12-Weeks In-Person/ Remote Live Data Science with Machine Learning Bootcamp

I would recommend this program to people who are interested in starting or enhancing a career in or related to data science. The program covers a wide range of topics and they constantly add new materials so you can learn the tools that have high industry demand. I just started working as a data scientist and engineers at my company are learning these new tools as well. 

I highly recommend the chief instructor, Chris, at this bootcamp. He is a talented teacher. Those who have prior experience taking a machine learning or a statistics class would understand that it is not easy to have a good instructor. I took statistics and machine learning classes at university, but Chris surprised me with better ways of understanding statistical concepts and advanced algorithms.

Everyone enters this bootcamp with high expectation in education and career assistance, but you are the only one who can choose to get the best out of it. The TAs and instructors are very helpful when you have questions and they provide guidance to the right tools and methods. I suggest anyone who comes to this bootcamp to be prepared to work hard and learn a lot of new things in a short period of time. 

A final suggestion to those who are interested in becoming a data scientist. The most important thing that I learned from this bootcamp is modesty. Modesty is critical because as a data scientist, you never want to assume results. Also, data science is developing field and requires continuous learning even after the program. I would recommend this bootcamp to anyone who is ready to join the exciting world of data science.

This 12-week data science bootcamp is great. The faculties have created an excellent curriculum to help you get in touch with almost everything you need to be a data scientist/engineer. Sure they did not cover every relevant theory, but remember this is only a 3-month bootcamp, which is designed to give you a "jump start," not a full-time college degree.

Besides the curriculum, most of the faculties are brilliant and always willing to help. Also, more importantly, you will make friends with people from many different backgrounds, which in my opinion is even more valuable than the course itself.

Regarding the career development, Vivian and her team have made a great effort to help us to reach out to hiring managers and arrange internal referrals. However, unlike most of my fellows in the cohort, I have a pure business background (bachelor in accounting & master in analytics). Therefore even though I have been studying DS and programming through online courses for about one and half years before joining this bootcamp, I still ended up taking a Data Analyst position instead of continuing my job hunting for the Data Scientist jobs.

At the end of the day, the cold fact is that most of the "real" data scientist positions require years of academic training and domain knowledge. The skills you have learned here at NYCDSA is definitely enough to grant you for an entry-level analytics position. However, if your target is the sexy DS title with six-digit salary, then unless you have a STEM Ph.D. or advanced degree in Computer Science / Statistics, this bootcamp will just be the start of a long journey.

I completed the Data Science bootcamp during the Spring of 2016. I enjoyed the Data Science bootcamp very much. It was a great experience overall.

My background is PH.D in Physics and I has more than ten years research experience as research scientist.  I am probably the most senior person in the class.

The course is very intensive and comprehensive. It covers most machine learning(ML) and data science skills:   ML in R and Python, website scraping, data visualization, big data with Spark and AWS. It is great to learn ML with both R and Python there. As I know, most boot camps don’t offer R. The school teaches a lot of stuff. It can be little overwhelming at the beginning. Everything I learned there is useful and helpful in my work. Just mention a few small things: Git, Mongodb, web scraping, AWS. I used all these skills in my work from day one.

There are enough TAs there and they are consistently available to offer help on homework, projects and software. I used windows system, the installation of some software is not straight forward.  Their great supports saved me lot of time in that way, and I can have focused on my projects and homework.

The instructors there are excellent too. They come from different background: statics, physics, and EE. Since the students come from different background, it is challenge for the lectures to deliver complicated pictures in clear way for most students.  They can present the material in a clear and logical sequence, explain complicated things in a simple way. I believed they did great job.

NYC Data Science Academy have a lot connection from local companies and this can add great values for the job seeking. I live in west coast and still got continuous supports. I worked at a start-up right after the bootcamp and then went to another  larger company a few months later.

Data Science is largely different from other science. It requires many skill sets and focuses on application much more than pure science. NYC Data Science Academy offer great opportunities for people who are seeking new career in data science in a quick way :  learn the fundamental skills of data scientist in the real world in 12 weeks.  I fell fully supported and encouraged from day one to the final job hunting.  

I have a Ph.D. in computer science, and I worked in tech industry for nearly two years. One thing I learned was that, great companies come and go, rise and fall, shine and fade. History repeats itself. However, no one can and shall beat the trend, since nothing is immortal. 

With a strong belief that machine learning is the key to the ultimate Artificial General Intelligence (AGI), I decided to embrace emerging trend and immerse myself in the field of data science, the field in which a critical piece is machine learning. In joining the NYC Data Science Academy, my motivation was simple: refresh my eyesight, build the intuitions, solidify my understanding, and meet with talented people.

It was a fantastic and rewarding journey with my fellow data scientists at the bootcamp. I will mainly concentrate on three aspects here: the curriculum, the instructors, and the like-minded peers. By no means they are complete, but hopefully they are useful for some people.

Firstly, the curriculum is comprehensive and well-tailored to balance both the breadth and depth of the data science field. Although each year there are perhaps hundreds of new machine learning algorithms devised in academic world, the essential ones are no more than ten and still widely applied in industry (see here for full list: http://www.datasciencecentral.com/profiles/blogs/top-10-machine-learning-algorithms). Almost all of them, including their nuances, nuts and bolts, pros and cons, were covered in the curriculum and explained well by instructors who really know them.

Secondly, the team is very efficient and professional. The instructors are technically proficient, articulate, and beyond my expectations. The lecture materials were self-contained, and covered related points that a data scientist should know. Especially, I was truly impressed by Luke’s passion in preparing useful materials and zestfully articulating his topics (such as sklearn framework, pandas, EM algorithms, or math, etc), by Zheyu’s professionalism and dedication in helping cohort to fix head-scratching problems and made their life easier, and by Shu’s enthusiasm in designing high-quality materials (sorting, hadoop, spark, etc) to broaden cohort’s skills. Besides, statistics was once a somewhat mysterious subject in my knowledge sphere. For a long time, I wanted to step my feet into its door to systematically cover it but I never managed to. I believe that if people want to explain something very easily without pain, they have to understand it deeply from beneath the bottom. It was Chris who unfolded the foundations of statistics and distilled many useful gists in my head within very short period of timespan. And he truly knew his subject inside out. I gained the gists, built the statistical intuition, and I am now more comfortable than ever before on this subject. 

Thirdly, most importantly to me, the feeling of spending three months with a group of talented people is simply awesome. There is a saying that, “if you are in a room and you are the smartest one, then you are in the wrong room” (https://www.quora.com/Who-can-this-quote-be-attributed-to-If-youre-the-smartest-person-in-the-room-youre-in-the-wrong-room). There were many smart people in that cohort so I was sure I was in the right room. I felt that sharing the joy of enlightenment (when somebody/team achieved high scores in Kaggle leaderboard) or sadness of frustration (when somebody’s code did not work no matter what) with other talented minds was unique and unforgettable experience. Besides, through brainstorming with like-minded, new insights were sparked and new ideas were transferred. Eventually those ideas were distilled into my projects and morphed into my sixth sense of mental muscles. I felt that I was fortunate to be amongst a group of great fellows: there was no bullshitting, no day dreaming, and people were nice and nobody wanted to waste time. They all knew what they were after and worked extremely hard. I am sure I will miss them from time to time.

I would highly recommend the NYC Data Science Academy bootcamp. I have been an IT Executive for many years and wanted to supplant and round out my experience with skills in data science and machine learning, as it is my belief that these are one of the most critical technologies of our times. While I did try lot of the online courses, the academy brought a more organized, regimented, and immersive track that allowed me to not only learn and absorb the materials quickly, but also engage in real world projects and applications that would elegantly blend theory and practice.

The quality of both the instructors and course materials is high. It has been an amazing learning experience for me and definitely worth the investment that helped me get to my next stage of career growth. Regardless if you are trying to supplant your post-graduate degree, thinking of doing a career switch to data science, or wanting to supplant your skills, the bootcamp offers that opportunity to push yourself to reach your maximum potential.

That said, this bootcamp requires that you bring your A-game into the arena. This is not an easy course to take, and for good reasons. The bootcamp will stretch you to surpass what you think your limitations are and push you to be at your best at all times. This requires 100% commitment from your part. Anything less will not be good enough. If you fully commit yourself, you will emerge from this course with a renewed sense of passion in this exciting field. If there is one regret, it would be that I should have done this bootcamp sooner.

The job opportunities for data science and machine learning specialists are just amazing. Since getting the certification (even before then), the contacts and network I have made in the data science community have accelerated at a rapid pace. The reachout from recruiters have also increased significantly. The demand for data scientists continues to climb. In hindsight, it was a great decision for me to have made the jump to go through the bootcamp, as I am now working on numeorus opportunities that allow me be more creative and innovative.

The academy is managed and run by an amazing team of people who have helped me through the many months of learning and growth. They have been such a strong support system for me as I take the next journey through my career as a Data Scientist. The academy has also opened my eyes to so many wonderful experiences and allowed me to validate the opportunities and potential of this exciting field I am in. I have learned so much and the real skills I have acquired will be of tremendous value as I embark on pursuing my passions.

As the saying goes... "Never give up on a dream just because of the time it will take to accomplish it. The time will pass anyway." I pursued mine and living it, now it's up to you to pursue yours.

The bootcamp provides an extensive overview of the most used Machine Learning algorithms in addition to RShiny, visualization and webscrapping (using Python). Like any classes in college and graduate school, instructors are there to walk you through the basics and it really is up to you on how much effort you would like to put in. However,  the TAs and instructors are far more accessible than any class I've taken so far!!! Ode to the TAs! In addition, the fellow students at NYCDSA are really nice people in general. And knowing that you are not alone really helps during those late nights at the bootcamp!

I would recommend the bootcamp to anyone in need of a career transition into Data Science, willing to go above and beyond, and are comfortable with either statistics or basic programming. 

I was an experienced academic professional with one-year experience in the oil-gas industry. After I joined the oil industry with a big oil company, the oil price started to go down till now. This caught me out of guard.  As I expected, I was laid off  at the end of 2015 .

By checking with other programs, I realize NYC DATA SCIENCE ACADEMY will provide the necessary tools and the big pictures about the emergent field of data science.

The instructors and TAs from the school are from diverse backgrounds including statisticians, physicists, mathematicians, and computer scientists. They make Ph.D. students feel comfortable to ask more technical and fundamental questions without feeling being discouraged.   They also let you be responsible for choosing your own projects to enhance your practice in data science in general. If you are a person who is very solid in any programming languages in the past, this is the place for you to learn the fundamentals of machine learning and statistics. In the end, you can put these skills together to be confident to attack data science problems in general. You will have a very strong foundation to jumpstart your new career in data science.

The program is very intense and I was constantly trying to catch up with the learning, homework, and projects. There is no time to think about negatives. This was also good once you find a new job you can handle the pace from the new job better. I strongly recommend particularly the students with excellent postdoctoral experience to make a career transition to join this program. Consider this as an investment for your career. (The tuition potentially can be offset by signing bonus from your future employers).  

I had great experience with this bootcamp. Intense program, nice course contents.  Comprehensive training on coding,machine learning, presentation and writing. I had five projects done and blog/github posting. The package drove to  interview opportunities.  During and after the program, I still keep having help on polishing resume, mocking interview, and receiving job opportunites. Finally, I accepted data analyst postion near my home in Portland. 

I completed the Data Science bootcamp during the Fall of 2015 and immediately was hired as a Data Scientist the following January.  During the NYCDSA bootcamp, I converted my skill set from a traditional statistician/analyst to a data scientist.  This bootcamp elevated my ability to apply a variety of advanced machine learning algorithms using codes like Python or R.  Today, I continue to use the skills that I had developed during this bootcamp.  In my opinion, this bootcamp was successful for me for three reasons:

Course Content:  

The course content covered coding in SQL, python and R during my time at the bootcamp.  As a data scientist, ability to code in this basic languages is critical to developing and testing statistical hypotheses and machine learning concepts.  All machine learning examples had supporting Python and R code to facilitate students' application of these algorithms.  This bootcamp covered application of Spark during the last few weeks of the course.  Knowing Spark capabilities was particularly helpful in my current position as a data scientist.

The bootcamp covered traditional statistical concepts such as hypothesis testing, linear regression and logistic regression as well as advanced machine learning algorithms such as K-Means clustering and Neural Networks.  The bootcamp strategically provided theoretically background for these concepts in conjunction with worked out examples in R and Python.  Knowing how to apply all of these algorithms helps me to rapidly move through proof-of-concepts in my current day-to-day.

Instructors:  

During my cohort, the bootcamp instructors were incredibly dedicated to helping the students succeed.  Instructors were consistently available to answer coding questions on-site in person or off site via slack or email.  I was always satisfied that the instructors were able to answer my coding and ML questions rapidly and completely.

Job Search:  

The bootcamp helped me find several job interviews towards the end of the bootcamp.  It was  clear that the NYCDSA had access to an increasing network of employers looking to hire data scientists.  During the interview process, I had felt that the bootcamp prepared me to answer all of the data science interview questions during each interview.

It has been over a year since I first enrolled in the NYCDSA bootcamp and I continue experience the benefits of the bootcamp in my day-to-day job as a data scientist.  I strongly recommend this bootcamp to anyone looking to make a career transition into the data science field.

The 12 week bootcamp at NYC Data Science Academy combines everything a budding data scientist needs while finding a balance between depth and bredth.  Coming from a background in strategy consulting I appreciated the intense nature of the schedule with tight turnarounds and explicit deadlines for coursework and project submission.  You'll be given the chance not only to learn from some of the best instructors with phenomenal backgrounds and real world experience, but also to showcase your own skills and ideas through 5 data science projects where you get to form hypotheses on data sets of interest to you and make meaningful conclusions.

Though the pace is relentless, the program is very managable given the dedication of the instructors to see you succeed.  You'll form great relationships not only with the staff but with other gifted students as well as you all learn together about this exciting field.

The NYC Data Science Academy provided an unparalleled experience - from the high quality of the instruction material to the dedicated teachers and staff, I gained both a strong personal and professional network and a greater exposure to the world of data science. The return on my investment was substantial, as I've successfully received five competitive job offers in a variety of industries (1 in finance, 2 in marketing, 2 in health) within just a few months of graduating. 

Most importantly, learning in the immersive environment quickly accelerated my technical know-how. I became adept at R, Python in addition to structured thinking, open-ended problem solving, and communicating my ideas and work across to a wider audience. 

Additionally, preparing for the five project presentations and homework assignments with like-minded peers in my cohort also positively influenced my experience. Sharing ideas, knowledge and experiences with my classmates, and TAs - encouraged me to creatively explore every approach when faced with a challenging problem or in-class lab. 

I am grateful for my time at the NYC Data Science Academy. I highly recommend enrolling if you're undecided - it's an awesome place to prepare for a new career in data science and machine learning.

I am writing to strongly recommend NYC Data Science Academy to anyone who is looking for opportunities as a data scientist. As a recent graduate student of the 6th data science bootcamp of NYC Data science Academy, I was immediately able to find an internship in an hedge fund as a quantitative trading analyst 2 weeks after I graduate from the bootcamp and currently actively seeking full time job under the guidance of Vivian, the founder of NYC Data Science Academy. Before attending the bootcamp, I graduated from Courant Institute of Mathematical Sciences, New York University with a master of science degree in Applied Math. I have always been in love with math and attracted by the beauty of proofs and theorems. However, I did not know how to make a use of my quantitative background into real life. By an occasional chance, NYC Data Science Academy came to my attention. I found out that they offer a highly immersive Data Science program involving data strategy and hands on expertise on machine learning, big data, advanced statistics and analytics. Students are able to solid R and Python development skills, various model ensembiling and stacking strategies and gain knowledge including but not limited to Unix, SQL, Hadoop, Spark etc. Soon after I contacted the academy, I got an chance to talk with Vivian and immediately feel that it is the right place for me. My intuition proved to be right after I attended the bootcamp because I not only strengthened my knowledge and learnt tons of new skills but also get to know many talented people from various background and developed strong network connection with them. The training contents are well-designed and students are required to complete 5 projects in the progress which comprehensively exhibits one's skills from visualization, web interactive app to machine learning and big data. To better assist the students with their job hunting process, the instructors and staffs in the NYC Data Science Academy worked very hard to organize a fantastic career fair and invited more than 30 companies and recruiters including JP Morgan, BAM, Google, FaceBook and Spotify. Students were able to show their accomplishment to the data scientists in the company directly and make connection with them. It was such a wonderful and unforgettable journey with my fellow data scientists. 

The decision to enroll in this Bootcamp was one of the best decisions I’ve ever made. I had high expectations coming in to the program, mostly due to the reviews I’ve read, yet the 12 weeks I spent at the academy exceeded those expectations. The coursework is difficult enough to challenge those with a PhD, while the instructor’s and TA’s help out to the extent that even those with a Bachelor’s will find it manageable.

The program covers a wide array of topics, combining theory and application to give you a well rounded understanding of the material. Students are encourage to learn by doing, and home-works are given out 2-3  times a week, with deadlines not always easy to meet. But given how much the instructors offer to help, students usually always find a way.

The whole team goes above and beyond to help out not only with teaching you data science, but also with things like interview readiness, job-placement, and helping you build a great portfolio.

You are surrounded with like-minded people for 12 weeks, forming great friendships learning from each other. You are tutored and lectured by industry professionals who go out of their way to make sure you understand the material. You are exposed to cutting edge softwares, advanced machine learning algorithms, and industry best practices. You are helped with building a portfolio, creating a great resume and how to pitch your work to employers.

I’m truly happy I did this program, and so will you.

I moved to United State in October 2015. I wanted to do a career transition and applied to NYC Data Science Academy 12-week Full-Time Data Science program after some searching over the web.

I come from a Mechatronics Engineering background, with 2+ years as a Business and Sales Consultant and an MBA in general business management. At the beginning I was a little bit afraid about the programming side because the only programming experience I had is a course in my Bachelor's about C++ and two simple projects throughout that course. Also mathematically speaking during my bachelor's I only took linear algebra and differential equations, not that much statistics and programming before entering the bootcamp.

The curriculum was mostly includes programming with SQL, R and Python and also learning to implement machine learning algorithms in R and Python. It is structured so well that eventhough you have a little experience with programming before, they start teaching it from basic level and build up nicely so that you do not get lost. 

The instructors are incredibly helpful during your learning process, homeworks and projects. The lectures are fun with modern learning tools.

They are known well in the industry. So when you apply to jobs the people will know the quality of NYC Data Science Academy and it will not be difficult for you to get interviews. They will also make it easier for you to meet with many hiring partners. 

My overall experience with NYC Data Science Academy was wonderful and I can easily say that it was the best investment that I did for myself. 

The most important thing to consider before applying is you should be ready to invest an intense 3-months. And also you should be ready to work hard as a student again.

If you are thinking about enhancing your career to a new level and enter to the fantastic world of Data Science, I strongly recommend NYC Data Science Academy.

I was coming from a Computer Sicience background. And I decided to make a career switch to Data Science. One of my data scientist friends recommended me to take the NYC Data Science Academy's 12 weeks Data Science Bootcamp. It turns out to be money worthy. 

The bootcamp covers all the skills that I need to know to be a successful Data Scientist. It provides training on: programming skills (in both R and Python), basic Linux/Unix commands, basic database SQL programming, exploratory data analysis & data visualizationn (in both R and Python), Machine Learning in both R and Python, and basic Hadoop and Spark skills. Some people might wonder why both R and Python were taught. From my experience, R is really helpful and handy when doing the EDA and visualiztion at the beginning. Python is more useful when building production pipeline models. Also Jupyter Notebook (orignially called iPython Notebook) makes sharing the code and charts easier. So I feel it was right that they taught both R and Python.

The program was very intensive. There was so much information thrown into my brain every day so thus I had to study and reivew the course material every night late in order to digest them. We were assigned homework every other day and projects every 2 weeks. There were about 5-6 projects through the course of the bootcamp. Each project had a different focus. While the earlier projects focused on Exploratory Data  Analysis, the later ones were more Machine Learning focused. I found myself was always rushing to wrap up the projects because I always had diffcult time to come up with an idea or started it late. Lesson learned!

During the bootcamp, because I was from computer science backgroud, I was quite relaxed on the programming parts. But I definitely struggled a little bit on the Machine Learning part since it invovled advanced Math and statistics. So I had to go back and review some of the Math material and took some online training on statistics. Therefor it would be great advantage for people with statistics backgroud. If one without statistics background is trying to take the bootcamp, I would suggest that you study some statistics material from online before the bootcamp so that you can really understand the theory behind. 

I also want to give credits to the awesome instructors. Special thanks to Sam, Chris, and Luke who did a great job on teaching the class and answered all my questions. There were also two TAs who has provided big help on homeworks and projects.

Quick notes on job assitance, NYC Data Science Academy has connections with hiring partners. Therefore we got many job opportunities directly from the hring partners, such as Goldman Sachs, Chase, NBL, Booz Allen Hamilton. There was a time that the former job placement manager was slacked. But it was quickly fixed and the job placement manager was replaced and things were back on track again. We were also provided training on preparing interviews and sharping up my resume. Even though I got a job from an opportunity I found from LinkedIn, but the job assistance from the Academy was definitely helpful.  

To sum it up, I have learned a lot from the bootcamp and I also spent a lot time to digest them after I finished the bootcamp.

The only two things I suggest are: 

Because EDA and Data Visualization are so import, it would be great to have a example on those that we could have walked through or done together. Or for at least one of the EDA and Data Visualization projects, we work on the same topic and review it together. 
More hands-on Spark excise. I would suggest using of Databrick community version or student excise.

The NYC Data Science Academy bootcamp is everything I hoped it would be. I entered as a recent Mathematics PhD unsure of my job prospects and left well prepared for the data science job market. I was offered a job within weeks of graduating and now have a great job as a data scientist.

The bootcamp is an intense experience that will reward you if you put in the appropriate effort. The lectures are fantastic and the instructors are incredibly helpful with your projects. They will offer you as much help and guidance as you want (they were, more often than not, there before me and were still there when I left). 

Job placement assistance was also crucial to my success. I met my current employer through a bootcamp and felt more then prepared during my interviews. You really feel that you are given individual attention and they will do everything in their power to help you find a job.

Some tips to prospective students:

Become familiar with the basics of R and Python (especially Python as this is introduced later in the bootcamp when you are becoming busy).  I didn't enter the bootcamp as a programming expert but I found having some knowledge was a large advantage. A few months of learning the basic syntax and doing exercises in your spare time should be sufficient (that is approximately what I did).
Enter if you are willing to commit 3+ months to your career (you will be studying and preparing for interviews after you finish the bootcamp).

NYC Data Science Academy was a fantastic introduction to the world of data science. I still stop by the offices to say hi to instructors and students and discuss life. I would make the decision to join the bootcamp again 10/10 times. 

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 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:

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.
With whatever time you have before the bootcamp, you will study statistics, R, and Python.
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.