NYC Data Science Academy Reviews
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Raymond Liang
Great Intro to Python
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Coming from the finance field, I had very little experience in coding. I had dabbled with a little bit of VBA where I worked, but by no means could I have claimed to know how to code. That being said, I feel this class provided me a great foundation to Python. Tony, the instructor, made sure the concepts were reinforced by easy to understand examples, and even silly examples at times which was greatly appreciated. The in class exercises were also helpful to glue the concepts together and homework was also given for more practice. The one thing I could have suggested in terms of the weekend class itself is to perhaps allow for a longer day so the teacher do not have to rush over any particular topic. Overall, I really enjoyed this class and would recommend it to anyone who is looking to get their hands dirty with coding and data analysis.
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Dav D.
Sr. Consultant in Big 4
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I joined NYCDSA in late 2016, and there is no doubt about that the Data Science Bootcamp had helped me a lot in achieving my career goal. I was looking among several data science bootcamp back then, and my primary concerns were job placement rate, background of people who might join the bootcamp, and what industries had the alumni been working for. I decided to join NYCDSA because it gave me statistical answer of my concerns, not to mention how resourceful it would be speaking of its alumni network.
The only thing that I felt they could do better, well in 2 yrs ago, would be the career service, and the design of project groups. It would be helpful to arrange people with working experience with those who may not.
The best thing about this program is its brand. I had several final-round interviews and some of the interviewers were from NYC. These interviewers, they know about NYCDSA, how the curriculum is organized, and how much practice students would receive from the bootcamp, so it is not challenging for me to leave some impression on them.
If you are thinking about a career switch, enrichment of experience on resume, or just an investment towards personal skillset, NYCDSA is definitely the place where you would wanna go.
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Anthony Tagliente
Python Data Analysis
This is the second course I've taken with NYC Data Science Academy, they continue to offer excellent courses and materials.
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Lee S-K
Data Analysis and Visualization
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I really enjoyed the Data Analysis and Visualization course. I took the Intro to Python class with Tony a couple months ago, and this course (also taught by him) was a great next step in my journey towards hopefully becoming an expert in Python. Whereas the first course gave us a great background in the basics, this one gave us a more concentrated ability to apply what we had learned to real-world problems (analyzing data and being able to display the results, which is more what you would do in a work environment). Also, the opportunity to put together our own project at the end of the coures is extremely useful. Highly recommend this course!
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Raj Atri
Great Intro to Python
I've taken both the introductory and Data Science course with Tony and it's been an incredibly effective and fruitful introduction to coding. I'm at the point now where I am working on a different project with python everyday and am greatly looking forward to the next class i will be taking.
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Deekshita Amaravadi
Introduction to Deep Learning
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I took the Deep Learning Course from July - August 2018. This is a part time course for 5 weekends. Jon Krohn is an amazing instructor. I am a Web Engineer and have zero to little idea about Deep learning. For me to sit in class and not be intimidated by the course and fundamentals of Deep learning is a testament to Jon's teaching. The course is a really good starter kit for anyone looking to get into Deep Learning and AI in general. There is some knowledge of python that might be useful to have prior to taking this course as there are many live exercises worked on python. You will be given an opportunity to complete a project during the course which I suggest you do as it will make you apply the skills you review right after class that will make learning the concepts more enjoyable. All in all, I will 100% recommend this course for anyone who is looking to get a thorough overview of the fundamentals and philosophy of Deep Learning and its future.
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Lee S-K
Intro to Python
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The Intro to Python course was great! Tony is a fantastic teacher who really took the time to get us acquainted with a new programming language, while simultaneously making the course challenging through both the in-class exercises and the homework assignments. I felt the course was especially well structured, as each part really built on top of the last to provide us with a clear understanding of the basics of Python. I highly recommend this course to anyone interested in starting on a path towards Python fluency.
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Raajiv R
Good course, instructor and environment
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I did not have experience in programming before this course. Had taken some courses in Java and pearl almost 9 years ago. I have a healthcare background and I was worried if this course will be advanced for an entry level. I can say now with confidence that this course not only taught me the basics of python and data analysis but also established a foundation to which I will be able to add advanced concepts in the future. I like the way the course was structured. Tony was punctual and the class always started on time. Tony encouraged us asking questions and was patient in explaining the concepts. Overall very happy with my decision to take this course and would recommend to anyone who is ooking to jump into the field of datascience.
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Vera Feng
Great introduction to Python
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As a Math major interested in Data Science, I've benefited tremendously from this course. Tony is a structured, detailed instructor. The course materials are practical and handy; and the lectures were helpful in both understanding the materials and honing up a programming mindset. I walk away from this class, feeling ready for challenges in my future job. I would strongly recommend this course with Tony to anyone who is new to programming and wants to have a head start.
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Dean Goldman
Amazing experience and job training
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I could not be more satisfied with my experience at NYC Data Science Academy. I met incredibly impressive and interesting people, learned more than I ever thought I could, made friends, and worked very hard. Within a few weeks after graduating, I was offered my first full-time job as a data engineer. (I do not come from a CS, math or stats background).
NYCDSA is very succesful at getting their students fluent in the tools and technologies of data science, and prepared for finding great jobs in the field. The bootcamp is exhilerating, and the people are truly the best. By the end, you will be ready to for a data science position, and you will have broadened your horizons.
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Lakshmi Prabha Sudharsanom
The most supportive team
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I took the 12-weeks bootcamp at the NYC Data Science Academy. I am a postdoc in India. I had been writing graph algorithms for social network analysis and analyzing data using MS-Excel. I decided to extend myself to data science from data analysis.
I researched for about six months to choose a proper academy to learn data science. I came up with a decision to join NYC Data Science Academy, because I can learn both R and Python within three months. But, I learnt more than I thought. I gained hands-on experience in Python, R, SQL, Spark, deep learning, Hadoop and Hive.
The materials are technically sound for job interviews. Many experienced professors and industry professionals design and teach the materials. The course laid a solid foundation in data science. The people in the academy show keen interest in every student to understand the concept, in resume writing and above all, to get a job.
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Yisong Tao
Very fulfilling bootcamp experience
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I attended the 12-week boot-camp at NYC Data Science Academy from Sep. 2016 to Dec. 2016. Before that I got my PhD in Chemistry and worked 6 years' as a Post-doc in biochemistry.
The curriculum was well organized. 12-week courses covered R and Python programming, statistical analysis and machine learning. During the last few weeks, big data tools like Hadoop and Spark were also covered. For one coming from academic background, the breadth of topics and difficulty level felt just right. The boot-camp courses weren't supposed to teach you everything, but they did prepare me very well if I wanted to explore further data science topics.
The boot-camp was intense. I was only sleeping for 4 hours during boot-camp days. It was demanding both physically and mentally, but I wasn't alone in the journey. The instructors, TAs and classmates were all amazing. This boot-camp takes students from very different backgrounds, which I think is a unique advantage. I was able to see people applying data science tools to their own expertise brilliantly, fashion, marketing, IT, health care... It was very helpful for me who was looking to step outside of academia.
The job assistance is good. There is networking, resume-editing and mock-interviews. Vivian also personally helps students tracking their job hunting status. I wasn't able to use lots of their services due to my personal situation, but for the one position I applied for I was able to impress the hiring manager with the machine learning knowledge and skills I acquired at NYCDSA and got an offer the same day.
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Chris
Great class!
Great class. The instructor did a great job of keeping us on track and packing a lot of content into 20 hours.
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Mustafa Koroglu
A comprehensive data science bootcamp with full team support
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The motivation in attending a data science bootcamp generally starts with reading testimonials, which are the experiences and thoughts of past fellows. I believe that my experience as a remote participant in the Summer 2017 bootcamp is unique as the NYC Data Science Academy made it live stream to me throughout the bootcamp. This is totally different experience than doing bootcamp online as I was able to join lectures, industry expert speaker sessions, and workshops as the fellows did in person. This was indeed great opportunity for me as I was able to ask my questions during the lectures and seminars and participated actively with my comments. The crucial point here is that live streaming the bootcamp and communicating through Slack channel made it possible for the team at the Academy to track my progress in the assignments and projects daily and encouraged me to participate fully in the bootcamp. I can definitely say that attending the NYC Data Science Academy bootcamp was one of the greatest investments in my life. I learnt how to code efficiently in R and learnt coding in Python with real life projects. I am hundred percent sure that my attendance to the bootcamp let me to find my current data science related post doctoral position. I could suggest future candidates to take some initial online courses for machine learning and deep learning, where they will find themselves more comfortable while approaching highly-technical projects in the bootcamp. One of the strongest side of this bootcamp at the NYC Data Science Academy is the time and effort that the hiring team spends on. For remote participants, this is much more valuable than any other thing as you are receiving constant help in finding best job depending on your portfolio. And you feel that you are a member of an excellent group of data scientist. As an active learner of data science field, I recommend the NYC Data Science Academy with full of confidence. -
Al Mercado
Part Time Deep Learning- Just Do It
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The approach in this course was more different that what I've seen in most workshops on this topic. It was more visual because Deep Learning sometimes requires mathematical derivations to understand the algorithms. I have read a few seminal Google papers on the topic and they're not alwasys easy to follow. John did not dive too much into this area and preferred to use powerpoint slides and diagrams by hand to explian it before we looked at the code.
Overall the coding portion was made easier by John's coding style and we were able to follow along with the Keras modules. However, we did not get to cover all the topics (like autoencoders or deep belief networks) that I've seen other presentations get into and I would have liked to learn more. But the foucs on NLP and the last topic on GAN got me more curious about those topics. I would recommend it to those who want to learn it more and I would even be willing to talk about what I tried as a result of taking the course in any future session that he runs with a new group.
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Former Alumni from Cohort 003
Life Changing Experience and Phenomenal Ongoing Support
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I was previously a student in one of the early cohorts of for the 12-Week Data Science Boot Camp, and it was one of the best experiences for my career.
Before going into lengthy detail, I will break this up into three sections: Before, During, and After in the hope of conveying a more comprehensive experience.
Before:
Before attending the NYCDSA, I had just finished my undergraduate degree in an engineering field. After taking an Intro ML course my senior year, I grew increasingly interested in the applications of AI and Machine Learning in industry. When I discovered the field of data science, I was instantly hooked, but I knew I needed to learn more.
I had a decent amount of programming experience, mostly with low-level languages and systems, but lacked statistical intuition and experience with scripting langauges. After some more digging, I knew that my skillset at the time would not be competitive for the actual job market. While my undergraduate education was excellent, the curriculum was reasonably classic, most of my courses focused on theory and textbook problems and what I lacked was skills and experience for real-world applications. While graduate school was an option, at the time I wasn't sure if Data Science was a field I wanted to commit more formal education to without experiencing it first hand. So after applying to various boot camps, I chose the NYCDSA to jumpstart my career.
The interviewing process for the NYCDSA was simple and effective and included phone screens, code exercises, and some Q&A. I chose this program because the company was relatively new and small and felt more like a community rather than a factory to churn out data scientists like other boot camps I came across. After making my decision, I promptly moved to NYC after graduating and began my journey into data science.
During:
The company was relatively new at the time I attended, but the caliber and experience of their faculty were top-notch, and it was transparent how passionate the staff was about developing the best and most efficient curriculum. Within another couple of years, they were able to scale up, expand, and further improve their curriculum and course content at an exponential rate.
It is important to note that your mileage may vary with any boot camp. This program offers awesome resources, but ultimately it's up to the student to determine how much he or she will get out of it. I spent an average of 60~90 hours a week on campus for the 12-week program. The course is still manageable for people who have families or other commitments, and I have seen many successful part-time students graduate from my cohort. I just wanted to note that this was particular to my experience.
The curriculum covers various aspects of data science and offers a cutting-edge foundational overview of stats, machine learning, and programming. The core languages are R and Python. The philosophy of spreading the breadth of languages rather than just choosing one is reflective of the fact that the tools in Data Science are highly mutable. Rather than memorizing a single programming paradigm, the goal is to expand your programmatic and discrete logic intuition so that you can pick up other languages if needed.
After class, the projects were engaging, and it was enjoyable to engage with other data enthusiasts and attend data science meetups and conferences together. I still keep in touch with many of my cohort mates years after the program.
Moreover, Vivian and company have a robust network of many NYC companies and quickly expanding to other areas of the country. By the 9th week, I've already had a couple of interviews lined up at top firms in the area and was able to practice and refine my onsite interviewing skills.
Three months after the boot camp, I landed my dream first job at a fast-growing tech-startup in Chicago after receiving multiple offers.
After:
After landing my role as a Data Scientist, I still maintained a close relationship with the NYCDSA.
The support of the NYCDSA does not terminate at the end of the cohort, and they do a phenomenal job of providing ongoing support for their alumni and students. After the boot camp, I've continued to receive ongoing help (practice interviews, coding exercises, access to review course content, network events, resume editing) which were crucial to my future employment.
Not only do they offer support for students seeking employment but they provide support for education as well. I was actively interested in an advanced degree in a field that leverages machine learning, and my experience at the boot camp only affirmed this for me. Many of the faculty come from incredible backgrounds and are very willing to share their experiences. Their advice and transparency were constructive in my choice of graduate program. Currently, I am a part-time Masters candidate at a top data science program with a focus on Machine Learning and Data Ethics while working full-time as a data scientist at my current company.
The skills that I learned from the NYCDSA and later refined at my current company significantly prepared me for my graduate courses, allowing me to test out of basic classes and attend advanced topics in machine learning and statistics. The skills from the boot camp carry over very well for most data science roles or education programs.
In short, what I wish to convey is that a career in data science is a journey of continual learning and NYCDSA does everything they can to optimize the learning experience for their students.
However, please note that the Data Science Bootcamp is tailored to provide balanced curriculum among programming, stats, and machine learning and is meant to be a program to strengthen core skillsets rather than a masterclass for already experienced data science veterans. Although the company does offer more specialized classes in more targeted areas.
If you are looking for a program that will teach you everything there is to know about data science within a mere few months, then I'm afraid that those may be in general hard to find since data science itself is both a hybrid of multiple subjects and growing as a professional field.
On the other hand, if you are serious about transitioning into data science as a career and if you are seeking a program that offers competitive curriculum, a strong alumni network, and a community of data enthusiasts to engage with, I would strongly recommend looking into this program to jumpstart your career. I cannot emphasize enough how much this program has benefitted my professional development both during and after the boot camp.
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Kathryn Bryant
Best career decision I've ever made
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Attending the NYCDSA 12-week bootcamp is the best career decision I've ever made. I came to it after finishing my PhD in math and working for a year in academia. I wanted to get into data science for lots of reasons (leveraging my background, interesting problems, ample job opportunities, interest in coding, good pay, etc.) but after spending six years in graduate school, the last thing I wanted to do was go back to school for two years to learn basic data science skills.
This program allowed me to do this career change quickly without compromising the quality of the material I learned. The program emphasizes sound foundations in coding in R and Python and in both the theory and application of machine learning. The pace is very fast but you learn and do an incredible amount in those 12 weeks. Even when full absorption of the material isn't possible, the bootcamp does a great job of exposing you to tools and concepts you'll need to be familiar with later.
The projects are incredibly valuable for building skills and exposing future employers to your work. You would be spending your money wisely just to come and complete the projects.
The bootcamp students and the TAs/instructors have varied backgrounds, which also makes for a great environment because you can learn from everyone. The entire company - from fellow students to TAs to instructors to the CTO and COO - is filled with smart, hardworking people who are pushing to help you reach your potential.
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W. Zhou
Great learning Experience help me land my dream job
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WHY Data Science and WHY NYCDSA: I had no idea about data science until 2016 Feb when Alphago defeated Li Shishi and it was the first time for me to get to know what is Artificial Intelligence and what is machine learning. Bringing my huge curiosity, I self-learnt an online Machine Learning course on Coursera and was able utilize the skill , for the first time, in my working project and had a positive outcome. Being proud of my achievement, I also realized there was still a long way down the road. This is actually the reason why I decided to join bootcamp - fully armed myself with comprehensive data science skillset and then shifting my career towards a new page. NYCDSA is a perfect choice for me as it teaches anything you need to know to work as junior data scientist and allows you to keep full time job as the same time.
Experience: Even though it is an part-time online bootcamp, I was investing 40+ hours / week on studying slides, having office hour with TA and doing projects with current full time students. The bootcamp starts with an introduction Toolkits (Unix,Git,SQL,etc.), followed by introduction to R/Python, then followed by statistics and machine learning immediately applied using R and Python. The comprehensive curriculum is completed by an introduction to Big Data tools. I was able to finish a strong portfolio with 4 projects in Shiny App, Web Scraping, Kaggle and Capstone. I learned a lot especially by collaborating with full time students and TAs, so I would strongly recommend those online students who are physically in NYC, walk in the classroom and collaborate with full-time students on your last two projects.
In terms of job assistance, NYCDSA can provide tremendous assistance on your job hunting after your graduation. Vivian and Chris know what you need to have on your resume to catch HR’s eye and get an interview, and they have a strong network which can expose you to much more opportunities.
Outcome: I finally received offer from 2 Top insurance companies, 2 Top hospitals, and 2 boutique consulting companies. I feel my investment of 7 months of study and $16K totally worth as it allows me to finally launch my dream job. Thank you New York City Data Science Academy and I would recommend it to anyone who has same dream to be a data scientist.
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Andrew Rubino
A life changing decision, and a fulfilling journey.
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I came to New York City Data Science Academy because I wanted to become a better coder, to become more knowledgeable about machine learning, and to get a better job. Having completed the bootcamp in the Spring of 2017, I can say that through the Data Science Academy, I was able to accomplish all three.
Before the bootcamp
Previous to the bootcamp, I had a job as a data analyst which gave me the exposure SQL, Linux, Hadoop, and some Python - all tools that are taught in the academy. I knew I wanted to improve my overall problem solving approach, specifically using Python and R. After a few years as an analyst, and many months of debating if enrolling in a machine learning bootcamp was worth the time and money, I decided to go for it. Although I do not have a masters degree like many of my fellow cohort members, I knew that I could use my work experience to my advantage in preparing for the bootcamp. Like many others have stated, giving yourself enough time to go over the 100+ hours of prep work before the bootcamp is highly advised - being able to perform the basics of Python and R will set you up for success.
Preparing before the bootcamp is also crucial in another way. As you spend more time studying, you spend less time doing all the other normal things you’re used to doing in your life. In order to make the most out of the bootcamp, sacrifices must be made, from your social life, to your eating and sleeping habits, and to the amount of coffee you normally drink. If you don’t get used to it before, adjusting to these changes midway through the bootcamp can be a challenge.
During the bootcamp.
If you spend enough time preparing before the start of the bootcamp, then the first month or so should not be too challenging (but still very useful). Many of my fellow cohorts actually became nervous, thinking that our investment in the bootcamp might not have been worth it. Don’t fret. After going over the basics again, the fun truly begins.
After the first month, you will spend every day learning machine learning concepts, applications, statistics, and then applying these techniques in both Python and R. This is no easy task in a few short months, which is why the instructors, teaching assistants, and Vivian, deserve so much credit in churning out so many qualified data scientists in such short time. The instructors are always, at all times, helping and guiding you in the right direction. On top of that, you have the additional resource of working with your fellow cohort members, all who have unique backgrounds and always willing to help.
In the end, the journey would not be worth it without days of extreme struggle and frustration. Some days I felt really confident in the material, other days I did not think I had what it takes to be successful. What I believe the instructors are best at is instilling the confidence in each and every student, spending as much time with you as needed to successfully complete the projects.
The last few weeks are spent on tidying up your resume, github, blog posts, and interview skills. Aside from learning both R and Python in the bootcamp, one of the reasons why I chose the Data Science Academy was because of the strong professional connections that Vivian and the team have developed over time. The final day is dedicated to a networking event, where the ratio of companies to students is almost 1 to 1. Although it can be a bit nerve wracking, Vivian and the team do a good job of preparing you on what to expect.
After the bootcamp
I was lucky enough to land an internship at a startup as a data science intern from one of the participating companies at our networking event. I have to give my experience to the bootcamp all the credit for this. Had I not had relevant experience and projects to speak of, I would not have been able to land the job. As my internship was coming to an end, I spent more time with Vivian and the team doing mock interviews, going over practice questions, asking for help on take home assignments, and constantly reviewing. Without a doubt, I can say that the three months of the bootcamp was the second hardest thing I’ve ever done - the first hardest thing was getting a job afterwards.
Vivian and the instructors have the uncanny ability of knowing what specific skills you need to improve on, based on constant back and forth communication based off of past interviews, as well as the interviews you eventually take. You will fail, and fail a lot. Most data science interviews are designed to test you on the very limit of your knowledge on data science subjects. With practice, you will answer the questions confidently, and even if you are unsure of a question, you will be able to communicate a thorough data science process on how you think the question could be answered. If you fail an interview, it’s another lesson on how to improve for your next interview, which Vivian will most likely have helped you set up already.
After months and months of dedicating my life to all data science related activities, I have landed a job as a data lead at a media company, and have the entire NYC Data Science Academy program to thank for it. If you are seriously considering a future career in data science, then I can 100% vouch for the academy, so long as you are ready to work harder than you have ever worked in your entire life. At the end of the day, it’s all worth it.
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Shivakumar Ranganathan
Summer Bootcamp at NYCDSA
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Machine Learning is transforming the world at an incredible pace and I felt it was imperative for me to acquire new skills in order to be professionally relevant. The summer bootcamp fit my schedule perfectly and I decided to enroll to better understand this exciting new field. With a PhD in Engineering from a top-five ranked school and significant background in Computational Materials Science, I felt that I had sufficient background to be successful in the bootcamp. Due to my hectic schedule, I was unable to complete all the pre-work prior to the bootcamp and I believe that this had an impact in my learning experience at the later stages of the bootcamp. In my opinion, pre-work is analogous to binary decision trees—you are trained to be independent weak learners ahead of the bootcamp. The actual bootcamp is more like a random forest where individual students work alongside other students as well as Teaching Assistants and Course Instructors to significantly contribute on a variety of real world projects related to Data Visualization, Web Scraping, Machine Learning and Big Data. The course is fast paced and students are exposed to a variety of technologies relevant to Data Science. The instructors are knowledgeable and fellow students in the cohort are sharp. It is not surprising that NYC Data Science Academy is one of SwitchUp’s Top Bootcamps of 2017. I strongly recommend this bootcamp to individuals who are seriously interested to pursue a full-time career in Data Science.
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Samriddhi Shakya
NYC Data Science Academy BootCamp - 6th Cohort
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Going to NYCDSA is one of the best decisions I’ve ever made. Data science was completely new to me and I didn’t have a vey good programming background. At NYCDSA, i was able to master both my data science and programming skills with the help of ever-present instructors, TA’s and friendly classmates. The curriculum was well balanced with all important data science topics, lab practices and mandatory individual projects included. In addition, they also had weekly coding challenges and professional development courses which teaches you how to deal with interviews and present your self in the real world. The three months program was intense but is doable if you put in effort and dedication. After the course, the academy also help you with your resumes and get interviews with companies within their connection. I highly recommend NYCDSA to all aspiring Data Scientist as this program helped me achieve my dream of becoming Data Scientist within 3 months after graduating.
Cheers NYCDSA -
Chris Lian
Worth the effort
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I am a recent NYCDSA graduate. Before the retrospect. The outcomes first: Know myself better, made great friends, landed a great job within 3 months, came back to the dream land……
My story is a little different. The pre-DSA career is not bad at all. I have had worked for a couple of top companies in the pharma and health industry for several years after getting my PhD. For some reasons, I am always thinking of expanding and tuning my fields. Life is quite dynamic that I recently moved to the east coast and happened to get stresses from various parts of the life. Rather than hanging there, I decided to challenge myself and make changes. I have thought of schools but it is not realistic for my situation. I have studied some bootcamps and visited NYCDSA last year. The people there were very kind and down to the earth. I was not too confident at first but I would like to give a try. Therefore I gave up what I was doing, which was pretty risky and got a lot of doubts from people around me.
But I always know very well and anyone should keep in mind that 3 months can hardly make one totally expert in data science, otherwise I will be willing to pay 10 times more. We should always keep learning; the effort will pay back.
The course designs are up to date. They focus on practical data science skills. The first month is about coding and analysis in R and python, which I found helpful in my case. After that, machine learnings have been emphasized on both python and R, then the big data part. Most of us are not directly from cs or math backgrounds. We had to work very hard for the classes in the morning, the homework at night and most importantly, the 4 projects with different emphases. We were pushed by the deadlines and harsh schedules, like the real world, have to come out the results before knowing everything. I was the humblest guy during the 3 months in my entire life J. The instructors are very kind, helpful and always there to help. During the process, I have made some great friends, knowing people from such diverse backgrounds and also know myself better. Although I got my job on my own search according to my specialized interests and desires. The NYCDSA tried its very best to connect alumni and companies for the hiring. They have great connections. There are many alumni get jobs from the network.
Suggestions and lessons: Once you have made the decision to attend the bootcamp, forget the past and dedicate yourself. Always focus, do not doubt your decision for one second or look back.
Skill is very important, but that’s not everything. Try to communicate, make friends and find out your strength well during the bootcamp. Design at least 2 of your 4 projects well, you know yourself the best, interact with the instructors frequently but do not solely rely on their ideas. Do not live far, I burned myself out on the long trip every day. For the projects, try to team up with members most accountable, fair and those with high integrity and work ethics. If you share the common interest, that’s even better. Do not judge others only by the technical or coding skills, it’s a teamwork, cultural fit is critical. Last but not the least, we do pay a lot and might give up what we already have for the bootcamp. But when you get the quick reward in life, these pains with hope are abosultely worth it.
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Dave L
Worth the investment
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I came to the NYCDSA after having spent several fruitless years on the academic job market with a Ph.D. in English. I was depressed and didn't really know where to redirect my career. I had a background in math and a strong enough interest in data, but I knew that I needed to skill up, because that no one was going to take me seriously without another credential.
Despite my unusual background, the NYCDSA was very welcoming and helped me get unstuck. I'm in a new, fulfilling career, and I couldn't have done it without this program. By the end of the first year in my current job, I'll recoup the investment with respect to my prior earning power.
The Good:
1. The cohort my term (and, I suspect, for most) is a really excellent mix of people. You have ex-academics, mid-career folks who are trying to reskill, fresh B.A.s who need to weaponize their math/CS skills; you have people from the sciences, from finance, from advertising; you have representatives of over half a dozen countries. They bring a variety of talents, and you learn a lot from seeing what problems they want to approach and how to approach them.
2. I've been in my current job about ten weeks, and I've already used most of the curriculum. I use R every day, Python frequently, and a fair amount of SQL and Mongo. Good BI visualization can really set you apart, so the early part of the course has been most valuable. I've already done a fair amount of scraping, too, and occasionally contributed on some machine learning. The only thing that would be useful for my job that the program didn't cover was JavaScript, but that's really more relevant to my field (advertising) than data science.
The Solid:
3. The instructors are all very committed. There's a lot to learn, and they work hard to see that you get it absorbed. I'm not wild about the setup pedagogically--three-hour lecture blocks make it easy to lose focus--and sometimes the instructors are not the easiest to follow as lecturers, but they put tons of work in, and it's appreciated.
Could Be Improved:
4. I know they try on job assistance--there's some work with resumes and interview prep, and they set up some interiews for you with their assorted hiring partners--but they don't seem to have the staff they need (at least as of my job run) to supervise it as well as they could. To give an example, they didn't have a dedicated placement officer when I was there. Job hunting is always terrible and unpredictable, but my impression is that some of the other camps (e.g., Insight) do a better job of minimizing the aimlessness and frustration it can incur.
Still, after three months in the program and three and half on the market, I got a job, and I wouldn't have done it without the academy. It was an important stage in my life, and I'm happy I made the decision to go in. It's let me move on with my life.
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Katie
Awesome experience- would recommend 100%
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What impressed me most about my experience at NYCDSA was that it exceeded all of the expectations I had from speaking with the instructors and researching the program online. The entire team truly went above and beyond and I have only positive things to say about the instructors, the curriculum, and the way the experience changed me personally.
I found the instructors at NYCDSA to be not only incredibly knowledgeable, but approachable, thoughtful teachers. They seemed to really care about each student’s development and regularly stayed late in the evenings to offer help. If they could not be present in person, the instructors were always an e-mail/Slack message away and made it a point to check in with students and offer additional resources. I also liked that they not only taught the theory behind machine learning algorithms, but explained their most common applications and pitfalls to watch out for.
The curriculum at NYCDSA is constantly updated to reflect the most valuable skills for the real world. I found during interviews that whenever I was asked whether I had experience with a certain data science technique or language, I could either say “yes” or show a project to demonstrate my skills directly. What I was taught always matched up with what was requested of me in the interviewing or working world. Even after the end of the bootcamp, I kept my slides and materials for review, and was provided with hundreds of interview questions to help me succeed going forward.
Most importantly, the NYCDSA provided an amazing support group and helped me transform myself during a critical point in time. The other students were dedicated, kind, and came from all different backgrounds. I learned a huge amount from them and the instructors about the process of learning a skill like data science/programming and collaborating successfully. Apart from teaching the curriculum, instructors also provided resume reviews, listened to elevator pitches, and made themselves available to discuss interview experiences. I felt as though I had a whole village behind me, rooting for my success.
I would without a doubt recommend NYCDSA to any friends or colleagues looking to learn data science. It was an exceptional experience and I feel grateful to have found it.
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Yabin Fan
Life changing experience
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I would highly recommend anyone who wants to switch career to data science or strengthen data science knowledge to apply NYC Data Science Academy.
Before I joined the Boot camp, two of my close friends already graduated from the program and landed their dream jobs. So unlike most of people who don’t know too much about this program and have to do some research before applying it, I applied the program without a hesitation and also had a high expectation as well.
The curriculum design was excellent and really taught you how to learn new tech skills, frameworks quickly. It could be hard for people who are not exposed to programming or statistics to keep up the pace. Make sure to go through all the pre work and learn basic statistics before attending the boot camp. Once you started to work on your final project, you will notice that you’ve learned so much.
All the instructors are very talented and very patient to students.
Vivian and Chris work hard to help you to find a good job once you’ve graduated. After you graduate, NYCDSA sticks with you. Vivian and Claire emailed us frequently with new job opportunities and openings.
It’s not going to be easy. You will have nights you have to stay up to finish the project, missed parties that you don’t have time to attend to. But it will be worth it! The knowledge that I’ve learned in 3 months are way more than my two years master degree and I got my dream job too.
I’ve never regretted to attend NYC Data Science Academy. I’ve met so many amazing friends in the boot camp. It’s a very valuable experience to me in terms of career development and personal growth as well.
If you are passionate about data science and big data and you are willing to put hard work to achieve the goal in a short time of period, there is no better place than NYC Data Science Academy to learn data science skills.
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Andrew
liberal arts to data scientist
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I went into the bootcamp with little more than a liberal arts B.A. and some online self-training. Within 6 months of finishing the bootcamp, I received multiple job offers and landed a dream job on the strength of my data science skills. The employer found me through the NYC Data Sceince Academy job network-- in that sense, the Academy continued paying dividends well after I had finished.
It is hard. When I read reviews that speak negatively the program, I suspect that they are from students who didn't put in the work themselves to take the many learning and job opportunities that NYC DSA provides. If you are willing to devote your time and effort to developing a new skill, you will be rewarded by this program.
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Mark Schott
Quality and open bootcamp that helped me find a job
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The NYC Data Science Academy 12 week in-person DS bootcamp will give you quality instructional resources, project experience, and beneficial job support. In 12 weeks I was able to learn a vast amount about the field, and gain the momentum necessary to secure a position 2 months after I finished. I greatly enjoyed the intense intellectual environment, as well as the comradery with my fellow students. The instructors, TA’s, and management are approachable and receptive to your needs, as long as you pester them. The bootcamp was not perfect, but I was highly satisfied with my experience, and it was worth the cost. It definitely accelerated my skill set and allowed me to gain experience, while making friends in the process.
The curriculum has great breadth ranging from fundamental statistics, to carrying out end-to-end analyses in both Python and R, to covering big data tools. The breadth and 12 week time constraint meant that depth was sometimes lacking, but this was reasonable. It just means that you pay more attention to the subjects you're interested in or where your time would be well spent. For example, I am not very interested in NLP, so I didn't devote much energy there, and instead focused on time-series analyses.
The instructors are all very knowledgeable, and passionate in their respective sub-areas of expertise. They were the real deal. The only drawback was that some of the lectures were hard to follow, but it was not hard to get clarification from the instructor or a fellow student.
The bootcamp structure is open and approachable. Everyone is on the same floor in midtown Manhattan. Feedback is encouraged, and I really appreciated the opportunity to talk to the people who were in control of things, and who could help guide me in the right direction. This openness was a huge plus in my experience.
The job support was pretty solid and consistent. I got some interviews from the hiring event, and the door was open for any job-seeking advice I had along the way. New opportunities were pushed in my direction, and I was frequently reminded to stay sharp with my skills. To help with this post-program training material was provided.
A drawback of the program is that seeking out the help you need was harder than it should have been. As a student you were expected to seek out the help you need. This is fair, but it would have been nice to be challenged a bit more in the curriculum, for example with more mini-DS case studies. Another issue was that It was difficult to get feedback on projects. I think support with projects over the whole process could have been better. On the other hand, you get to choose your own project topics, and you will learn by doing. Also, there is continuing support after the bootcamp has ended until you find a job at the least. You also have a place to come sutdy even after the bootcamp is done.
All in all, go down and talk to them if you have any doubts. Talk to the students, teachers, and anyone else you can find. I think if you love to learn, and you are proactive about seeking out the help you need, then this bootcamp will help you learn a ton in a short amount of time.
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Jessie
Opened up a new world for me! Highly recommended!
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How I started
When I started getting interested in data science, I was looking for any online courses/ bootcamp to help me get into the data science world. And I found out NYC Data Science Academy was the best out of all the data science bootcamps in terms of curriculum, and after talked to Claire and Vivian about how they helped students to locate job after the bootcamp, I decided to apply for the full-time bootcamp.
Preapre for the full-time bootcamp-Prework
After I got admitted, I got access to the online prework courses (Python and R introductory courses). I really love how they organized each video and there are exercises following with each part in the video. I didn't know anything about R and Python before, and the pre-work assignments are overlaped with the content of the first 4 weeks of bootcamp, so it helped me to adapt to the speed of the class in the bootcamp.
12-Week Full-Time BOOTCMAP
The bootcamp was very intense, the curriculum was comprehensive, which covered from data anlysis, machine learning in both Python and R, and introduction to Big Data tools. We also did 4 different projects, which was important especially when it comes to job hunting.
I didn't look for full-time data science jobs after the bootcamp because I got admission to the master program at Columbia University, and thanks to my experience at NYC Data Science Academy, I can handle the programming and data work in my current courses and projects.
And I still receive ongoing career support from the team and chat with instructors and students time from time now. It was so nice to work with all these hard-working and passinate people in the data science world. 100% RECOMMENDED
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Cristina
A great gateway to the world of data science
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The 12-week data science bootcamp is a highly useful experience both for people looking to transition into data science and those who seek to expand their skills set in their current field. A core dimension of the program is exposing and drilling you in a range of technologies that are very sought after on the market for data scientist/data analyst/quantitative analyst positions, spanning fields from tech, finance, healthcare, marketing, research etc. On this front, a distinguishing feature of the bootcamp is that you work in both either R and Python as primary languages, so that you become proficient in both languages by the end of the bootcamp, which is very valuable. Besides these languages, the bootcamp also teaches staples of database, file management and version control like bash, git, SQL (MySQL, SQLite) and MongoDB as well as in demand big data tools like Spark, Hive, Hadoop, AWS, etc. This is a very powerful set of tools to have under your belt. Certainly, the more familiar you are with these technologies before joining the bootcamp, and the more intense effort you are willing to put into practicing these skills, the more you will be able to get out of the experience, and you must be prepared to absorb new technologies very fast, but at the bootcamp, you get a structured and very supportive environment to help you achieve this. The TAs are excellent, very dedicated, and willing to assist you with any question or problem you may have.
A second core dimension of the program is anchoring you in the mechanics of statistical inference, machine learning algorithms, and data mining. The curriculum is grounded in canonical texts in machine learning and is organized such that you get to cover a lot of ground in a short time. The concepts are explained very clearly, first from a mathematical perspective and then implemented step by step in both R and Python. The instructors have various specialties in which they teach, are extremely knowledgeable and can answer questions at any level of depth.
Tying these first two dimensions together are mostly daily problem sets and five projects, where you get to use the skills you are learning. For the projects, you can even go beyond, learning and adding a technology or skill that may not have been directly taught, if it serves your project. You will have ample support from the TAs and instructors through all this, and your classmates will make a very useful learning community. For the projects, it is helpful to give yourself plenty of time in advance to come up with ideas, but here again your TAs, instructors, and classmates will be very helpful sounding boards.
The third core pillar of the program is job search assistance. During the bootcamp there is a series of job search preparation lectures that include resume review, search and interview tips, interview type quizzes, and industry guest speakers. You will be encouraged, given many useful tips, and get motivated to become very disciplined and efficient in your approach. At the end of the bootcamp, each cohort is invited to a career event focused exclusively on the newly graduated cohort, with hiring managers from a diverse set of companies. You won’t be handheld, and you must apply discipline and commitment to your search, applications and preparation for interviews after the boot camp ends, but the job search assistance from the bootcamp will continue until you find a job, with the opportunity to interview with companies that hold interviews at the bootcamp, referrals to positions you’re applying through the frequent advertisements sent to alumni or to positions you apply on your own, a bank of practice interview questions, interview performance review, and an alumni dedicated place to come work on your search at the bootcamp headquarters available to all alumni.
The bootcamp is a very intense experience and you have to commit yourself to it 120% percent, but you will leave with a skill set that will advance your career, a set of projects and a certification that, in my experience, will attract many recruiters, the drive and inspiration to push yourself to reach your maximum potential, and a support network that will be there for as you pursue your professional dreams post-bootcamp. In addition, in my experience and that of several of my cohort classmates, both during and after the bootcamp, you will become an independent learner in the field of data science who is capable to advance and add to their skill set on their own. This is an invaluable skill in any data-related role you will hold. In sum, the bootcamp is a highly valuable experience that will leave a very positive impact on your professional life. I am very grateful I made this choice and I can only wholeheartedly recommend it to everyone else.
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Wann-Jiiun Ma
Online Data Science Bootcamp Review
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I was a postdoc at Duke University (Engineering) and my background is control and optimization. I participated NYCDSA Online Data Science Program (10/2016 - 02/2017).
NYCDSA online video lectures have a very high quality. I found that the well-organized class material and lecture notes very helpful to prepare for data scientist job interviews. I can review the material repeatedly until I am ready for the interviews. Also, almost everything I need to pass a data scientist job interview is covered in the program, which can certainly facilitate my interview preparation.
Finally, Vivian and the entire NYCDSA team are extremely helpful for data scientist job searching. From resume/cover letter revision, coding practice, to data scientist technical interview preparation, NYCDSA has enabled me to make a smooth transition from academia to industry.
I found a job at Citibank as a Fraud Data Scientist. Without NYCDSA online program, I would have to spend much more time to find the right direction to achieve what I have been able to accomplish through this online program.
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Chris V.
A Step Up & A Step Ahead
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I can’t begin to describe how inclusive, rigorous, and rewarding is New York City Data Science Academy’s Data Science Boot Camp. It is inclusive in the sense that those applicants it admits are not exclusively from among statisticians, mathematicians, and computer scientists. Professionals from other disciplines who recognize and appreciate the importance of a more structured, quantitative approach to business comprise a significant component of each boot camp cycle, providing context, breadth of experience, and real-world application to the data science discipline. In turn, they benefit from the experience and capabilities of their classmates specializing in more technical disciplines. The boot camp program is rigorous in that it demands broad competence not just in a single language. While competing programs may focus exclusively on developing competence narrowly in R or Python, the NYCDSA boot camp demands that its recruits master both. This gives those who complete the program greater flexibility, as they can appreciate the strengths of each language and invoke one or the other as best suits the task at hand. Apart from the new skills obtained, the NYCDSA boot camp is rewarding in other key respects. The curriculum is grounded in teamwork, giving participants a greater appreciation of how to build and manage teams in a business context. This team-based approach also fosters friendships among classmates who, as in a military boot camp, become battle buddies as they overcome the significant business and technical challenges they confront. The resulting camaraderie produces a very strong alumni support network that provides boot camp graduates with long-term opportunities for professional growth and advancement. The NYCDSA boot camp provided me with the precise set of skills I sought, allowing me to continue my career on a higher plane and enrich the value I provide to my clients in their pursuit of market share and increased profits. I am incredibly grateful and appreciative of the opportunities which NYCDSA’s boot camp has afforded me, both personally and professionally. -
Eli Raymond
Great Experience
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I took the Part Time Into to Data Science with Python class as a means of hands on introduction to some of the more common and powerful Python libraries used for data science, and I found it to be perfect for that. This is certainly not as rigorous as a bootcamp, but if what you're looking for is an introduction or even something to supplement learning on your own time, I highly recommend it. I would definitely say I am now comfortably proficient with the basics of each library covered and I have a great foundation I can build upon.
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Reza
Great way to learn python
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I took the Intro to Python and Python for Data Analysis/Viz courses. I came in not knowing much about python but came away knowing how the syntax and how I can use python for my job. I took both classes with Tony and he was great at explaining the nuances of the program without getting us lost in the unecessary details.
I would recommend taking these classes if you want to learn python while also being introduced to aspects of data science and analysis.
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Annie
Terrible - Stay away if online
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I will strongly advice not to take up online for the 12 week data science bootcamp offered by NYC data science. It is not worth the money you pay. It is better to do an MS with the same amount. Reasons
1. Lectures are unprofessional. Just plain text and not much plots or anything to really explain things
2. Instructors are just there to read the slides aloud and nothing more. The machine learning lectures and slides are just terrible. It is better to take up interactive tutorials such as datacamp than to review this. There has been no change or improvement from the school having brought this up.
3. Teaching assistants provided are not very knowledgable. They are just there to review your project. You are really lost when you have to ask them a question
4. Online is a big mistake because you are not learning anything significant other than what is being taught as there is less interaction with other students.
5. Projects are just namesake.
I will remind you - DO NOT TAKE UP ONLINE FOR THIS BOOTCAMP. 16K IS A HUGE AMOUNT
If only I could turn back time and run with my 16k.
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JC
Great way to jumpstart your career in data
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This is a highly intensive program with immediate returns. If you want to turbocharge your career progression in the world of data analytics, this is without a doubt the best decision you can make. However, this isn't a free pass into the field of data science; if you do not have the passion or are not willing to put in the work, it will be a waste of your time and money.
Prior to enrolling in this program, my major consideration was: If I skip the program and use the free resources online, would I be able to learn this stuff on my own?
Naturally, this was the path I initially pursued. But with a full time job, even if you put 2 hours aside each day to learn on your own, there will be days where you are too drained and lack motivation. Leaving my employer and investing in this program kept my accountability up and allowed me to gain new skills in 12 weeks that would have otherwise taken months or years of consecutive study. The content in the program is not secret sauce. Things you learn here can be found for free online. But in this generation, what can't be found for free online? Where this program shines is the extremely bright instructors and peers that you get to interact with on a daily basis. There were countless times during the lectures in machine learning where I was lost. If this was a MOOC, I would probably be replaying the video for the 7th time and then hopelessly closing the tab. At NYCDSA, you have access to some of the most talented and extremely patient resources (with the credentials to back it up) to help you until you understand what's going on.
The instructors are there for your to utilize, but you need to take action on your own. If you get the instructors engaged, their passion for data science is very contagious, and you will learn a lot just by bouncing ideas off each other and actively problem solving. This will be extremely advantageous for your projects. Please don't sit idle and let the instructors debug your code, you will learn nothing except how to press ctrl + enter.
In regards to job assistance, NYCDSA is a great way to expand and grow your network. Vivian and Chris both have deep connections to the data science employers in the NYC area. Although the company I am now employed at wasn't a result of the school's networking, I have gotten many interviews and employers reaching out to me solely due to Vivian and Chris. At the end of the day, getting a job requires putting in the work. Do not expect to come out of the program with employers throwing themselves at you for simply having NYCDSA on your resume.
Vivian and Chris provide great support to help you improve your job search experience, but they will not baby you. There are 40+ students they need to support. If you need help your best bet is to reach out instead of waiting around for Viv and Chris to ask you if you're okay.
My overall rating is 4 stars due to the course pacing. Whether this was an effect of too many/ too diverse of a class, or change in instructor(s), There were a handful of lectures that went too far over the scheduled time. For some of the later lectures in the program, there was a pattern of discontinuation of lectures. This was difficult to manage especially if it occured over a weekend. For example, if a Friday lecture ran over time, it would carry over to the next morning session on Monday. I would have much rather prefered a continued lecture in the afternoon while the material was fresh in my head. Although this was my personal experience, rest assured that Vivian and Chris are constantly improving the student experience and something like this is probably already being worked on.
TL;DR: come in with a passion, put in the effort, there is much to be gained
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Kevin M
Solid Class
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This course was a solid intro to using python for simple data analysis projects. Tony was a great instructor - he was very thorough with his explanations and made sure that we got through all of the materials necessary for us to progress through the curriculum. My main knock on the class was how short it was - if you're thinking about taking this class, keep in mind that there are only 5 classes, so all of the material that needs to be covered is jam packed into each session. While we did end up covering everything as displayed on the curriculum, it's harder to remember everything that is densely packed into each class.
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Arjun Singh Yadav
12 Week Bootcamp: It Changed My Life
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I am Data Scientist at Anheuser Busch today and I am going to share my experience with finding the right school and struggle that I faced.
Search for Schools:
It was hard to choose the right school for Data Science just by being online, I had recently graduated as a robotics and automation engineer and all my programming skills were result of self-education, In late August I was selected for the Interview process at New York Data Science Academy and General Assembly.
I first came to New York Data Science academy and I was interviewed by one instructor and one Business person, I never met them after that day so I don’t remember their names now, they asked me a series of programming questions, pretty basics some were based on the online application I filled and later some on my knowledge of statistics, it seemed to go well but at the end of the interview I was rejected.
The reason was I was not ready for the bootcamp, they had previously seen other student promise that they can learn quickly but what ended up happening was they left the bootcamp in middle, I was upset cause I really wanted to do it, but I also knew I was in a hurry, they suggested to take it slow and come for next cohort so I will not just be able to survive the bootcamp but also learn and really take something valuable from the camp.
I later went to General Assembly and attended their interview and introductory session, they had a much larger location, also a big conference room, I really like the place, I was provided an instructor who gave me a brief understanding of the course and what it would feel like. A week later I had my interview with Lally M, I had filled and application online but I never answered any programming questions, Lally was very nice and asked me few general questions, and also gave me few advices but all and all she did not really bothered if I was ready for the cohert, at the end of the interview she said I can join this cohort.
Prework:
It’s obvious what I did next, I left the option of General Assembly and prepared on my own for next 3 months, I met Vivan personally In November she is the Co-founder of New York Data Science Academy, she gave me access to a online learning and testing platform which is called the prework for the bootcamp, it covered all the basics of Python and R.
During the Bootcamp:
My Bootcamp started on 09th January 2017, I felt very confident during the bootcamp, I remember Chris said on the very first day "There are very few things in life that will give you a chance to have absolute devotion", in the beginning we were introduced to all the subjects again for first week, so even if you did not do prework you would not suffer entirely but I would suggest do your prework well.
Things started to get serious as soon as second week finished and it did not stop after that, we had classes from 9:30 AM to 3:00-4:00 PM, after which there was homework at the end of each day, added to it we had to do our first project, also I had to study for the subjects I learnt in the class, also I had to keep my LinkedIn and resume up to date, also you better keep going to networking events, all in one day with you getting enough sleep and food to have the same energy the next day.
Curriculum:
1) Introduction to R and Python , Unix (which helps in big data part)
2) Machine Learning - (a) Importing Data (b) Foundation of statistical Methods (c) Missing value and Imputation (d) Simple Linear Regression (e) Multiple Linear Regression (f) Generalized Linear Model and kNN Model (g) Regularization and Cross Validation (e) Tree Models, Bagging , Boosting , Random Forest (f) SVM (g) Time Series Analysis (h) Cross-Validation (i) Bootstraping (j) Feature Selection (k) Regularizartion (l) Hyperperameter Tunning (m) SVM (n) Tree Models (o) Association Rule (p) Naive Bayes (q) Principal Component Analysis (r) Clustering (s) Unsupervised Learning (t) XGBOOST (u) Tensorflow (v) Netral Network (w) Concolutional Neural Nets.
3) Big Data - (a) Hadoop (b) pig (c) hive (d) nosql (e) Apache Spark (f) DATAiku(platform) (g) DataBricks(platform) (h) Virtual Environment - Docker.
Project:
1) Try to solve real life problems in your Projects, you will have the freedom to choose your projects, choose them wisely. I had a chance to do one of the Kaggle project, it helped me learn from some of the best Data Scientist in the world and if I did not understand something in any project, the teaching assistants came to rescue.
2) You will do 4 to 5 projects including Capstone, finish them well, do not leave any part mid way, submit your code on Github and you will be told to write blogs on the platform provided by the academy, write them well.
Job Assistence:
1) Mock Interview sessions - Coding Test, theory of Machine Learning Test.
2) Resume Writing Session - Resumen writing, cover letter, Job status sheets, email - cold warm, Meeting Letter, thank you notes.
3) General Prep Session - Photo Shoot, Linkedin, In house Meetups, In house video recording during project presentation.
4) Interviews - Hiring Event, Introduction to Employers, Referal.
The Bootcamp:
The bootcamp changed my life as I am no longer the same person I was before January, even though 50% students in my batch had a PhD, 46% had a Masters and many years of job experience, I was among the 4% Undergraduate category who luckily got here, but this played in my favour as I learnt a lot from my peers, I truly came out a Star in my own eyes, I would like to give the credit to Vivan and Chris as a host in my Ex Home, who were supportive at the end of each day, coming up to you and checking on you if you are still doing okay, the reason I finished all my projects in Flying colours was my Teaching Assistants, who stayed back every day till 7:00PM sometimes and came back in at 8:30 AM, yet managed to stay active on Slack during the night during, I would also like to thank my peers with who I learned many Industry Skills and Best Practices, during my group projects I was led by a Math PhD Mr. Domingos, who now works at google, I had a chance to grow enormously on his team.
At the end of the cohort we all graduate in flying colours, it was very emotional day, thank fully we all are still in touch, I strongly suggest to make meaningful relationships during the cohort, after the school, you constantly have doubts and questions, like after job interviews, during your projects in the company, your colleagues will help you understand and overcome these doubts.
After the cohort we had our official Hiring day just a week later on 5th April 2017, I managed to meet 12 - 15 different companies, out of which the one I had a heavy interest in was IBM (who would not). Later I got a referral from IBM and I am currently Interviewing as a Data Scientist for IBM advance Global Analytical Team. I was trained to crack these interviews and trained to speak and write during the bootcamp, so I would do pretty well. One more advice will be to take this week and go through all the lectures once again and not give in the temptation to rest or relax.
I got my offer after 15 days of the bootcamp but for many it can take few months. At the end I would say 3 months of bootcamp can only prepare you to understand the science behind the scenes and provide capacity to be a more analytical person, but to be a good Data Scientist, I still study everyday, learn about ongoing research and connect with knowlegeable people.
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Stefan Heinz
Comprehensive and demanding program teaches you all you need to know
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The 12-week Data Science Bootcamp offered by NYC Data Science Academy is a very intense but also very rewarding experience. It is very demanding and forces everyone to keep up at all times. That being said, I can only recommend taking the program if you want to become a data scientist. Here you'll learn all the skills you'll ever need for working in the field.
The bootcamp starts with an introduction to Unix and Git, followed by two weeks each of introduction to R and then Python, then followed by statistics and machine learning immediately applied using R and Python. The comprehensive curriculum is completed by an introduction to Big Data tools such as Hive, Pig, and Yarn, database programming (SQL, NoSQL) and various useful jump-start sessions such as Shiny, Knitr, Geo/Maps. Every lessons covers both theory and practice, here in terms of R and Python code using basic and well known datasets. From time to time, industry professionals and alumni drop by for guest lectures in the afternoon.
For questions concerning assigned homework, project work or just better understanding of the material, great TAs are at hand throughout day to help out every single student to make sure everyone gets the best out of the bootcamp.
Every cohort is a very heterogeneous group consisting of people of all kinds of backgrounds, from fresh graduates to senior managers and PhDs from all kinds of fields, all interested in learning everything they need to know about data science.
To make sure everybody will be able to apply their newly-learned skills in the foreseeable future in the real world, they also have sessions on how to get the job you want, covering all aspects from resume writing to actually meeting people looking for candidates at one of their networking events. Hiring assistance continues even after the bootcamp is finished.
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Xinyuan Wu
A Great Investment
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The 3-month study at NYC Data Science Academy was a wonderful experience. For me, I polished my R and Python skills, did 5 projects including web scraping and machine learning, and more importantly, developed strong connections with many great people. 3 month after graduation I was hired as a data scientist by a data research company in NYC.
The curriculum is well organized. We learned R and Python programming, statistical analysis and machine learning. During the last few weeks, big data tools like Hadoop and Spark was also covered. As a student coming from an academic background, I feel the classes taught by NYCDSA are pretty good. The knowledge covered in this class are broad and the difficulty feels just right. You can't expect to learn everything in 3 months, but the courses give you the ability to further explore any data science topic on your own. Both instructors and students are awesome in my cohort and I really learned a lot from them. The job assistance is good. In my opinion, the bootcamp have tried their best to help the students. There are network events, resume editing, and mock interview to help you prepare the job hunting. Vivian and Chris also arranged a few on-campus interviews, which were great chances for practice. It should be noted that the career transition into data science is not easy, and a 3-month study can't change your life. Only high-quality work, nonstop studying, and active networking can make this happen. -
A S
Misleading and Misguided
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Bottom line: the bootcamp is a swindle, cheat, and ripoff. Save yourself the frustration.
If I could turn back time, I would not have wasted $16,000+ on tuition and moving to NYC. My money would have been better spent at an accredited program. The whole operation seems glued together like a popsicle stick diorama...it was like a total free-for-all. No rules, structure, or guidance. The few rules in place were hardly ever enforced (homework deadlines? grading? feedback? none). We were left to fend for ourselves with barely any help. I learned more from other students who had previous experience than any of the instructors, most of whom listed on the website had nothing to do with the bootcamp at all. I agree with some of the other posters...Vivian will accept anyone to make a buck. Some people in my cohort had backgrounds so far from data science I wonder how they got accepted in the first place (fashion? what? ok...).
Claire Tu of NYC Data Science Academy
Marketing Manager
May 18, 2017
We’re sorry to hear that you didn’t have a productive bootcamp. The vast majority of the students who attended our bootcamps find them well organized, challenging and beneficial.
We pride ourselves on our well-designed structure, rigorous curriculum, and responsiveness to student’s feedback. Our program structure and curriculum were approved and regulated by BPSS (Bureau of Proprietary School Supervision) and NYCDSA is a licensed school. We are required by law to deliver the program based on our approved curriculum and to give students grades and clear instructions of the standards for passing. All of the course structure, schedules, and graduate requirement are shared with students from Day 1. Our daily schedule begins with a three-hour morning lecture, followed by afternoon student lab sessions, jumpstart sessions, project presentations, or guest speaker lectures. Each student has access to a team of 6-7 instructors and TAs for personalized instructional, project guidance, and feedback.
We are always open to alumni feedback, as our alumni are all proudly displayed on our alumni page with their available contact information. We have been constantly receiving positive reviews and feedback regarding the program operation and structure from our students. As quoting to one daily feedback from a student in the current cohort: “I'm very happy with how things have been going, am really appreciative of the time taken to put together a solid curriculum (excellent project topic selection so far) and especially to have customized the curriculum based on student feedback.”
In terms of acceptance standards: to ensure that students are fully prepared for the bootcamp, all students are required to complete prerequisite coursework, covering programming, data visualization, and over two hundred coding challenge questions from both R and Python. Additional recommended readings and lectures on calculus, linear algebra, and statistics are also provided. Students who didn’t meet the requirement or aren't a good fit will be asked to defer their enrollment.
We believe that education is about creating new opportunities, and it should not solely depend on one’s past education background. We trust in people's potential and have developed an intensive pre-work program to get non-technical people ready for the intensive bootcamp
The fashion background student that mentioned in the review got a Data Scientist position at a major ad agency within TWO months of graduation.
That being said, by the end of most recent graduated cohort, among 200 enrolled students, 77% of them hold a degree in STEM majors. Among the rest of 23% NON-STEM background students, 40% of them come from Economics major, 25% from Business and Finance, and 11% from a Marketing background. For the highest degrees enrolled student obtained, 28% holds a PhD’s, 38% Master’s, 5.2% MBA, and 28% Bachelor’s. Each cohort we have 32-36 students. The ratio of students to Instructor/TAs is 6:1.
We welcome every student to raise a concern on our daily feedback survey and weekly pulse check, and talk to our school officers and instructors. If you are a prospective student who wants to gain more insights about our program, we welcome you to read those reviews with a VALIDATED real name on Course Report or SwitchUp. Questions and inquiries about program offerings can be directed to admissions@nycdatascience.com.