NYC Data Science Academy

I really enjoyed the R course with instructor Amy Ma. The content is very practical. It can be directly applied to solve real-world data analysis problem.  We had many in-class coding exercises, which helped us understand the R syntax. 

Also, Amy tried her best to provide a lot of useful resources. We could tell that she is very passionate about what she is doing, and she is patient with students. We could reach her after class through email, even the course was finished. I highly recommend this course to anyone who is interested in data analysis and wants to learn R from the beginning. 

 

I really enjoy taking the R course with Amy Ma. She's patient and thorough. Her analogies made it easier  for me to understand the R syntax. I really like the in-class coding exercise and it was good to practice what I have learned. Amy's class is very interactive. She doesn't just talk off the slides. She always codes with us and shows us different ways of doing the same thing or breaking down the code part by part. She would compare and contrast the nuances between different commands, which was quite helpful. 

The NYC Data Science Academy's 12-week bootcamp is an intense, well-thought out and comprehensive program that accelerates one's immersion into the world of data science. Having worked in IT infrastructure consulting for 8 years at one of the Big Four, I wanted to shift career orientation and focus more on data science, elements of which had begun to interest me over the course of several client projects.

 

Comments on the program:

• Strong teaching staff who is clearly passionate about teaching data science as evidenced by the late evenings and weekend support
• Focus on concepts and skills that are actually relevant to the marketplace
• Broad and dense curriculum (R, Python, machine learning, Hadoop, Spark, MongoDB, etc) to maximize learning in a limited timeframe
• Flexibility and nimbleness of the program to adapt to feedback from alumni, employers and the market to maintain the relevancy of every topic taught
• Good mix of lectures, homework and projects
• Helpful job prep activities such as interview coding simulations (and others that I won't spoil)
• Eclectic mix of students (though this may vary by cohort) that allowed us to learn from each other's diverse backgrounds and areas of expertise, and develop deep personal friendships and professional relationships
• Opportunity, if selected, to present projects at Data Science Meetups which offers networking opportunities as well as practice of presentation skills

 

Suggestions for improvement:

• As data science is a dynamic and evolving field, keep up with the latest advances such as improvements in R packages and update the curriculum accordingly
• Give harsher constructive feedback to students when required
• More transparency on student evaluations overall and for Meetup project selections as well

 

Recommendations for aspiring students:

• Be committed: the bootcamp is demanding but that is by design. It's an investment; you get out what you put in. Don't show up late, don't ignore the homework. If you do, it's your loss
• Don't fall behind: there's a lot of work and learning a very rapid pace, not to mention homework almost daily
• Be proactive: reach out to the TAs or the instructors for feedback (not just help), read up on machine learning outside of the bootcamp, talk to your classmates on how to collaborate
• Manage your time: you will have to juggle many responsibilities and will most likely feel overwhelmed in general. That is also a skill you will need in the professional world
• Learn to be autonomous: don't run to the TAs or the teachers for help as your first recourse. Google, StackOverflow and other resources most likely already ahve the answer you are looking for. Only when you have made a decent attempt at figuring out the problem should you ask for help. After the bootcamp, that safety net will no longer be there so it's best to practice early

 

Overall, very positive experience. I can't speak to the job placement assistance as I returned to my original firm, but regardless, I'll maintain the great relationships built with the Academy.

NYC Data Science Academy (NYCDSA) provided the platform to pursue my dream career.  The curriculum is well thought out, with detailed notes, hands-on projects, and great hiring partners. NYCDSA gave me the tools to be come a data scientist, and the exposure to land the job.  Truly one of the best investments I have ever made!

NYC Data Science Academy's 12-week bootcamp was a life-changing experience. It was an intensive 3 months but definitely helped me transition from healthcare to data science.

Comparing against other bootcamps, I decided to go with NYCDSA for its thoughtfully planned schedule. From the large volume of content to the scheduling of each day, it had what I needed to succeed. Each day consisted of lectures with really useful slides and concluded with time for homework and projects in the afternoons. The allocated time in the afternoons gave us time to digest what we learned and the homework assignments reinforced the new knowledge.

Coming from a background in biomedical engineering and biological sciences, I was used to being told everything I had to know. The bootcamp gives a lot of information with its detailed lectures but also challenges students to find their own answers. For example, a homework assignment had a problem mentioning a function that was not mentioned in lecture. We had to research it and learn how to use the function before we could do the problem. This taught me how to be resourceful and find answers on my own instead of relying on someone to tell me everything. Because data science is a growing field, you cannot expect to learn everything in a short period of time but should know how to find solutions on your own.

Being challenged to learn may sound intimidating but it really isn't when you're surrounded by supportive peers and staff. The staff are extremely hardworking and friendly. They stay late, sometimes even until 11pm and they love what they do so they won't be grumpy or annoyed at you. They also come in on the weekends and will help with homework assignments and projects if you require it. The TAs are excellent resources who are passionate about data science and motivate you to always do better.

Advice: Try to familiarize yourself with the suggested R and Python readings before you begin the bootcamp so that you can spend less time trying to understand concepts and more time on the data science parts.

Even after graduating from the bootcamp, I still feel like family around them. The instructors and staff do not forget you and continue to help with your job search. Vivian actively connects you with resources and posts jobs you may be a fit for. She also holds coding review sessions so that we are better prepared for interviews.

Job Prospects: Besides the countless data scientist and analyst job posts found online, NYCDSA hosts a hiring party at the end of the bootcamp that connects recruiters from multiple companies with students. It gives you a big opportunity to speak with recruiters and build connections. I interviewed with one of the hiring managers from the event and got an excellent data scientist job approximately 1 month after graduation. You have other opportunities to stand out from crowd when Vivian reaches out to her contacts and sends in your resume so you're not just another applicant in the pool. There are tons of jobs and the support from NYCDSA is outstanding.

I have no negative memories of the bootcamp besides the late nights spent on projects but you get as much as you put into the program. Overall, the bootcamp does a good job preparing you for a career in data science as long as you work hard for it. Your peers will be your friends and consultants for your data science problems. I would join another cohort at NYCDSA if I could!

I took the data analysis and visualization with R class in June. The lecture and presentation was very thoughtful. The instructor was very helpful. After taking the course, I can actually pick up some skillsets like doing some descriptive analysis and creating some plots. But more practice is needed outside the classroom if you really want to get something from the course.

Overall, I would recommend the course to people who have some coding experience and would like to learn more on the topic.

 

I finished the bootcamp yesterday. I have a BA with honors in Math, an MA in Applied Math, and an MS in Civil Engineering. I have 8 years of work experience in both the private and public sectors. I committed to this program to help me transition to becoming a data scientist. I had minimal professional programming or statistics experience when I applied.

• I bought a new computer and studied statistics, R, and Python for over a month before my first day in the bootcamp.
• I worked more intensely and consistently at the bootcamp than I've worked on anything over a 3-month period, either in school or in a job.
• The staff are maybe the bootcamp's finest feature. The instructors are technically proficient, patient, and articulate. Somehow, I didn't feel intimidated, more inspired. In three months, every time I requested support, I was supported.
• The office has a simple aesthetic and is well-equipped and well-maintained. It is often crowded, but overall a space where I felt focused and could work.
• I gave the curriculum 4/5 stars. I found the material fascinating. There were many times when I simply didn't keep up. There is a lot of material. Read that sentence again. The curriculum moves so quickly that it often felt like a day-tour of Europe.
• I found my classmates highly-educated, focused, and committed. I forged some excellent working and social relationships.

Overall, I recommend this bootcamp under the following conditions:

1. You will commit yourself to this program for 3 months. For these 3 months, this is what you will do during the day and in the evening, weekdays and weekends.
2. With whatever time you have before the bootcamp, you will study statistics, R, and Python.
3. You accept early on that sometimes it will be acutely stressful and overwhelming.

Having completed the bootcamp, I see the value in Vivian's approach: by working at capacity among such skilled staff and focused students, my skills and knowledge developed quickly. Overall, this bootcamp worked well for me and I'm glad I did it.

This is an awesome program you will not regret attending! 

I was in the Jan-April 2016 cohort. The course covers everything you need to know to apply for data scientist jobs. We started from the fundamental of stats in R, and moved into machine learning in both R and Python. In the last two weeks we also got a fair exposure to big data tools like Hadoop and Spark. The instructors we have are AMAZING!!! They are super knowledgeable and also very passionate about data science. TAs are the most hard working group of people I know! They really try their best to help you. Students at the bootcamp are impressive as well. Most of them either have a phd degree or have significant/successful work experiences prior to joining the bootcamp. We did five projects during the bootcamp which you can totally show off during your job interviewsss! And you will have a least a few job interviews guaranteed during/after the bootcamp. They really tried their hardest to help you preparing and securing job interviews. I personally had at least 5 interviews while I was still in the bootcamp, and was hired only two weeks after the bootcamp ended.

The program wasn’t easy, you will have a ton of homework and projects to do, but they are always there to support and help you. I would recommend this 12 weeks bootcamp to anyone who wants to be a data scientist or simply interested in data science. 

This course is ideal if you already have programming experience. I had experience with Matlab and R, so this provided the answer to the "how do I do that in Python" question. If you have never programmed before, go through Learn Python the Hard Way very thoroughly before enrolling. You will get the most out of this course if you have already learned basic programming concepts and can therefore focus on the intent of the course: data analysis and visualization.

The class teaches very practical aspects of Python and data manipulation and visualization. Often we know what question we want to ask and maybe even already have the data, but need to get it into a form to analyze and present visually. This course was good at preparing you for that. Little time was spent on cleaning data, most was spent on learning Python and manipulating data and how to visualize it. 

The instructor, Liz, was easygoing and personable, which made it very easy to ask questions. She was also knowledgeable about the topic and could give insights into what it was like to actually use these tools on a daily basis. I enjoyed having her as an instructor.

I'm only giving it four stars, which to me means very good, because five stars to me means truly exceptional. In order for this course to be truly exceptional, it would need to ensure all students were up to a certain standard in Python, allowing the class to go into the data analysis and visualization much faster. Given that the students in the class had extremely different backgrounds and levels of programming experience, I was very impressed.

In conclusion, if you are using other tools like Excel and have some programming experience, I recommend this course as a good way to move your work into Python to take advantage of its speed, flexibility and packages. I was able to create visualizations of crime and weather data I got from the NYC Open Data site in only a couple hours after taking this course. Well worth it!

I took both the intro to data analytics and the machine learning course, both using R. Both the instructors Luke and Shu went out of there to answer emails and help me get a better understanding of the field. I'm new to data science and computer science and after the course, I felt very comfortable using R and discussing machine learning and data science with other individuals. 

Well, i could have learned much more things by finding a good book and reading it or taking online course which would've been much more chaper as well. First of all if you re beginner at python , this course deffinetly is not for you . You get very brief information in the lectures and you have to figure out  rest by yourself. I took this course just because i didnt have time to learn by myself and i thought they will actually teach me , not pushing me figure out by myself but obviously i was wrong, so disapointed.

It was very bad idea to pay more than $1500 and take this course.It doesnt worth at all !

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.