Testimonials

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.