Student Testimonials

In short, the bootcamp excels on the curriculum, providing guidance, and career services. I found this bootcamp online, and I decided to go for this one because of the curriculum and the feel of it during the assessment process - they sounded like they knew what they were doing! They provided valuable feedback on the areas I needed to improve. I have a math degree and was already a Sr. Data Analyst, but wanted to move a step forward in my career by learning Data Science and Machine Learning. What I liked is that the coursework is tailored to each person depending on their experience, strengths and weaknesses. I went for the part-time program since I was also working, and I am not going to lie, it is challenging! But worth it. Throughout the bootcamp I learned of many DS/ML concepts that are widely applied across different roles and companies, the projects assigned were the best way to apply and practice the things learned, and I eventually was able to apply them in my own job. They also offer TA sessions that are very helpful to review on the parts that seem confusing. One thing to note is that because of the extensive material taught condensed in a short period of time, studying extra materials is needed in order to get the most out of the bootcamp. Upon graduation, there are helpful resources on landing the next job - mock interviews, career advising, and networking. I landed a job at The Trade Desk as a Business Intelligence Analyst thanks to the stories I was able to tell of the projects I worked on in the bootcamp, the projects I worked on my previous role with the bootcamp knowledge, and with the various mock interviews (I was very bad at interviewing).

In my mind, there is no such thing as a perfect bootcamp but NYC Data Science Academy got as close to perfect as it can get for me, which is why I gave it a 4 star. The curriculum is the most comprehensive of all the data science bootcamps available and covers topics that are the most practical for job search. What students learn at schools are often not used in real-world settings. NYC Data Science Academy gets this so its curriculum focuses on skill sets that graduates can apply directly at work but also offers materials for those who want to take an extra step and learn about non-practical aspects of data science. Instructors are all well qualified to teach and mostly do a great job but the only thing I would say is the pace of learning could be overwhelming for some students if they don't take the time to review the materials before and after each class. Doing the homework, which is optional, reinforces the learning. This three-pronged approach of lectures, homeworks, and projects positions the students well for a data-related job post-graduation if they put in the work to complete all of them. Lastly, the career team does a fantastic job guiding the students through the job search process. The team knows what works and what doesn't, so as long as students follow the guidelines, the prospect of finding a data-related job is very high (bootcamp has statistics on this). Overall, I'm very satisfied with the experience and would recommend the program to anyone who's looking for a new career path or looking to add a new skillset.

I joined NYC Data Science Academy this summer to help me make a career transition from Material Science Engineering into Data Science, and in short, it worked! I increased my salary, easily making the Bootcamp worth it as a purely financial decision, and am starting to work in a new exciting field. I chose them over others because I was impressed with their instructors and they offer continuous career support after graduating. I was not disappointed. Their instructors are passionate and knowledgeable and seem to genuinely care about teaching and helping their students. After graduating I had two internships directly from relationships and connections I made at the Bootcamp and had many interviews from the same network. Their career services have always been available, helping me with my resume and acting as a soundboard to help prep for interviews. I only recommend getting into Data Science if you love math and coding. If you do and are willing to put in the work NYC Data Science Academy will prepare you for and help you get a job.

Before my NYC Data Science Academy Bootcamp Experience, I was a high school mathematics teacher. In order to make informed pedagogical decisions, I increasingly relied upon data collection and data analysis. This sparked my interest in data science. Since I enrolled in the Summer Session of the Bootcamp, I was able to continue to receive my teacher salary for most of the 12-weeks. After making the decision to enroll in a bootcamp, New York City Data Science Academy quickly became my top choice for the following reasons: Multiple Languages (Python and R) I appreciated the emphasis on learning both Python and R. When searching for a position, this increased the number of jobs I was qualified for, and I used both Python and R during the Technical Assessments of my job search. Pre- and Post-Bootcamp Support From my research, I was convinced I would be supported before and after my bootcamp experience...which was true! Pre-Bootcamp I had no previous programming experience, so I enrolled in 2 helpful introductory courses at the NYC Data Science Academy, one for Python and one for R. The price for these classes was subtracted from my Bootcamp tuition. Post-Bootcamp During the final Capstone Project, many students elect to work with outside businesses that partner with the NYC Data Science Academy. The company I worked with offered my team an additional 2-month, post-bootcamp data science internship. This was a great learning opportunity, plus a great addition to the resume! Months after my bootcamp ended, I was able to participate in a free, 2-week intensive, marketing-focused workshop led by NYC Data Science Academy Bootcamp Founder Vivian Zhang (open to any graduated bootcamp student). The workshop was filled with marketing domain knowledge and practical applications. In addition, I was also able to schedule over 10 meetings with NYC Data Science Academy Career Support, Bootcamp Alumni, and Bootcamp Faculty, allowing me to brainstorm and prepare for my data scientist & data analyst interviews. I am very glad I chose to join the NYC Data Science Academy Community. I just landed my first job as a Data Analyst, and I believe my Bootcamp Experience was worth every penny.

The NYC Data Science Academy (NYC Data Science Academy) was one of the most intense, career-boosting – and yet enjoyable – educational experiences in my life. This coding bootcamp was a crucial factor in landing me a data scientist role at one of the largest and most respected companies in the U.S. First, I would like to highlight its usage of real-world data to train students on key steps in the data science lifecycle: defining the problem at hand to be solved, gathering, cleaning, visualizing the data, feature-engineering, training and deploying a variety of machine learning models, and quantifying the business impact. The coursework is taught in Python and R, the two most widely-used languages in the industry, and we worked through many examples (homework + projects) of how to use the famous libraries: pandas, sklearn, seaborn, matplotlib, dplyr, ggplot2, and shiny. By the end, students have a complete portfolio of 4 projects to showcase to employers, complete with github code, business summaries (blog posts), and a Linkedin profile tailored towards the job search. Additionally, on top of the immersive technical skills preparation, there is also an emphasis on how to launch a successful job search. We benefited from networking events with alumni who are currently employed at prestigious data science companies, and an abundance of interview questions to practice with, ranging from data structure / algorithm questions to how to answer those tricky behavioral questions with no right answer, i.e. – “What is your biggest weakness?” Finally, everyone is hard-working and smart, but also very nice people as well. The instructors have Ph.D.s and/or industry experience in data science, but they are also down-to-earth, fun, and great to chat with outside of coding advice. All of my classmates were very friendly as well, and the alumni network is strong, i.e. – many graduates from the program are happy to tell you about their experience over the phone and provide advice. As a result, I would like to contribute and give back to the community as well, so I am happy to answer questions from prospective and current students. Final note: NYC Data Science Academy is well worth the time and money, but you have to work hard for it. You get what you put into it. So, my recommendation is: don’t skip the pre-work, try to do all of the homework assignments, understand the concepts, work hard on the projects, get to know your classmates, do the interview prep exercises (especially SQL), and treat applying for jobs itself as a job.