About NYC Data Science Academy
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NYC Data Science Academy is the only national accredited Data Science Bootcamp in the United States. We are also proud that we are the only bootcamp that teaches Python and R. The academy is well known for its industry project-oriented learning experience... Read More
- The only national accredited Data Science Bootcamp in the United States
The academy offers accredited data science and data analytic bootcamps in New York City and remotely online. The programs can be completed within 3 months, 4 months, and 6 months. In these programs, students learn beginner and intermediate levels of Data Science with Hadoop, Spark, Github, Docker, and SQL, as well as popular and useful Python and R packages like XgBoost, Caret, Dplyr, Ggplot2, Pandas, Scikit-learn, and more.
- Individual/ group projects showcased to hiring partners
Once the learning foundation has been set, students work on multiple projects through the Bootcamp. The program distinguishes itself by the breadth of its curriculum as well as by balancing intensive lectures with real-world project work. Students will work individually and with teams throughout the program to create at least four projects showcased to employers through multiple channels; private hiring partner events, student blogs, meetups, and film presentations.
- Lifetime Career Support
The academy also offers solid lifetime career support. There are four channels of engagement: Tech interview prep, unlimited mentorships, career services adviser who's forwarding your resume on your behalf, and a lifetime job portal. We also provide mock interviews, including challenges and behavioral questions and 1-on-1 post-interview reviews and feedback meetings from career mentors.
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Courses
12-Week Data Science Bootcamp
Big Data with Hadoop and Spark
Data Science with Python: Data Analysis and Visualization
Data Science with Python: Machine Learning
Data Science with R: Data Analysis and Visualization
Data Science with R: Machine Learning
Data Science with Tableau
Deep Learning
Introductory Python
NYC Data Science Academy Reviews
Average Ratings (All Programs)
Anonymous
Graduated: 20177/7/2017
Course
12-Week Data Science Bootcamp
"Mixed feeling after graduating bootcamp"
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
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.
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S Sarmadi
Data Scientist | Graduated: 20176/6/2017
Course
Data Science with Python: Data Analysis and Visualization
""Data Analysis and Visualization with Python course with Tony Schultz""
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
Mayank Shah
Data Scientist | Graduated: 20175/26/2017
Course
12-Week Data Science Bootcamp
"Rewrote my whole life story in just a few months"
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
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.
Jhonasttan Regalado
VP Production Support Manager | Graduated: 20164/22/2017
Course
Data Science
"Bootcamp Journey"
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
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.
Lukasz
Graduated: 20174/22/2017
Course
Data Science with R: Machine Learning
"ML in R: Thorough and rigorous class in which you'll learn the fundamentals well"
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
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.
Lei Zhang
Data Scientist | Graduated: 20163/30/2017
Course
Data Science
"Great Jump start for Data Science"
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
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!
Rahul Bhat
Graduated: 20173/13/2017
Course
Data Science with R: Machine Learning
"Machine Learning with R with Luke Lin"
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
Anonymous
Hedge Fund Analyst | Graduated: 20163/4/2017
Course
Data Science with Python: Data Analysis and Visualization
"Solid foundation for Data Science and Visualization"
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
L. Kan
Data Scientist | Graduated: 20162/28/2017
Course
Data Science
"Great program that leads me to the world of data science"
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
They provide as many helps as they can, but you have to be proactive and eager to learn to take everything in!
Abhishek Desai
Graduated: 20161/31/2017
Course
Data Science with Python: Data Analysis and Visualization
"Excellent structured approach to develop your Python skills"
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