the bootcamp.

1.  Be open - This is a boocamp, not a usual school class or an online course.  So share your experience and expertise with others.  You will learn much more from each other.

2.  Be in a hurry - This is a short bootcamp, whereas it covers a LOT of content.  So be ready to work hard.  You need to have a sense of urgent that you are going to jump into interviews after 3 months.  Without your own hard working, it is hard to achieve the success after the bootcamp

3. Be brave - This is a hard bootcamp.  Some students slept less than 6 hrs per day for three months.  Does it sounds scare?  However I would like to say that be brave, after learning with others, you will see your shining point and know how to show your merits to others.  So be brave to take challenges and be brave to share with others.

4. Be collaborative - I hope after the bootcamp, you are not only getting a good job(s) but also getting a lot of friends.

Enjoy the bootcamp,

I attended the Data Science Bootcamp in summer 2015. It was a very enriching, useful and enjoyable experience. It offered plenty of important things that one couldn't hope to find by taking online courses or reading textbooks. The instructors possessed valuable knowledge and perspectives in the data science industry, and were able to share them with the students through various activities (e.g. lectures, invited talks, meetups, company visits, individual counseling, etc.). Also, students had a lot of opportunities to interact with established data scientists, as well as collaborate with fellow aspiring data scientists on real-world projects.

I took both Data Analysisand Machine Learning with Python with Vivian.

I highly recommend these classes to anyone who wants to take their analytics skills beyond Excel, pivot tables, and averages and into more advanced predictive modeling methods. Luckily, a lot of the work has already been done for us by the developers who created pandas, matplotlib, statsmodels, and scikit-learn. I didn't know anything about these tools prior to taking this class. Vivian makes machine learning easy. At work I can now stand on the shoulders of Python's giants. Pretty cool. Extremely useful.