NYC Data Science Academy

My bootcamp experience has been incredibly positive and supportive. From day one, the entire team made me feel welcomed and encouraged. Everyone was always willing to help, whether it was during coding sessions or when I had questions outside of class.... Read More The coding sessions, in particular, were extremely helpful — they not only strengthened my understanding of key concepts but also gave me the confidence to apply them in real-world scenarios.
Vivian has been especially responsive and supportive throughout the journey. She consistently goes above and beyond to make sure students are on track and feel motivated. Her quick feedback, guidance, and approachable nature really made a difference in my learning experience.
My skills in Python, Pandas, and SQL have greatly improved during the program. I now feel much more confident working with data, writing clean and efficient code, and approaching problems with a structured mindset.
Overall, I feel grateful to be part of a community that genuinely cares about my growth and success. I would highly recommend this bootcamp to anyone looking to gain strong technical skills in a collaborative and encouraging environment.

I decided to join the Data Science with Machine Learning In-Person track at the NYC Data Science Academy because I knew it would help me break into the New York job market. The bootcamp’s strong connections in the city were a major draw, and knowing that... Read More it’s accredited by the New York State Department of Education gave me added confidence. After comparing it to other bootcamps, the quality of the project portfolio stood out to me. The projects we worked on were not only challenging but also helped me stand out to potential hiring managers.
What really made a difference for me during the bootcamp was the support from the instructors and TAs. They are incredibly knowledgeable and always available to help, which made a huge difference in my learning experience. The peers in the program were mostly people with Master’s degrees, which created a highly motivated and intellectual environment. The course itself is intense, with a lot of material to cover, but the hands-on projects made it worthwhile. We spent a lot of time working on real-world projects, and the support from TAs and professors was exceptional throughout the process.
During the bootcamp, I learned Python, SQL, R, and machine learning techniques that gave me the practical skills I needed to break into the field. However, I do want to point out that the bootcamp doesn't focus on algorithms or data structures, which might be useful for those who want to dive deeper into that area. But for anyone looking to become a data scientist and get their foot in the door, this program is perfect.
The career support was one of the most valuable aspects of the bootcamp. They helped me build my resume, gave me job referrals, and even after I graduated, Vivian continued to use her network to help alumni like me. One of the best things about the bootcamp is the network of peers you build. I made so many great connections during the program, and many of my classmates are now data scientists in top companies. Those connections have been invaluable in my career journey.
Before joining the bootcamp, I was an industrial engineer, but after completing the program, I landed a data scientist role. I’m currently an Analytics Manager at a Fortune 500 company.
The alumni network and ongoing career support were crucial in helping me land my role. As a hiring manager now, I’ve found that it’s so easy to connect with the bootcamp to find talented candidates. The students are incredibly smart, and I’ve hired a top performer from the program who has exceeded expectations.
Overall, the NYC Data Science Academy helped me make a seamless transition into the data science field, and I highly recommend the In-Person Data Science with Machine Learning track to anyone looking to jumpstart their career in this field.

My journey with NYC Data Science Academy began in 2018 when I enrolled in their Data Science and Machine Learning bootcamp. As a Biology PhD looking to transition into Data Science, this bootcamp became a pivotal moment in my career. Within two months... Read More of completing the program, I received offers from two different groups at JPMorgan Chase. Over the next five years, I was promoted to Vice President and Data Scientist Lead, where I developed personalized financial insights that were integrated into the Chase mobile app.

Recently, I relocated to Europe for personal reasons and took some time off, only to find myself facing the ever-evolving tech job market. It quickly became clear that the landscape had shifted significantly towards generative AI. After researching multiple options, I returned to NYCDSA and enrolled in their "AI Bootcamp for Real World Applications." This program provided the deeper technical training in state-of-the-art AI, particularly in Large Language Models (LLMs), that I needed to reenter the workforce. For my capstone project, I developed an advanced hotel recommender system using semantic search, Retrieval-Augmented Generation (RAG), and LLMs, hosted entirely on AWS. Additionally, I published blog posts on the project and my AI insights, which helped demonstrate my expertise to potential employers.

What sets NYCDSA apart from other institutions is the depth of their technical curriculum and hands-on approach. While many programs lean more towards business concepts and inspiration, NYCDSA strikes the perfect balance between theory and practical application, particularly in design and implementation. Cole, the lead instructor for the AI Bootcamp, was instrumental in my success, breaking down complex AI concepts in an accessible and engaging way. Thanks to this bootcamp, I re-entered the job market with confidence and cutting-edge AI skills. Two months after completing the program, I received offers from two different companies. I highly recommend NYC Data Science Academy, especially their AI Bootcamp, to anyone looking to advance their career in Data Science and AI.

An awesome experience! The pace is fast, the program is demanding. You need all your ability and energy for this course. The staff is composed of brilliant and kind folks who are there to support you in all possible ways. It is up to the individual how... Read More much is taken out of the program. It is not inexpensive but certainly amazing experience and tool under your belt.

Transitioning into a new career, especially in a demanding field like machine learning, can be an overwhelming challenge. But thanks to the NYC Data Science Academy, my journey was not only smoother but also deeply enriching.

The curriculum at NYCDSA is... Read More comprehensive and well-structured, covering everything from fundamental programming and statistics to advanced machine learning algorithms and data engineering. The instructors are not just knowledgeable but also deeply passionate about teaching, which makes learning complex topics much more manageable. They ensure that every concept is not only understood but also applied through hands-on projects, which are integral to the learning process.

I chose to attend NYC Data Science Academy in 2019 because their campus was located near Port Authority and they provided individual courses after work hours. I was new to data and coding and took advantage of my employer’s tuition reimbursement to take... Read More NYC Data Science Academy’s courses before heading back to New Jersey. While taking the courses, I appreciated each lecturer’s ability to translate difficult concepts into digestible content for non-technical students. This was possible because each class size about 5 to 10 students per lecturer. When the time came to fully transition from my life science research job and enroll into a data science bootcamp, I chose NYC Data Science Academy because of my positive experiences from the individual courses. For those new to data and coding, NYC Data Science Academy is a great place to start as you transition into the data field. It’s intense. You’ll learn and forget a lot. You might think why do I need to learn Python, R, and SQL when you just want to learn about Machine Learning and AI. When you look back years later after you’ve finished, you’ll appreciate having learned them all because employers don’t use the same technologies or languages and the bootcamp will give you the ability, but most importantly, the confidence to learn the job requirements. Unfortunately, bootcamp completion is just the beginning. You need to keep learning after you graduate and expect to be studying outside work hours and on the weekends. There is no prestige upon graduation. It’s a Data Science bootcamp. Your friends and family but most importantly your employers won’t know about it. In the past 5 years, I had only one interviewer know about the bootcamp and it was because the interviewer was also an alumni. Otherwise, in every interview you’ll need to explain what you learned and what you developed. Every student comes from different backgrounds and different experiences. I graduated from a state school with a Bachelors in Biology with no technical background whatsoever. I took my first coding course at the NYC Data Science Academy, 2 years after my undergraduate degree. I’m thankful for the bootcamp. Without this opportunity, I wouldn’t have been able to get my foot in the door. My current salary is more than 4 times the salary of the research position I had before the bootcamp. If I could go back and start over, I would save at least 6 months of expenses before enrolling. I would expect at least 6 months after graduation to start your next role.

I took this bootcamp mainly due to a referral from a friend and colleague from work. I had a background in working with R but had never really worked with python or ML. My schooling is in Engineering and have been exposed a bit to ML and programming,... Read More but have neve really delved deep into it. The Good: I though the availability of the TA’s and their responses were amazing. You essentially have infinite time you can schedule with them and their responses re always great. If you asked a question they didn’t have an immediate response to, they would even go back do research and follow up through email and personally cater to your questions, it was great! The best parts of the course were the python and R modules, they do a great job at explaining these and help you get started right away. The advanced modules on ML were hit and miss and found that I definitely needed to re-inforce after with more studying. The career guidance and the career network is amazing, at the time of writing I have not yet been actively pursuing a job (just graduated), but am already finding a ton of support. The guidance you can get from Vivian (the bootcamp founder) is great, she’s always actively trying to get you the best offers and career guidance and you can notice that she really wants her students to succeed. The projects are well structured, and I really loved them. They are designed to make you progressively get into designing a full blown ML project and though they were great. The Bad: Many of the office hours, live lectures and additional support are only offered from 9-5, even for the part-time online version of the bootcamp, this makes it difficult for working professionals to actually benefit from this. It would be nice if some of these were offered after 5pm so that we could attend. As you get more advanced and specialized, not all the TA’s can really help you, for example I had questions about CNN’s and LLM’s that the TA’s couldn’t really help with until they hired an expert (sometime later) that really knew the topics. The help on all the basic programming stuff is great though. I thought the SQL and Git modules were a bit lackluster and need more development, however, I also didn’t take the Data Engineering part (I decided to take the data science curriculum), so perhaps they’re better explained in the Data Engineering part and are only supposed to be a gentle intro for the Data Science curriculum. Some TA’s give better lectures than others, at the time I took the course the best and most comprehensive lectures (especially for the math heavy bits) I thought were given by Luke. The other TA’s did not give great lectures and found were difficult to follow. This mostly applies only to the advanced ML lectures were the math really played a big role. For the basic programming parts, all of the lectures were great, as a matter of fact I found Alex to be a great lecturer for these parts. Overall: I found this experience great, for me it was much better than just taking a course online from coursera or other platforms since here you actually have deadlines and classmates that you can interact with and they help keep you honest and push you towards actually finishing. That part was important to me as a working professional since I always found it hard to motivate myself to actively separate some time to studying ML on my own, but this course gave me all the correct motivation in all the best ways. If you’re looking for a smooth introduction to ML and can’t find the motivation to go it on your own, this bootcamp is the best. I will definitely need to study more after graduating to snag a job, but that comes with any bootcamp, and the post graduation services here are great as well.

I completed the online Data Science Bootcamp in 2021. I had been thinking about enrolling in a DS bootcamp for years, and although the price was steep, I read many positive reviews on NYCDSA and it was recommended to me by colleagues. I decided to put... Read More my life on pause for a few months and dove both feet forward in the full-time program looking to invest in myself and my future. Coming from a non-DS, non-programming background, one of the primary reasons I enrolled in an interactive bootcamp would be the structure and support working with peers and instructors. I quickly found this to not be the case. For the online program, the curriculum is entirely self-paced, online self-study. There are check-ins and office hours with instructors and mentors, but support is always passive, never active. The student must always take the prerogative 100% of the time to take ownership of their own learning progress and know their own deficiencies and weaknesses. This can work for certain extremely Type A, self-motivated individuals, but gets tiresome for anyone. Especially if you don't have a DS/programming background, you don't know what you don't know yet. There is never any feedback on code or any type of code review, and I found myself struggling to self-learn code and never knowing if I was implementing it efficiently. The program assumes a baseline knowledge of programming and it can feel like trying to run before knowing how to walk. At first, I had been extremely motivated and took advantage of all available learning resources, meeting with instructors and mentors regularly. But after weeks and weeks of self-studying challenging material, it becomes tiresome without real accountability. If I had suddenly decided to quit the program, nobody would have noticed. There is nothing about the program to hold you accountable, and it becomes little different than self-studying an online program like Coursera while costing tens of thousands more. The program sets you up with a cohort of peers early on, but other students either drop off slowly and/or progress through the material at different paces, and soon you feel like you're just studying by yourself. In terms of the quality of curriculum and instructors: the instructors themselves are second-to-none. You learn a lot from the live learning sessions and office hours as long as you can proactively utilize the available resources. The curriculum itself is good but has some holes. There is a heavy emphasis on machine learning - so much that you repetitively learn it twice, once in R and once in Python. There is less focus on key skills like Docker, Git, SQL, data visualization, data engineering etc. I have since been able to land several data jobs in my industry, and have done most of my continued learning while on the job. Only through actual work experience have I been able to reflect on things I wish I focused on more in the bootcamp. The positive is that you have lifetime access to the learning materials, so that you can always go back and review at anytime. Overall, I realized that most of these reviews are geared towards the in-person version of the bootcamp, and it felt like most of NYCDSA's support is biased towards its on-premise students. Maybe the in-person experience is entirely different, but the online experience felt isolating, even second-class, and I would recommend self-study elsewhere instead.

The 12-week Data Science bootcamp at NYCDSA was an incredible learning experience. The program provided an extensive and comprehensive curriculum that covered a wide range of data science topics, from data manipulation and analysis to machine learning... Read More and deep learning. What made it truly exceptional was the combination of expert instructors and hands-on projects. The instructors were knowledgeable and passionate, always ready to clarify doubts and provide valuable insights. The real-world projects allowed us to apply what we learned, reinforcing our understanding and building a strong portfolio. Furthermore, the academy's commitment to providing career support was remarkable. They offered guidance on job interviews, resume building, and networking opportunities, which greatly enhanced our chances of landing data science roles in New York City. Overall, my experience at NYCDSA was transformative. It not only equipped me with the necessary skills but also gave me the confidence to pursue a career in data science. I highly recommend this bootcamp to anyone looking to excel in the field of data science.

Biggest pro is the community which is very strong and the support you get from them in tbe job search is the best. Another pro would be the teaching staff who are very knowledgable of they are teaching. I could not think of a con as of this moment as... Read More my time in the program was very good