Student Testimonials

Mayank Shah
Mayank Shah

-Live-

This course was the best thing to ever happen to me. In 20 weeks (4: pre work, 12: course, 4 job hunt) I went from someone who couldn't write 'Hello World' in python to a full blown Data Scientist, making six figures, with multiple companies vying for my interest.

What you should know:

You will get as much out of this course as you put in. I had many, many days where I was working well past midnight and back in class by 9:30am. You learn how to learn, which is THE skill required for any coding job. The curriculum is intensive, and a lot of times I couldn't totally complete the homework without checking for answers from my peers, and that's okay! In the real world, much of your job will be interacting and working with a team.

Course: Go every day, work hard, finish the projects on time, and hold yourself accountable. The lecturers do a great job, but ultimately when you're 24+ years old, nobody is going to spoon feed you. The homework is great, but when you try to put everything you've learned together into a well rounded project (there are 4-5 projects), that is when you really understand what is going on. Throw yourself full bore into the projects, and take pride in your work. 90% of what I learned, no exaggeration, was in the 3-5 days before projects were due. Its one thing to figure out homework by looking at the example sets, and a different thing entirely to apply those concepts to a data set with different structure and goals. If you are proud of your projects at the end, you will get a job. Period.

Job Hunt:

The job is the ultimate goal for 99% of people entering the camp. Unfortunately, there is some confusion about how the search will work. For one, you will not be "given" a job. For most people, the job search will take 1.5-3 months. Vivian has excellent contacts but she also has 40+ students. In order to guarantee yourself a job, you need to approach the process like a data science project. For me, I did "easy apply"s on LinkedIn, 50 a day. These take literally 15 seconds each. I then selected 15 companies a day with a more formal interview process, and sent them a variation of a pre-written cover letter. For my top picks, I tried to find a hiring manager or data scientist on the team, and add them on LinkedIn. I put my name on AngelList, and got many companies reaching out. I humbled myself and told everyone I was more interested in a great learning position, not a great salary. I iteratively changed my own interview methods, including voice tone, inflections, negotiations, honesty levels, until I found a balance that worked for me. You cannot just apply and hope. That is not a method.

Basically, the bootcamp is the first big step. The second big step is learning how to apply and interview. Many people send out 5-10 applications to their top picks (who are often everyone else's top picks as well) and then sit on their hands and wonder why they haven't gotten a job. When entering a new field, you have to make concessions about your salary and place of work, in order to reap the rewards down the line. Also, without multiple options, you will not be able to negotiate because you'll feel this is your only chance. BROADEN YOUR HORIZONS!

Overall:

The camp was the best decision I ever made. I read a book called Design Your Life, which basically said take how you want your life to be, then decide what is necessary to get it there.

I wanted to live in NYC, with a six figure job, working in an office with low stress, and love what I do. NYCDSA made all of that possible. If you have gotten a degree that isn't taking you where you want to be, but you know you're smart and can work hard, I strongly urge you to apply to NYCDSA today.

Kyle Gallatin
Kyle Gallatin

Honestly one of the best decisions I’ve ever made. Yes it’s a reasonably difficult course, but if you are truly interested in data science you enjoy every second of it. Like anything, you get out what you put in. If you’re ready to work as hard as you need to in order to master this wealth of knowledge in 12 weeks, this course is 100% for you.

The instructors and TAs are excellent, all accomplished data scientists with a wealth of skill and knowledge. The resources, from slides to code examples and practice questions, are things I will continue to use throughout my career as a data scientist. There is ALWAYS more to learn in the field of data science.

If you’re thinking about going because you simply want a pay raise, then don’t. The course is relatively difficult, and if you aren’t willing to put in the work to master everything you need to land a job, then you won’t get a job. Simple as that.

However, if you are committed to becoming an expert data science, the job support here is immense. There are mock interviews, code interview practice questions, linkedin workshops, presentations from hiring companies and data scientists etc…I myself recently accepted a dream offer from a company I was connected with through the bootcamp.

You likely won’t get a job immediately, it’ll take awhile and a lot of interview practice. It took me about 3 months. If you haven’t mastered the skills you need to be a data scientist, then you don’t have the skills to pass through the interview process. But again, if you are committed there is no shortage of resources made available to you. If you do not succeed here, it is because you did not put as much effort into them as they did into you.

Finally, an underrated part of the experience is the other students. Some of my best friends in the city I met through the bootcamp, and we still go out for drinks all the time. The course not only provides you with knowledge, but connections. It’s a room full of intelligent, driven and entrepreneurial people. You could expect nothing less.

If you want to be a data scientist, and more importantly you have the drive to learn and succeed, you’ll thrive here. Simple as that.

Carlos Salas
Carlos Salas
I was enrolled in the NYC Data Science Academy full-time bootcamp during 1Q17. I found it a very good programme to enhance my computer science skills, particularly in the fields of EDA (exploratory data analysis), machine learning and web scrapping. In my case it was a very good way to upgrade my skill set and enhance my professional profile (originally finance field). Positives: - The program materials are very good (theory and exercises) allowing to properly study the syllabus and find the right balance between theory and practice. - The school staff is very close and dedicated to the cohort and always looking for feedback to improve the experience. - I am more a "lone wolf" type of person but I found useful to be forced to cooperate in one project with other team mates as it allows to have a experience close to what a real job in Data science will be. Things to bear in mind: - You need to have at least a good basic-to-intermediate level in coding. If you never have coded, you better spend 3-6 months preparing yourself using Python and R beginner courses since the programme can be an uphill struggle for those who lack of minimum programming skills. - This bootcamp is very focused on EDA (Exploratory Data Analysis) and Machine Learning. Although big data software like Hadoop or Spark is in the syllabus, it's basically an introduction since the program lasts only 3 months. If you are looking for a pure Big Data experience, this is not your program although it offers a good intro. - This is a non-stop bootcamp so prepare yourself to be fully-committed during the 3 months as you will have to attend lectures in the morning and deliver homework almost on a daily basis. Overall, I enjoyed my time at NYCDSA and think is probably the best bootcamp for professionals looking to upgrade and enhance their computer science skills specializing in Data Science.
 
Yvonne Lau
Yvonne Lau

Rochetmiles

Overall: 

100% YES!!! I wholeheartedly recommend NYC Data Science Academy! If you want to switch into data science, the bootcamp will help you land your dream job. I got an internship offer shortly after the end of bootcamp(~2.5 weeks) through the bootcamp’s hiring partner event, and recently became a full-time data scientist at the same company. All of this would not have been possible without the help of NYCDSA!

Full Review

When I was reading through bootcamp reviews, I personally thought it was more helpful to find people of similar background as mine and see how well they fared.  For instance, knowing that people with only bachelors degree attended NYCDSA and got data scientist jobs helped to not only inspire me, but also to set realistic expectations on what type of jobs I could get and how long it could take. So here is a blurb about myself:

TL-DR;

  • Bachelors degree In math and economics
  • <1 yr of work experience
  • Limited exposure to R/SQL/Big Data tools prior to the bootcamp(Does using a select statement in SQL count?)
  • Prior experience coding in C and basic Python through an intro level computer science course in college. No exposure to data packages in Python.

Prior to coming into the bootcamp, I asked myself: “Is the bootcamp worth the $16,000 investment?” Is it going to give me enough skills to find a job as a data scientist?”. If you read my introduction, the ultimate answer is an obvious YES! Below, I am listing the top 7 reasons why I think NYDSCA was a worth investment for me:

  1. Top-notch job assistance:  From teaching how to craft your resume to preparing for technical interviews, Vivian and Chris did an excellent job at explaining what interviewing for data scientist positions was like. This “soft skill” portion was really important for me since I wasn’t accustomed to interviewing for technical roles. Thank you Vivian for always pushing me to become a better data scientist! Thank you Chris for all the earnest advices on job hunting!
  2. Connections of the bootcamp: As I mentioned earlier, I got my job through the bootcamp’s hiring partner event. Being able to take advantage of the wide network of employers definitely made “getting the foot in the door” much easier
  3. Learning both R and Python: I wanted to learn both as I knew it would help me cover my bases and be prepared for most data science-related jobs.
  4. Transforming me into a confident coder: having learned coding through a class in college and a bit of self-learning, I knew I needed to improve my skills if I ever wanted to land a serious job as a data scientist. The pre-work material along with projects were really helpful in that sense
  5. Structured curriculum: There is a lot of thought put into the structure of each class. It was very nice to have all materials that I needed to learn organized for me so that my only worry was to learn.
  6. Instructors: They deserve their own section as most staff have been teaching for quite a few cohorts. They are all very knowledgeable and approachable. Special shoutout to Zeyu for being an amazing TA and always offering helpful guidance through my projects!
  7. Projects: Each project covers an essential area of data science-data visualization, web scraping, machine learning - and I learned so much through them. The projects were also essential to build my data science portfolio and showcase my skillset to employers.

If you made it all the way to the end, thank you reading this review! All in all, NYCDSA was great!! It worked perfectly for me as it gave me the skills (both technical and soft) I needed to land a data scientist job.  BE PREPARED TO WORK HARD. Treat both the bootcamp and job hunting as a full-time job and you will be rewarded. :)

Rahul Bhat
Rahul Bhat
Took the weekend course for Machine Learning with R. Course was very helpful in helping me understand the basics of Machine Learning, different models. My instructor was Luke. He was very helpful and would spend enough time covering each topic. He even took an additional class because he didn't want to rush through the material. Overall I am quite satisfied with the results. Would recommend Luke to anyone else who is interested to venture into Machine Learning field.
Lukasz
Lukasz
I studied mechanical engineering and physics for my undergrad at a top university and work in product management with a focus on search. I took this class to satisfy a personal interest in the subject matter and familiarize myself enough with the fundamentals of machine learning to be able to explore the field more deeply on my own. I was also motivated by a career interest: the subject matter is highly relevant to my domain, and I feel that developing an understanding of the concepts and how to deploy them myself will make me better at my job long-term. Prior to enrolling in the class, I spent roughly 8-10 hours learning R and felt sufficiently prepared (I had some previous programming experience). In the end I was extremely happy with this class (Machine Learning in R on Saturdays, 8 hrs at a time). The curriculum and content were excellent, the instructor, Luke, was fantastic and the assignments were challenging and informative. I felt the course did a really great job of driving home the core fundamentals of each subject with a focus on statistics, mathematical theory, derivations and best practices. We covered a LOT of material, yet the material had a lot of depth. I thought the sequencing of the subject matter was very well thought out as well. The class was demanding and had the caliber of a graduate-level course. The course also struck a very nice balance between theory and implementation. After learning about a new model, we would immediately implement it in class using R on our own machines. Luke did a particularly great job at relating the implementation back to the concepts and teaching us how to interpret outcomes of our analyses (I can’t stress enough how important this latter point was for me). He has a really strong grasp of the subject matter, he’s very patient and responsive to questions, offers a lot of insightful commentary on the theory, implementations, and best practices, and he cares about his students a lot. The homework assignments complement the class nicely as well, helping to drive home the methods taught in class and how to interpret your work. If you’re interested in developing a strong understanding of the fundamentals of machine learning in a rigorous format, this class is for you. I also couldn’t recommend Luke as an instructor more. He’s awesome! I was also was very pleased with my choice of the R class. R reduces a lot of the friction in model implementation, which allowed me to focus on developing an understanding of the concepts and interpreting results.
Spencer Stebbins
Spencer Stebbins

Data Scientist
CKM Advisors
Preface:
I attended the July cohort and was then a Data Science in Residence at the NYCDSA prior to accepting an offer for a Data Scientist role at a consulting firm based in NYC. I will do my best in this review to be as straightforward about my experience and address a lot of questions I had prior to the program and have understood a lot of incoming students to have had through prepping them for the program.
My Overall Opinion:
Lets start with this: get over your hesitation, take a leap of faith, and you surely will not regret your decision to attend the NYC Data Science Academy 12 Week Bootcamp. Whatever reservations you have, you are not alone; almost all graduates have felt that prior to attending the program. You may be wondering about if this program will really teach me the necessary skills to get a job, am I prepared enough for this, will the program be rigorous enough, and most pivotally; is this the right decision for me? I cannot speak for you, but I can attest to my own experience and I graduated this program with no regrets, soak in a waterfall of new knowledge and skills, and have walked away a smarter, more capable, more confident professional now employed Data Scientist in field. The program is amazing, and the instructors are passionate, and you will learn a lot, but that also being said, you get as much as you put in and the first step is trusting in yourself to join and commit to the three rigorous and insightful months ahead of you.
My Background:
Prior to attending NYCDSA, I was a software engineer at a large shipping company for almost 2 years focusing primarily on front end development. Before that I attending another bootcamp called Hack Reactor, similar to NYCDSA, to study software engineering and javascript. It was growing interest in machine learning, the success of my experience at Hack Reactor and the thirst for that similar immersive and intensive program that led to me to the NYC Data Science Academy. In another life, I graduated from NYU with a degree in Music Business.
Common Questions:
Do you need a masters or a background in a quantitative field?
The answer is no. No, you do not need a masters degree or professional experience in a quantitative field. During my cohort, I thought some of the best and most creative presentations and chosen topics by students were from some that had no prior coding or heavy math experience. That being said, coming in with a math or software engineering background will definitely allow you to vamp up your projects flashiness and you may have an easier time understanding some of the formulas associated with the advanced machine learning algorithms.
Will I get a job from this program? What are the job stats? etc..
Although I can't attest to job stats, I received my first offer less than 6 weeks after the program ended. I met the firm at the Career Day at the end of the program. Vivian, the CEO of NYCDSA, is the job placement tsar and wizard and without her and her relationships with so many great firms there would not be as many companies at the career day as there are: Spotify, JP Morgan Chase, MindShare, etc.. Vivian will do every in her power to connect you with your dream job. That being said, getting an offer is entirely on you. You must have great visual and complex projects, you must interview well, and you must be actively job seeking and cultivating relationships on your own. Vivian and the team will do everything they can to prepare you and connect you with your dream job, but you need to show up with the bus fair to ride the bus. I cannot stress this enough.
How does this compare to other bootcamps?
I am actually in a unique position to answer this question. A few years prior to graduating NYCDSA, I graduated Hack Reactor, which is a similar 12 week bootcamp, but for software engineering. Prior to that I took web development course at General Assembly, Coursera Machine Learning courses, Harvard Extension School’s Intro to Data Science class to name a few. Needless to say, I’m hungry for knowledge and a challenge. I can’t speak to the other Data Science bootcamps out there like Metis or Galvanize, but I can say that there is nothing like 3 months of learning something at a such a rapid pace. The sum of its parts is greater than the whole and you can spend years learning on your own secondary to whatever else you are doing or you can jump in the deep end. I did before with Hack Reactor and walked away amazed and the same held true for NYCDSA.
Inside Tips:
Pick good project topics. Your projects will be portfolio to potential employers and if your project outshines the other students, employers will take notice.
Pick good project team mates. I didn't have a poor experience with anyone I worked with, but it goes without saying that if you pick bright, easy to work with project partners, you'll be able to build a better end product.
If you don’t know how to code in R or Python and have no prior experience code - Learn now. Codeschool.com is an excellent introductory resource.
DO NOT think you will have a social life. This is only 3 months of your life, but 3 very important months, so give it your all and don't expect to get as much out of it if you don't.
Comments to the Academy:
Scaling the program will require more job assistance personnel.
Increasing the amount of coding done in the program may be beneficial as most jobs now require coding every day and are rarely purely theoretically
Additional content on computer vision would be fun
More TAs and one on one knowledge quizzes (like done as a group at the end of the course)
Lydia Kan
Lydia Kan

Data Scientist
Publicis
Overall:
I will recommend this bootcamp to anyone who is eager to learn and have great passion towards data science. Before I attended the bootcamp, I received my master degree in marketing from school. I did not have a lot of math and coding background back then. With my passion towards data science, I decided to take a deep dive and applied for the NYCDSA’s 12 weeks bootcamp. Due to my limited coding background, they did not accept me at the beginning, instead, they provided one month prep course for me to get prepared for the bootcamp. I attended the September cohort after the prep course. It was one of the best decisions I have ever made. With the extensive knowledge and training, and great support in job assistance, I am able to land my dream job in 2 months after bootcamp.
Curriculum:
The curriculum is very well designed. I did a lot of research before I applied for this bootcamp. NYCDSA is the only program that covered data science in both R and python, big data processing tools such as Hadoop, Spark at once. I am really glad that I started my journey in data science with them, so my foundation in data science is much stronger now than I was when taking online classes by myself before. The curriculum will also help you to develop a portfolio for job hunting, however, you are the one who decides how much effort you want to put in and how far you want to go.
Instructors:
The instructors and TAs are the best part of the bootcamp. You will never receive this kind of learning experience through online courses. They are all very knowledgeable in computer science, statistics, and machine learning. They are so passionate, and so willing to help each student. There were so many times that they stayed after 7pm, came in during weekends, answered slacks questions at 11pm to provide extra helps. They are far more than just instructors and TAs, but also supportive friends after I finished the program.
Job assistance:
I got hired by a major ad agency as a data scientist within two months of completing the bootcamp.
The hiring team put the best effort to help their students. They hosted awesome hiring partners event, which the students got to make connections and talk to some great companies, such as IBM, citi bank, Mindshare, Publicis and so on. During my job hunting process, Vivian tried her best to provide any connections with the companies that I really wanted to get in. I also received a lot of helps and mentorship from Chris. The way he helped me to prepare for net-working and interviews are very strategic, systematic, and effective. I learned so much and I won’t get this far without him. You can learn all the hard skills anywhere else, but this kind of support and mentorship is hard to find even if you have a lot of money.
They provide as many helps as they can, but you have to be proactive and eager to learn to take everything in!
David Steinmetz
David Steinmetz

Machine Learning Data Engineer
Capital One
Attending the NYC Data Science Academy 12-week Data Science Bootcamp was one of the best decisions I have made. It was instructive and rewarding. It provided a speedy career transition and enabled me to get a job within two months of graduation as a Machine Learning Data Engineer at Capital One. I will summarize my background and describe my experience at the bootcamp and why I recommend it highly.
I have a PhD in materials science, which is a blend of math, chemistry and physics. I had programmed models and simulations in Matlab, but have no formal computer science education. I switched to management consulting after the PhD to apply my analytical skills in the business world and quickly realized there is a great need for data analysis at companies. After taking the complete Data Science Specialization on Coursera, I knew I wanted to switch to data science and found the NYCDSA bootcamp to be the most comprehensive, teaching R, Python, and Big Data technologies.
I recommend this bootcamp for three reasons: quality of teachers and materials, structure, and networking, both at the bootcamp and in job placement.
It takes a lot of knowledge, experience, and hard work to distill complicated and complex topics and communicate them in a simple and understandable way. The materials presented in this bootcamp were presented that way. When I can understand statistical concepts which I had tried to understand for a long time in a matter of minutes, it means the quality of teaching and materials are excellent. During the job search, I also realized that the correct balance between breadth and depth had been selected to give us a very solid foundation on which to start a job in data science.
The teachers were exceptional. Their passion and dedication to the students were visible from day one. This was shown again and again in how hard they worked to constantly improve and expand lecture materials to how much support they gave to each individual’s success outside of class. Having them as teachers was an honor.
The structure of the bootcamp allowed an incredible amount of materials to be covered in a short amount of time. Particularly, it used both R and Python for statistical concepts and machine learning. In addition, we learned about many other tools in extra sessions designed to round out our knowledge. Big Data technologies such as Hadoop, Hive, and Spark were covered toward the end of the bootcamp. Spark was asked for often in interviews, and familiarity with it was helpful. Having five projects under your belt is exactly what you need when interviewing. I always had an example I could use to answer questions. The value of this is not to be underestimated.
Lastly, the opportunity to network was incredible. You are beginning your data science career having forged strong bonds with 35 other incredibly intelligent and inspiring people who go to work at great companies. The value of those friendships and the ability to create a strong network at the beginning of your data science career will become evident a couple years down the road.
I was fortunate enough to meet and give a presentation to managers at Spotify, at Meetups, and get connected to many hiring partners. Vivian, the founder, is a strong proponent and has an incredible network. She seemed to have a contact at almost every company I wanted to apply to. Her one-on-one evaluation of interview performance with me was very helpful. She and the rest of the staff are very dedicated to each student’s success, being clear in their purpose that this experience will change both you and your family’s lives for the better. Their hearts are in it and their dedication is clear.
If you are considering this bootcamp to get more into data science, it is exactly the accelerator you need to get your career in this field off the ground. I cannot recommend it enough.
Charles Leung
Charles Leung

Associate
Societe Generale Corporate and Investment Banking - SGCIB
I recommend this bootcamp to anyone who wants to transition into the field of Data Science. Before this bootcamp I was a process engineer for a large North American steel company. With the rate of growth in the technology industry, I knew it was time to transition to a new career, and I could have not chosen a better place to do so than NYC Data Science Academy. Instructors: The Instructors were amazing. Chris is extremely knowledgeable in statistics, and his passion for teaching really shines through. With every lecture, he not only shows mastery of the material but also the best way to teach complex materials to a class of non-programmers. Luke goes above and beyond to describe the theory behind the algorithms. His work ethic is shown through the countless hours he has stayed to review lessons with students and believe in continuous improvement. The TAs (Shu, Zeyu) were immense help, and had very good knowledge of big data applications (Hadoop ecosystem, front end work, SQL database design, etc.) Curriculum: The bootcamp offers a good basis for understanding prediction models and when to use which types of algorithms. There just isn't enough time to cover all aspects of statistics and the many branches of prediction models. Both R and Python are taught here, which allows for great flexibility. While this bootcamp is rigorous, self discipline is required to fully delve into algorithms and build impressive products for your portfolio (natural language processing, image recognition, recommendation engines, etc. ; these advanced topics are covered briefly but enough for you to take the reins). All in all I believe the bootcamp set me on the right foot into the industry. Job Assistance: While there is some assistance, the majority of the legwork work is still on the student to be duly diligent - sending out applications, getting interviews, networking and working their way up towards their dream job. There is no easy formula for this, and you MUST continue learning (Algorithms, data architecture, and more advanced ML topics etc. ; network to find out what people in your ideal companies expect you to know) and reviewing material even after the bootcamp to prepare for interviews.
Shuheng Li
Shuheng Li

Data Science Analyst
Aetna
*MY BACKGROUND: I had a Master in Business Analytics before joining NYCDSA, with a knowledge of programming and data science/machine learning. Though I knew how to make graphs and build models with R and Python, and knew some concepts learned from the online course on EDX and Coursera, this bootcamp was still truly helpful for me. My goal was to explore more deeply the big data techniques including Hadoop and Spark and get a chance to review data science and machine learning stuff in a systemic way. This bootcamp gave me almost everything I desired, with so many unexpected benefits. It was seriously life-changing for me. I achieved something that would otherwise never be possible had I just stuck with online courses. Read on for more detail. *COURSES: All the courses were well-designed. They covered everything I needed in my data science journey. Some might wonder why I chose to spend money on this bootcamp to learn something that seems available online. The reason for me was that I feel my time is quite valuable. For me, the efficiency really matters. Rather than spending an hour searching for the right function or parameter and ending up being confused, I wanted to have professionals help me going through the relevant resources systemically. I also found that when confused by problems after the fact, I would open the slides, code, and my repo for that topic instead of having to jump online and wade through Stack Overflow. What’s more, the curriculum covered topics such as Unix, Bash, Git and version control, which seem necessary for a data scientist/programmer but which I never paid attention to when I was teaching myself. *INSTRUCTORS AND TEAM: They are so great. Everyone is kind and willing to help you and share their experience and approach with you. In my humble opinion, there is a huge difference between teaching yourself programming or machine learning and learning with instructors and advice. Especially when you are putting things into practice. I saved tons of time. The NYC Data team is really curious and love to try new techniques with the students. They are a caring bunch, and it was great to become friends with the people who participated in and ran the program. *JOB PLACEMENT: I got hired by Aetna as a data science analyst within three months of completing the Bootcamp. The job search is intense but Vivian and the hiring team were always there trying their best to help us. There is a room set aside for graduates to work in when on the job hunt, which made for easy access to staff. During the Bootcamp, we had several courses about how to sell yourself which was especially important for people who are new to the U.S. job market. From teaching you how to impress your interviewer to helping research relevant details about a target company, the hiring team was very dedicated to providing the necessary support to help me succeed. Also, Vivian seemed to have a contact at almost every company I wanted to apply to, which was a real plus. I’m glad I made the decision to do this, it was worth it for me.
Joe Keepers
Joe Keepers
This course was a masterpiece. Derek Darves the instructor, quickly brought us to competency with the R programming language. Then he expanded the course by introducing the packages used for analysis and visualization, progressing through introductory use to somewhat elegant and sophisticated programming challenges. Ultimately Derek brought us to a self-sufficiency level for continuing our R education. The course was a pleasure as Derek is clearly an R expert and aficionado weaving many practical tips and historical insights into the lectures. His programming experience, statistical insights and extensions of the course materials gave it a graduate level feel, while never ignoring the fundamental skills being taught. I highly recommend it.
Carlos S.
Carlos S.
I attended NYCDSA 5-week course (5 full-time days, one per week) in 4Q16 as part of my preparation to start the same school bootcamp. This was a great introductory start to learn R due to the comprehensive syllabus and dedicated teacher effort. About the syllabus, you will learn Base R syntax and principal data structures identification and manipulation plus a bunch of other packages (e.g. DPLYR) that will make your life easier when treating data sets. The instructor was a Sr. Data Scientist that really gave us two sides: theoretical and hands-on day-to-day professional experience views. This was very helpful. I found that there're lots of courses out there but most of the times taught by recently-graduated teachers that haven't applied a lot of the syllabus to real-life professional situations. This for me was a plus. The only soft point of the course was that I would have liked to go more deeper into web scrapping, yet it's true this course name is 'data analysis and visualization in R' and not 'Web scrapping using R'. One advice only for prospect students: block your agendas during five weeks since you will need a lot of time to review the materials and deliver exercises, which after all it's not a bad thing as it makes you feel good as you feel you have learned a lot. Highly recommended.
Vinod Shekar
Vinod Shekar
This was a great class that I truly enjoyed attending every Saturday for 5 weeks. The class had a pretty steep learning curve but the slides and the homeworks did a good job of teaching the material. Our instructor, Derek, was an R guru and could answer any question we threw at him. I definitely plan to continue learning R and I can attribute my enthusiasm to having taken this class.
Sandra Barral
Sandra Barral
Great course to get started with R programming. Convenient location in the city, nice classroom mates with very different backgrounds, and an amazing instructor, Derek has an impressive deep knowledge of R and he is a very talented and dynamic teacher Totally recommended to gain beginner understanding of this language.
Ethan Weber
Ethan Weber
In October, I signed up for the 12 week bootcamp which starts in January. They recommended I take this course (free of charge) in preparation for the bootcamp to prepare myself in the language (I'm already comfortable in Python). I'm giving this course 5 stars because, for the format, I think they did a perfect job. The instructor, Derek Darves, was definitely qualified and a nice guy in general. They gave the tools to learn the basics of data analysis, manipulation and visualization.
Bernard Ong
Bernard Ong

AVP, Data Science & Application Architecture
Lincoln Financial
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 lots 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 numerous opportunities that allow me to 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.
Linlin Cheng
Linlin Cheng

Data Scientist
2U
The bootcamp provides an extensive overview of the most used Machine Learning algorithms in addition to RShiny, visualization, and webscraping (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.
Tyler Knutson
Tyler Knutson
The 12 week bootcamp at NYC Data Science Academy combines everything a budding data scientist needs while finding a balance between depth and breadth.  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 manageable 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.
Wanda Wang
Wanda Wang

VP, Data Scientist
Fraud Detection Citigroup
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.
Brian Saindon
Brian Saindon

Data Scientist
Medivo
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.
Trinity Yu
Trinity Yu

Quantitative Trading Analyst Intern
Hermes Capital Advisors, LLC
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 ensembling and stacking strategies and gain knowledge including but not limited to Unix, SQL, Hadoop, Spark etc. Soon after I contacted the academy, I got a 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 learned 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.
Jurgen de Jager
Jurgen de Jager

Data Scientist
Barclays Bank
The decision to enroll in this Bootcamp was one of the best decisions I’ve ever made. I had high expectations coming into 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 challenging enough to challenge those with a Ph.D., 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 encouraged 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 software, 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.
Arda Kosar
Arda Kosar

Senior Data Scientist
Publicis
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.
Tingyan Zheng
Tingyan Zheng

Big Data Analyst
GroupM
This course covers major R machine learning topics; it is intense, and you will learn a lot if you keep up with the pace. Instructor Shu Yan is great at explaining complicated statistical concepts/formulas and translate them into R coding techniques. Course materials, in-class practices, and homework assignment are helpful regarding learning and future references. I would recommend this course to anyone who is interested in data science/machine learning but doesn't know much about this field. It will be a good start for you if you plan to work in this area. It certainly helped me understand a lot about data science and improved my R coding skills. What I learned from this course is worth the money I paid and the effort I put in.
Bin Lin
Bin Lin

Data Science Engineer
Hearst
I was coming from a Computer Science 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 visualization (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 visualization at the beginning. Python is more useful when building production pipeline models. Also Jupyter Notebook (originally 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 review 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 a difficult time to come up with an idea or started it late. Lesson learned! During the bootcamp, because I was from computer science background, I was quite relaxed on the programming parts. But I definitely struggled a lit bit on the Machine Learning part since it involved advanced Math and statistics. So I had to go back and review some of the Math material and took some online training on statistics. Therefore it would be great advantage for people with statistics background. If people without statistics background and 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 assistance, NYC Data Science Academy has connections with hiring partners. Therefore we got many job opportunities directly from the hiring 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 important, it would be great to have an 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. Second suggestion is that more hands-on on Spark excise. I would suggest Databrick community version to be used for student excise.
Iris Huang
Iris Huang

AVPt, Quantitative Analytics
Barclays Investment Bank
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.
Jiaqi Luo
Jiaqi Luo
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.
Robert Castellano
Robert Castellano

Data Scientist, Digital Intelligence
JP Morgan Chase
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.
Tatiana Sorokina
Tatiana Sorokina

Sr. Director, Data Science
Medivo
Hiring a Data Scientist in NYC is a full-time job on its own. Your inbox may be exploding with hundreds of applications, yet it is extremely challenging to find the right candidates. While I was in the middle of sorting through resumes I was invited to a Data Science Academy happy hour by Vivian. I heard of Data Science Academy but never thought to look for hires there.
As soon as I arrived I met Vivian and her team who already knew what type of Data Scientist I was looking for and introduced me to a few students. I was so impressed by them that I decided to invite them for an interview and within one week hired one of the graduates. He has been working with us for a few months and has already made a difference. His amazing technical skills combined with a very strong business acumen helped him take a lead on critical corporate projects and execute them with excellence.
I strongly recommend all employers looking for Data Scientists to contact Data Science Academy as it truly helps prepare the next generation of data scientists for real world jobs.
Denis Nguyen
Denis Nguyen

Data Scientist
Ameritas
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!
Kelly Mejia Breton
Kelly Mejia Breton

Associate Director, Marketing Science
Mindshare
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!
Ho Fai Wong
Ho Fai Wong

Manager
PWC
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.
Barbara Wang
Barbara Wang

Business Intelligence Analyst
SPS Commerce
I have been taking classes at NYC data science academy, there is a reason I came back. I learned so much from both of the instructors I had. They really really do care about you and give you a lot of individual attention. You almost can't slack because they will be right there and push you to finish your problem sets. This is something you can't get just taking an on line class. I highly recommend anyone to take this class in person instead of on line.
Wendy Yu
Wendy Yu

Business Intelligence Modeler
ASCAP
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 interviews! 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.
Adam Cone
Adam Cone
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.
Christopher Redino
Christopher Redino

Lead Data Scientist
Nielsen
I chose NYCDSA over similar bootcamps because they seemed to have largest breadth of content and also seemed to be the most challenging, and I believe they delivered 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 engaging, and the instructors are very knowledgeable. The course content (slides, lecture code, homework, etc) are not only excellent for learning the material, 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.
Sricharan Maddineni
Sricharan Maddineni
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.
Joseph Lee
Joseph Lee

Data Scientist
Uptake
The program offers a very good course for building foundation 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.
John Montroy
John Montroy

Data Scientist
theLadders
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.
Sebastian Nordgren
Sebastian Nordgren

Senior Vice President
Citi

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 to anyone with an interest or stake in Big Data.

Jake Lehrhoff
Jake Lehrhoff

Analyst
Spotify

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.

David Comfort
David Comfort

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 learning, in a rapid but focused manner. The NYC Data Science Academy provided the perfect opportunity 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 challenge 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.

Jean-Francois Darre
Jean-Francois Darre
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:
  1. the theory
  2. the tools
  3. coding
  4. 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:
  1. 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).
  2. 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 organizes "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 briefly (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 optimize 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.
Nate Aiken
Nate Aiken

Data Analyst
Memorial Sloan Kettering

I had an interest in data science but was making slow progress learning it on my own. This program gave me a strong foundation to build my future growth upon. It covered all the statistics necessary to apply statistically learning methods appropriately. It taught the most commonly used machine learning methods across industries. These methods were covered in both R and Python. Seeing the material in both languages was great, it gave you two chances to be exposed to each topic. All of the material was presented with clear lecture slides that will continue to be a resource. Each topic was also presented with sample code and exercises to explore the material in a hands on fashion. We also had the chance to work on real world data science projects that applied the material covered, with the assistance of our teachers and TAs. The bootcamp hosts a monthly Meetup that gave us a chance to present our work publicly. We had weekly speakers who were leaders in their respective fields come and speak to the class about different facets of data science. In some instances these speakers also had projects we could work on if we were interested in their field. The bootcamp went to great lengths to get us access to hiring partners, actually bring data science managers/HR managers to us. To be successful in this program you need to work as hard as they work for you. It wasn't uncommon to work with instructors late into the night or on weekends. This has been a great experience and I would recommend it to anyone who is serious about becoming a data scientist.

Shin Chin
Shin Chin

Associate - Senior Data Scientist
Booz Allen Hamilton
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.
Pokman Cheung
Pokman Cheung

Associate
Goldman Sachs

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 other aspiring ones on real-world projects.

Sam Brand
Sam Brand

Product Growth Manager
Stack Overflow
I took both Data Analysis and 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.
Punam Katariya
Punam Katariya

Biostatistician
Mount Sinai Hospital

Data Science Bootcamp was the best experience in my career. Instructors were not only helpful in teaching the regular materials but also guide you to establish your confidence in yourself to be a Data Scientist. They will help you even after completing your bootcamp. Nice and honest environment.

Mark Li
Mark Li

Quantitative Researcher
Twitter

I took Machine Learning with R and Hadoop data engineering classes in 2015. They are all well-structured classes with extensive information coverage and concrete learning process design. All the techniques been told in the class are very practical and can be applied to work very fast. In addition, it is also a great opportunity to build your "data science" fellow network because all your classmates are "Pro" in this domain with a lot of wonderful industry experiences to share. I would definitely recommend NYC Data Science Academy to my friend!

Jinying Li
Jinying Li

Director of Campaign Analytics
Bloomberg LP

Vivian came to our company and taught us five one-day sessions in R from entry level to intermediate level. I had no experience in R before. But I have learned a lot from Vivian and from the resources she provided, both from online and from the books. The homework and the office hour are also very helpful. After the classes, I have started to use R in my job from very basic stuff to more advanced data manipulation and analysis. Vivian is very knowledgeable in R and a warm person to work with. Thank you, Vivian.

Yu Ma
Yu Ma

Risk Analyst
Upwork

I took Machine Learning with Python and Data Analysis with Python in the Spring. I found both course useful and informative. The courses have given me a comprehensive and yet in-depth introduction into Machine Learning and Python. And these skills turn out to be invaluable at work. Most importantly, Vivian is an excellent instructor. She is immensely helpful and supportive which makes the learning process quite enjoyable. Definitely recommend NYC Data Science Academy!

Liz Klobusicky
Liz Klobusicky

Senior Manager, Management Science & Integration
NBCUniversal Media, LLC

I took the Data Science with Python: Machine Learning course and I learned a lot. This course helped me to improve my data analysis and general Python skills. It introduced me to several new libraries and algorithms, most of which I plan to use at work. Overall, I had a very positive experience.

Bret Fontecchio
Bret Fontecchio

Python Developer
Akamai Technologies

I took Vivian’s Data Science course and had a fantastic experience. I networked with Data professionals from the NBA, the Federal Reserve Bank, NYC startups, and more. I learned a lot very quickly and had a lot of fun. It’s a nice part of the city and the building has a great startup feel to it. …While I was still enrolled I implemented a hierarchical clustering algorithm and put it into production. I wouldn’t have been able to do that if I hadn’t learned Data Science at NYC Data Science Academy.

Korrigan Clark
Korrigan Clark

QA Engineer
Basho Technologies, Inc

Thanks to NYC Data Science Academy, I was able to find a great job as a data scientist at a startup before the 12 weeks was even up. Had it not been for the Data Science Boot Camp, I would still be looking for a job. The Boot Camp builds confidence in data science through exercises, homework, lectures, and personal projects. These projects are immensely helpful when job searching, and students are encouraged to take on as many as possible. Over the 12 weeks, I gained proficiency in R, Python, Hadoop, and SQL, just to name a few. Vivian, the Program Director, is truly devoted to her students’ success. She continuously challenged us to step outside our comfort zone and dive head first into the most difficult concepts. The other staff members at NYCDSA including Bryan and Janet, are also extremely knowledgeable and helpful. Students have the full support, encouragement, and expertise of the NYCDSA staff. This experience, while extremely challenging, exceeded all my expectations. The skills and knowledge gained from NYC Data Science Boot Camp is well worth the price, and the effort.

Aaron Ouyang
Aaron Ouyang

Analyst
Annalect

Great class. For only a 5 week class it is very comprehensive. Covers the basics and commonly used libraries used in python for data analysis as well has how to use them. Notebooks used in the class are a great go-resource after the class ends. Also a great community of data professionals and networking if you are thinking about a new gig.

James Cai
James Cai

Head of Data Science
Roche

Vivian led two training sessions for our team at our company location, and covered both introductory and intermediate data analysis using R in five days. We very much enjoyed Vivian’s engaging teaching style and the hands-on exercises. She was able to draw on a broad array of real world experiences she had with clients in many different industries. This helped us feel the excitement of how data science techniques were used to solve challenging problems. I particularly like the fact that she insisted on the post-training projects that were completed by all attendees. It was satisfying for me to see what our team could do in a very short period of time using the skills gained in the training.

Michael Caruana
Michael Caruana

Senior Product Manager, Data Science
Fusion

Great comprehensive course that give you a thorough overview of Python and how it can be used in the field of Data Science.

Matt Gray
Matt Gray

Analyst, Insights & Strategy
NBCUniversal, Inc

As a novice coder, this class was a great way to learn how I can manipulate and analyze data in Python. Would recommend for anyone interested in learning how to use python and apply to daily work.

Mark Rothe
Mark Rothe

Senior Statistical Programmer
Roche Innovation Center

Excellent 2 days of GIT and GITHUB training! The trainer, Bryan Valentini was very personable and took the time to answer everyone’s questions as well as provide desk-side assistance. Would definitely recommend to others new to GIT and GITHUB!

Christopher Bian
Christopher Bian

Cofounder & CTO
Unlockable

The intermediate python machine learning course was a fascinating time. It gave me a much better feel for the variety of practical techniques that can be used in the field, and I’m frankly really excited to apply what I’ve learned in the near future. Make no mistake, the course and topics are challenging, but your perseverance will be rewarded.

John Maiden
John Maiden

Data Scientist, Digital Intelligence
JP Morgan

I found Vivian’s Intermediate Python class to be very refreshing, given the formulaic approach that most books I’ve read on Data Science tend to be. She definitely knows her subject, clearly communicates that to her students, and fosters lively debate during class. Can’t wait to see what my fellow students present for their final projects!

Margaret Hung
Margaret Hung

SVP, Intelligence Solutions & Strategy
Millward Brown Digital

As the business world becomes increasingly data-driven, the Data Sciences classes at NYC Data Sciences Academy are invaluable to driving career success, not only for actual data science practitioners, but those who collaborate with them day-to-day to execute on insights to be gleaned from data sciences. I just completed the Intermediate level Data Sciences with R class and have immediately benefited from the ability to understand the different type of advanced analytic techniques that are available to help my clients with their business issues, to better communicate and collaborate with our Data Sciences team on a tactical level and then to take their output and accurately translate it into our clients’ business language. The course was comprehensive and Vivian brings a lot of passion and dedication to the class and ensuring her students’ success.

Yide Pan
Yide Pan

Business Consultant
Binocular Vision LLC
The 4 days R training was very impressive. I am new to the R world with little technical background, Vivian and her team explain the R with various examples close to my daily works, they prepared a very detailed training slides, and gave us plenty of time to do the hands on. We also created some virtual project after the class under the help from trainers. The trainers are very very energetic, they are very good at leading you to the key points, and always pushing you to complete the homework,LOL. Great thanks to Vivian and her team. I am exploring R in more area in my works, looking forward to work with you again.
Kai Sun
Kai Sun

Scientist (DMPK & Safety)
Roche

It was only a four-day entry-level training, but it turned out that I made the right choice to come along, join Vivian and her talented colleagues, and benefit tremendously from the lessons, discussions and on-site exercises. What’s more, with the encouragement from the teachers, I managed to complete my own small R project, and have been interested in further my studies on R ever since. I strongly recommend any one, who is intrigued by data management, visualization, data mining, statistics, or critical thinking using mathematical tools, to learn R, or preferably, learn R with Vivian and her colleagues, to expand his or her horizon, and make use of R in many ways possible.

Harrison Adler
Harrison Adler

Product Adoption/Data Scientist
Google

I took both the intensive beginner and intensive intermediate R classes back-to-back on weekends over a four-month period. Although 7 hours a session may feel hefty, once you’re in the class time will fly by. Sessions split time between lecture and hands-on exercises, so you have lots of time to ask questions. Homework assignments are manageable – Vivian is very accessible should you have a question by email or in-person office hours. Each class ends with a Demo Day of a project of your choice. You will access real data from the Internet using APIs and analyze this information and ways you never would have thought possible using Excel or even SQL! Because of the initiative I took to learn the material, I have accepted a position as a Data Scientist at Google. A big thank you to Vivian and the team at the NYC DSA for helping me make the leap in my career from business analyst to data scientist!

Jiten Pai
Jiten Pai

Big Data & Business Intelligence Architect
A+E Networks

I took the Data Science by R programming (beginner level) class taught by Vivian. The class material was very well organized and consisted of tips and tricks that only someone who has worked extensively with R would know, some undocumented features included. The course, home work, and project are quite intensive, so be prepared to put the time in; but when you are done, you will be a much more valuable professional! It’s all well worth the effort and hard work. The beginner course has set the stage for me to take the next level data mining class, which I am eagerly looking forward to.

Diana Enriquez
Diana Enriquez

Content Researcher, TED Content
TED Conferences

I enjoyed this class — I would give it a 4, only because it went a little too fast for me at some points. I am a beginner of the most clearly beginner level. I had played with some front end programming, but never attempted backend work. The 5 hour classes on Saturdays were tough because it required a lot of homework and studying during the week, but the instructor was good about answering questions and pushing us to keep working on new and interesting things. The program was extremely supportive of me while I was trying to learn new material, I have and will continue to recommend this class/NYC Data school.

Kannan Sankaran
Kannan Sankaran

Software Engineer, Business Systems
AppNexus

I took the first offering of Data Science using Python a few weeks ago, and definitely recommend it to anyone who loves hands-on learning with some guidance. Let me explain: Last year, I took Coursera’s Machine Learning/Intro to Data Science courses and did well, but did not do a hands-on project that would enable me to retain a lot of knowledge. But this course required me to pick a detailed project and present it to a live audience, who then determined whether I did well or not. So I learned how to do web scraping, extract social media API data, write object-oriented Python, utilize a NoSQL database (MongoDB) to store results, and finally create visualizations in D3 and HighCharts. And then the pressure to present well, just to pass the class. Our instructor John was competent, knowledgeable and helpful, and covered a variety of useful tools like Pandas and Scikit Learn, including machine learning algorithms. And Vivian is always pushing us harder to do better. Sounds familiar?

Christopher Crosbie
Christopher Crosbie

Healthcare and Life Science Solution Architect
Amazon Web Services

The instructor, John Downs, was very knowledgeable and did an excellent job of providing an overview in the key areas of Python. After the five week class I went from knowing essentially nothing about Python to using it as one of my “go to” tools in which I am able to accomplish tasks at work on a daily basis.

Sasha Bartashnik
Sasha Bartashnik

Analytics
Zulily

I took the beginner level Python class with John Downs and really had a great experience. John is very knowledgeable about Python and programming in general, and was able to be helpful to students of all levels in the class. The exercises in class and the homework got our hands dirty with the language and the final project was a great way to create a real result by the end of the course. Overall it was challenging, but a valuable intro to a useful tool that was easier to approach with real-life sessions than self-study demos on my own. I’ll definitely take classes with NYC Data Science Academy in the future and would recommend it to my friends.

Pia Ramchandani
Pia Ramchandani

Manager
PwC Advisory Analytics

John Down’s Python for Data Analysis class was a helpful introduction to using python toolkits such as Pandas and Scikit Learn to work with large and complex data structures. John started the class off slowly to get the group adjusted to Python syntax, but made sure to include all of the essential data management/analysis techniques to get started (e.g. dataset merging, manipulation, basic stats/regression, etc). In a short course, John did a great job of including numerous examples in ipython notebooks that he gives to the class– this approach was very helpful for exposing beginners to more complex techniques that they can go back to when they are ready. I definitely recommend this course to any beginner interested in learning how python can help make data analysis faster and easier.

Akiko Togami
Akiko Togami

Business Analytics | Data Visualization
Bloomberg LP
Before taking Vivian’s R Intensive beginner course, I had no experience in programming and I was just someone who was interested in data visualization in more sophisticated ways than making bar graphs in Excel. The class was really intense. A lot of preview and review would be needed to keep up with the 5 weeks long course, but Vivian always lifted our spirits up and consistently provided necessary help, online and offline, literally anytime we needed. After completion of the class, I am still not used to myself who can confidently use various packages and functions to come up with different kinds of data visualization and manipulation. This is indescribably great feeling and Vivian’s voice “delivery is our goal” echoes in my head now. Creation is pure joy (though the process could be painful). I think taking this course was one of the best investments I made in my life, and it could not be it if that was not brought by you, Vivian. Thank you so much!!
Roger Huang
Roger Huang

Data Analyst
Shyp

Very informative class. Vivian uses intensive exercises and hand-on practices to make sure you understand how to use the packages she teaches!

Marifel Corpuz
Marifel Corpuz

Associate Director, Advanced Analytics
MEC Global, Rosetta

I completed the Intensive beginner course for R and I highly recommend it! I’ve learned a lot in 5 weeks and I can say that I am now an R convert (from SAS). I’ve learned so many functions and packages that I am now able to use them confidently at work. Vivian was also a great, hard working teacher who encouraged every one in the class to study harder which means she really cared that that her students would become great data scientists sooner than later. I like the class so much I am now taking the R intermediate class.

Paul Schaffer
Paul Schaffer

Director
Analytics Media Group

I strongly recommend this class to all potential students who have some programming background. The pace at the beginning is necessarily rapid to cover the basics of syntax and structure, so that more time can be devoted to numpy/scipy/pandas/etc. John was a fantastic instructor, and impressively it was his first time teaching the course! Super nice/patient/knowledgeable, and he has a real knack for explaining stuff. Taking introduction to Python for Data Analysis was a great decision for me. In a relatively short period of time, I was introduced to the top analytical code libraries in Python and gained experience using them. Well worth the time and money: I’d do it again in a heartbeat.

Morgan Polotan
Morgan Polotan

Software Engineer
Tapad

The D3 class was a great intro to the library. After finishing the class I can create simple data visualizations (bar, line, scatter, chloropleth, etc) and know some more advanced concepts (brushing, reusable charts). I also know enough about how the library works to continue learning on my own. I’d recommend coming in with some JavaScript knowledge as that will help you grasp the concepts quicker.

Eugene Zee
Eugene Zee

Google for Work - Global Head of Android Operations
Google

As an employer, I have found NYC Data Science Academy classes significantly improved the data science and visualization skill set of our research and business analyst. The courses are practical, compressed and come with lots of support. We sent a motivated team member to the Intensive Beginner R class. Previously he had no R experience and in one month’s time he was able to achieve proficiency. Since completing the course, our analyst has built, analyzed and presented data in valuable new ways.

David Russo
David Russo

Landscape Architect / Data Science Student
ExecThread, Inc.

I just finished the 002 session of the beginner R class. We certainly got a lot of “bang for our buck”, because Vivian is preeminent in the field of data science, and she was able to move through a lot of material very quickly. She worked extremely hard in preparing well organized slides, and for me the key was to go through the day’s presentation, provided beforehand, during the week prior to the class, running all the code and seeing what it does. This allows you to keep up and absorb her lesson when you get into class. In addition to getting a solid start on the use of R, the class also provided valuable insight into the field of data science, which is a career into which I am interested in transitioning. Lastly, Vivian made herself available to us weekly for extra help, either in person or via web interaction, which was much appreciated. Like I said, she is very dedicated and works extremely hard at seemingly everything she does. Thanks Vivian!

Heena Doshani
Heena Doshani

Quantitative Researcher
QS Investors

I attended the beginner’s workshop for R and I found it extremely useful. The classes were very well organized. The slides were well paced with many practical examples. I especially like the hands on format of the class, you work through the slides on your laptop. I had very little knowledge of R before and I learned many tools during the course. I was particularly interested in the visualization tools. Since the course, I have used some of the charting tools that I learned in my presentations at work as well. Both Scott and Vivian did an excellent job teaching R basics. They were very helpful and answered questions in person, email and piazza (online platform where we would post our solutions). Vivian also shared with the class a lot of material and practical examples. I would highly recommend this course to users who are interested in learning R.

Donald Fleurantin
Donald Fleurantin

US Private Equity Lead
Thomson Reuters
NYC Data Science Academy provided me great exposure to data science topics that I haven’t come across in either school or previous jobs. The hands-on assignments are practical and make use of real-world examples. As product development is becoming more data-driven, it will be crucial for product teams to have a solid grasp of data analysis which NYC Data Science Academy fills the knowledge/skill gap.
Mike Selender
Mike Selender

Technical Analyst
Chubb

I took the initial version of this class late fall 2013 and found it to be well worth the time. The slides, examples and exercises were well organized. Scott Kostyshak’s presentation style is clear and concise. The second iteration will have twice the classroom hours and cover a lot of material that there wasn’t time for in the initial format. It’s worth the investment if you want to dive into the R ecosystem.

Jasna Vukovic
Jasna Vukovic

CCB Risk MIS Reporting & Analytics Manager
JPMorgan Chase

The Introductory R class covered a broad range of information, and for a statistics and programming newbie like me, was indispensable for coming up to speed on a variety of related subject matter. Vivian is passionate about R, open data, statistics, etc.. Her enthusiasm is contagious!

Annaliese Wiederspahn
Annaliese Wiederspahn

Managing Member
Equipoise

Super helpful. Vivian is a fantastic teacher. She really pushes everyone to dig in and start solving problems.