NYC Data Science Academy

Am writing this review for students coming into the program as to know what they are signing up for. Firstly dont get biased by the Data Science hype there are tons of people flooding into the space from all directions. Secondly do serious research to... Read More know if you really are going to be able to recover the money and time spent.

Pros:
-Good structured course content
- You get to taste both R and Python

Cons:
- None of the teachers are experienced enough in Data Science field to be able to firstly give you in depth knowledge to be able to build the foundation in Data Science and nor can they give real time industry application knowledge. I heard there were good teachers but they left due to some conflict. Vivian and Aiko are the only teachers who have some knowledge but Vivian wont be teaching any of the class since she is busy with other stuff.
- Being a recent graduate and going through interview its not easy to land a job and its not NYC data science fault they try their best to get companies to come to hiring partner event but none of the companies hire and if they do very few. I would encourage students planning to join to ask for stats who get jobs after completing bootcamp and you would be surprised it not more than 20%.
- Reviews are biased so please do your research and ask all kinds of questions before you join.

I recently took the 5 week "data analysis and visualization with python" course with Dr Tony Schultz. The course starts with a quick review of main concepts in Python (data structures, functions, control flow, exceptions handling, etc) and then moves... Read More on to some more advanced topics such as classes, objects, inheritance, string operations, file handling and regular expressions. In week 3 and 4, Numpy and Pandas packages are explained in detail and finally the course concludes in week 5 with visualization packages matplotlib and seaborn. Tony is an amazing instructor. He re-wrote many of the materials used in this course to make sure all material are continuous and cohesive and easy to follow from beginning to the end. He is very approachable and easy to talk to (both in class and through email) and because he has used Python for many years to conduct his PhD thesis, has an excellent grasp of programming concepts in Python. I strongly recommend taking this course with Tony to anyone who wants to learn how to use Python to perform data analysis and create visualizations.

Well lets see, I basically went from the lowest rung on the ladder to a data scientist making 6 figures with multiple big name companies chasing me.

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

What you should know:

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

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

Job Hunt:

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

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

Overall:

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

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

I started working in the financial industry in 1998 and have had roles in IT spanning development and production support. I attended the NYC Data Science Academy bootcamp during a three month sabbatical from work and it was a worthwhile investment. I... Read More have gone back to work to a new and challenging role that allows me to apply my new found skills (such as data exploration, visualization, and analysis for decision making) as a production support manager for an ultra low latency and algorithmic trading platform at a top financial institution.

What did it take for me to achieve success at the bootcamp?

My three months at the academy was intense. I had a strong support system at home and at the school. My instructors and TAs were smart, caring and invested in my development every step of the way. Delivering on five different projects that stretch your knowledge of Data Science and Machine Learning fundamentals, Python and R programming, through daily classroom and homework practice was exhausting yet rewarding because you were not alone through the journey. As an early riser, the academy facilities were available to me starting at 7AM daily.

My advice for a strong finish.

I strongly advise that you complete the prep work provided by the academy by the time you start the bootcamp. The amount of work expected to be completed during the three-month journey is not an easy feat; however, the projects you are exposed to, the knowledge you gain and the practical experience you collect through individual and team projects is indispensable and can be quickly applied upon your return to work. Going into the bootcamp I felt uncomfortable thinking of myself as a potential Data Scientist. Leaving the bootcamp I am comfortable with the fundamentals of Data Science and the application of hypothesis testing to data problems. I am not a Data Science unicorn, hence, I rely on my new found strengths and maximize the talents within my team to investigate and find solutions to technical problems.

I studied mechanical engineering and physics for my undergrad at a top university and work in product management with a focus on search. I took this class to satisfy a personal interest in the subject matter and familiarize myself enough with the fundamentals... Read More of machine learning to be able to explore the field more deeply on my own. I was also motivated by a career interest: the subject matter is highly relevant to my domain, and I feel that developing an understanding of the concepts and how to deploy them myself will make me better at my job long-term. Prior to enrolling in the class, I spent roughly 8-10 hours learning R and felt sufficiently prepared (I had some previous programming experience).

In the end I was extremely happy with this class (Machine Learning in R on Saturdays, 8 hrs at a time). The curriculum and content were excellent, the instructor, Luke, was fantastic and the assignments were challenging and informative.

I felt the course did a really great job of driving home the core fundamentals of each subject with a focus on statistics, mathematical theory, derivations and best practices. We covered a LOT of material, yet the material had a lot of depth. I thought the sequencing of the subject matter was very well thought out as well. The class was demanding and had the caliber of a graduate-level course.

The course also struck a very nice balance between theory and implementation. After learning about a new model, we would immediately implement it in class using R on our own machines. Luke did a particularly great job at relating the implementation back to the concepts and teaching us how to interpret outcomes of our analyses (I can’t stress enough how important this latter point was for me). He has a really strong grasp of the subject matter, he’s very patient and responsive to questions, offers a lot of insightful commentary on the theory, implementations and best practices, and he cares about his students a lot. The homework assignments complement the class nicely as well, helping to drive home the methods taught in class and how to interpret your work.

If you’re interested in developing a strong understanding of the fundamentals of machine learning in a rigorous format, this class is for you. I also couldn’t recommend Luke as an instructor more. He’s awesome! I was also was very pleased with my choice of the R class. R reduces a lot of the friction in model implementation, which allowed me to focus on developing an understanding of the concepts and interpreting results.

1.12 weeks' course with machine learning, spark, hadoop helped me solve almost technical interview questions. Also introduce several latest and popular topic, such as NLP, Deeplearning (CNN) and tensor flow.

2. This bootcamp faces people with different... Read More backgrounds, who can choose between "how to use machine learning" and "how to implement the machine learning(more math). TAs helped a lot if you wanna learn more advanced level.

3. Chris and Vivian helped prepare resume and the interview practice, and the hiring partner event was very helpful to present myself to the hiring managers directly.

Great appreciate!

Took the weekend course for Machine Learning with R. Course was very helpful in helping me understand the basics of Machine Learning and different models. My instructor was Luke Lin. He was very helpful and would spend enough time covering each topic.... Read More He even took an additional class because he didn't want to rush through the material. Overall I am quite satisfied with the results. Would recommend Luke to anyone else who is interested to venture into Machine Learning field.

I took the DATA SCIENCE WITH PYTHON: DATA ANALYSIS AND VISUALIZATION (WEEKENDS), with Aiko Liu. It was a well-designed course that moved quickly through key concepts. While most of the examples are taught of the standard datasets, the concepts are easily... Read More transferable to your area of expertise/focus. I found the examples to be very helpful and the amount of ground covered impressive. Aiko was very responsive to my questions via email despite having a busy schedule. I have since transferred many of the skills learned in class to my job, streamlining many tasks in the process.

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

They provide as many helps as they can, but you have to be proactive and eager to learn to take everything in!

I took the DATA SCIENCE WITH PYTHON: DATA ANALYSIS AND VISUALIZATION (WEEKENDS), with Aiko Liu. Aiko is an excellent teacher, who taught methodically and progressively. The course was extremely well designed, and elevated my skilset by building my understanding... Read More step by step in a structured fashion. I would highly recommend the instructor and the class if you want to truly develop a solid foundation to build your skills on.