AVP, Data Science & Application Architecture
The quality of both the instructors and course materials is high. It has been an amazing learning experience for me and definitely worth the investment that helped me get to my next stage of career growth. Regardless if you are trying to supplant your post-graduate degree, thinking of doing a career switch to data science, or wanting to supplant your skills, the bootcamp offers that opportunity to push yourself to reach your maximum potential.
That said, this bootcamp requires that you bring your A-game into the arena. This is not an easy course to take, and for good reasons. The bootcamp will stretch you to surpass what you think your limitations are and push you to be at your best at all times. This requires 100% commitment from your part. Anything less will not be good enough. If you fully commit yourself, you will emerge from this course with a renewed sense of passion in this exciting field. If there is one regret, it would be that I should have done this bootcamp sooner.
The job opportunities for data science and machine learning specialists are just amazing. Since getting the certification (even before then), the contacts and network I have made in the data science community have accelerated at a rapid pace. The reachout from recruiters have also increased significantly. The demand for data scientists continues to climb. In hindsight, it was a great decision for me to have made the jump to go through the bootcamp, as I am now working on numerous opportunities that allow me to be more creative and innovative.
The academy is managed and run by an amazing team of people who have helped me through the many months of learning and growth. They have been such a strong support system for me as I take the next journey through my career as a Data Scientist. The academy has also opened my eyes to so many wonderful experiences and allowed me to validate the opportunities and potential of this exciting field I am in. I have learned so much and the real skills I have acquired will be of tremendous value as I embark on pursuing my passions.
As the saying goes... "Never give up on a dream just because of the time it will take to accomplish it. The time will pass anyway." I pursued mine and living it, now it's up to you to pursue yours.
I would recommend the bootcamp to anyone in need of a career transition into Data Science, willing to go above and beyond, and are comfortable with either statistics or basic programming.
Though the pace is relentless, the program is very manageable given the dedication of the instructors to see you succeed. You'll form great relationships not only with the staff but with other gifted students as well as you all learn together about this exciting field.
VP, Data Scientist
Fraud Detection Citigroup
Most importantly, learning in the immersive environment quickly accelerated my technical know-how. I became adept at R, Python in addition to structured thinking, open-ended problem solving, and communicating my ideas and work across to a wider audience.
Additionally, preparing for the five project presentations and homework assignments with like-minded peers in my cohort also positively influenced my experience. Sharing ideas, knowledge and experiences with my classmates, and TAs - encouraged me to creatively explore every approach when faced with a challenging problem or in-class lab.
I am grateful for my time at the NYC Data Science Academy. I highly recommend enrolling if you're undecided - it's an awesome place to prepare for a new career in data science and machine learning.
The course content covered coding in SQL, python and R during my time at the bootcamp. As a data scientist, ability to code in this basic languages is critical to developing and testing statistical hypotheses and machine learning concepts. All machine learning examples had supporting Python and R code to facilitate students' application of these algorithms. This bootcamp covered application of Spark during the last few weeks of the course. Knowing Spark capabilities was particularly helpful in my current position as a data scientist.
The bootcamp covered traditional statistical concepts such as hypothesis testing, linear regression and logistic regression as well as advanced machine learning algorithms such as K-Means clustering and Neural Networks. The bootcamp strategically provided theoretically background for these concepts in conjunction with worked out examples in R and Python. Knowing how to apply all of these algorithms helps me to rapidly move through proof-of-concepts in my current day-to-day.
During my cohort, the bootcamp instructors were incredibly dedicated to helping the students succeed. Instructors were consistently available to answer coding questions on-site in person or off site via slack or email. I was always satisfied that the instructors were able to answer my coding and ML questions rapidly and completely.
The bootcamp helped me find several job interviews towards the end of the bootcamp. It was clear that the NYCDSA had access to an increasing network of employers looking to hire data scientists. During the interview process, I had felt that the bootcamp prepared me to answer all of the data science interview questions during each interview.
It has been over a year since I first enrolled in the NYCDSA bootcamp and I continue experience the benefits of the bootcamp in my day-to-day job as a data scientist. I strongly recommend this bootcamp to anyone looking to make a career transition into the data science field.
Quantitative Trading Analyst Intern
Hermes Capital Advisors, LLC
The program covers a wide array of topics, combining theory and application to give you a well-rounded understanding of the material. Students are encouraged to learn by doing, and home-works are given out 2-3 times a week, with deadlines not always easy to meet. But given how much the instructors offer to help, students usually always find a way.
The whole team goes above and beyond to help out not only with teaching you data science, but also with things like interview readiness, job placement, and helping you build a great portfolio.
You are surrounded with like-minded people for 12 weeks, forming great friendships learning from each other. You are tutored and lectured by industry professionals who go out of their way to make sure you understand the material. You are exposed to cutting edge software, advanced machine learning algorithms, and industry best practices. You are helped with building a portfolio, creating a great resume and how to pitch your work to employers.
I’m truly happy I did this program, and so will you.
Senior Data Scientist
Big Data Analyst
Data Science Engineer
The bootcamp covers all the skills that I need to know to be a successful Data Scientist. It provides training on: programming skills (in both R and Python), basic Linux/Unix commands, basic database SQL programming, exploratory data analysis & data visualization (in both R and Python), Machine Learning in both R and Python, and basic Hadoop and Spark skills. Some people might wonder why both R and Python were taught. From my experience, R is really helpful and handy when doing the EDA and visualization at the beginning. Python is more useful when building production pipeline models. Also Jupyter Notebook (originally called iPython Notebook) makes sharing the code and charts easier. So I feel it was right that they taught both R and Python.
The program was very intensive. There was so much information thrown into my brain every day so thus I had to study and review the course material every night late in order to digest them. We were assigned homework every other day and projects every 2 weeks. There were about 5-6 projects through the course of the bootcamp. Each project had a different focus. While the earlier projects focused on Exploratory Data Analysis, the later ones were more Machine Learning focused. I found myself was always rushing to wrap up the projects because I always had a difficult time to come up with an idea or started it late. Lesson learned!
During the bootcamp, because I was from computer science background, I was quite relaxed on the programming parts. But I definitely struggled a lit bit on the Machine Learning part since it involved advanced Math and statistics. So I had to go back and review some of the Math material and took some online training on statistics. Therefore it would be great advantage for people with statistics background. If people without statistics background and trying to take the bootcamp, I would suggest that you study some statistics material from online before the bootcamp so that you can really understand the theory behind.
I also want to give credits to the awesome instructors. Special thanks to Sam, Chris, and Luke who did a great job on teaching the class and answered all my questions. There were also two TAs who has provided big help on homeworks and projects.
Quick notes on job assistance, NYC Data Science Academy has connections with hiring partners. Therefore we got many job opportunities directly from the hiring partners, such as Goldman Sachs, Chase, NBL, Booz Allen Hamilton. There was a time that the former job placement manager was slacked. But it was quickly fixed and the job placement manager was replaced and things were back on track again. We were also provided training on preparing interviews and sharping up my resume. Even though I got a job from an opportunity I found from LinkedIn, but the job assistance from the Academy was definitely helpful.
To sum it up, I have learned a lot from the bootcamp and I also spent a lot time to digest them after I finished the bootcamp. The only two things I suggest are: because EDA and Data Visualization are so important, it would be great to have an example on those that we could have walked through or done together. Or for at least one of the EDA and Data Visualization projects, we work on the same topic and review it together. Second suggestion is that more hands-on on Spark excise. I would suggest Databrick community version to be used for student excise.
AVPt, Quantitative Analytics
Barclays Investment Bank
Data Scientist, Digital Intelligence
JP Morgan Chase
The bootcamp is an intense experience that will reward you if you put in the appropriate effort. The lectures are fantastic and the instructors are incredibly helpful with your projects. They will offer you as much help and guidance as you want (they were, more often than not, there before me and were still there when I left).
Job placement assistance was also crucial to my success. I met my current employer through a bootcamp and felt more then prepared during my interviews. You really feel that you are given individual attention and they will do everything in their power to help you find a job.
Some tips to prospective students:
- Become familiar with the basics of R and Python (especially Python as this is introduced later in the bootcamp when you are becoming busy). I didn't enter the bootcamp as a programming expert but I found having some knowledge was a large advantage. A few months of learning the basic syntax and doing exercises in your spare time should be sufficient (that is approximately what I did).
- Enter if you are willing to commit 3+ months to your career (you will be studying and preparing for interviews after you finish the bootcamp).
NYC Data Science Academy was a fantastic introduction to the world of data science. I still stop by the offices to say hi to instructors and students and discuss life. I would make the decision to join the bootcamp again 10/10 times.
Sr. Director, Data Science
As soon as I arrived I met Vivian and her team who already knew what type of Data Scientist I was looking for and introduced me to a few students. I was so impressed by them that I decided to invite them for an interview and within one week hired one of the graduates. He has been working with us for a few months and has already made a difference. His amazing technical skills combined with a very strong business acumen helped him take a lead on critical corporate projects and execute them with excellence.
I strongly recommend all employers looking for Data Scientists to contact Data Science Academy as it truly helps prepare the next generation of data scientists for real world jobs.
Comparing against other bootcamps, I decided to go with NYCDSA for its thoughtfully planned schedule. From the large volume of content to the scheduling of each day, it had what I needed to succeed. Each day consisted of lectures with really useful slides and concluded with time for homework and projects in the afternoons. The allocated time in the afternoons gave us time to digest what we learned and the homework assignments reinforced the new knowledge.
Coming from a background in biomedical engineering and biological sciences, I was used to being told everything I had to know. The bootcamp gives a lot of information with its detailed lectures but also challenges students to find their own answers. For example, a homework assignment had a problem mentioning a function that was not mentioned in lecture. We had to research it and learn how to use the function before we could do the problem. This taught me how to be resourceful and find answers on my own instead of relying on someone to tell me everything. Because data science is a growing field, you cannot expect to learn everything in a short period of time but should know how to find solutions on your own.
Being challenged to learn may sound intimidating but it really isn't when you're surrounded by supportive peers and staff. The staff are extremely hardworking and friendly. They stay late, sometimes even until 11pm and they love what they do so they won't be grumpy or annoyed at you. They also come in on the weekends and will help with homework assignments and projects if you require it. The TAs are excellent resources who are passionate about data science and motivate you to always do better.
Advice: Try to familiarize yourself with the suggested R and Python readings before you begin the bootcamp so that you can spend less time trying to understand concepts and more time on the data science parts.
Even after graduating from the bootcamp, I still feel like family around them. The instructors and staff do not forget you and continue to help with your job search. Vivian actively connects you with resources and posts jobs you may be a fit for. She also holds coding review sessions so that we are better prepared for interviews.
Job Prospects: Besides the countless data scientist and analyst job posts found online, NYCDSA hosts a hiring party at the end of the bootcamp that connects recruiters from multiple companies with students. It gives you a big opportunity to speak with recruiters and build connections. I interviewed with one of the hiring managers from the event and got an excellent data scientist job approximately 1 month after graduation. You have other opportunities to stand out from crowd when Vivian reaches out to her contacts and sends in your resume so you're not just another applicant in the pool. There are tons of jobs and the support from NYCDSA is outstanding.
I have no negative memories of the bootcamp besides the late nights spent on projects but you get as much as you put into the program. Overall, the bootcamp does a good job preparing you for a career in data science as long as you work hard for it. Your peers will be your friends and consultants for your data science problems. I would join another cohort at NYCDSA if I could!
Associate Director, Marketing Science
- Strong teaching staff who is clearly passionate about teaching data science as evidenced by the late evenings and weekend support
- Focus on concepts and skills that are actually relevant to the marketplace
- Broad and dense curriculum (R, Python, machine learning, Hadoop, Spark, MongoDB, etc) to maximize learning in a limited timeframe
- Flexibility and nimbleness of the program to adapt to feedback from alumni, employers and the market to maintain the relevancy of every topic taught
- Good mix of lectures, homework and projects
- Helpful job prep activities such as interview coding simulations (and others that I won't spoil)
- Eclectic mix of students (though this may vary by cohort) that allowed us to learn from each other's diverse backgrounds and areas of expertise, and develop deep personal friendships and professional relationships
- Opportunity, if selected, to present projects at Data Science Meetups which offers networking opportunities as well as practice of presentation skills
- As data science is a dynamic and evolving field, keep up with the latest advances such as improvements in R packages and update the curriculum accordingly
- Give harsher constructive feedback to students when required
- More transparency on student evaluations overall and for Meetup project selections as well
- Be committed: the bootcamp is demanding but that is by design. It's an investment; you get out what you put in. Don't show up late, don't ignore the homework. If you do, it's your loss
- Don't fall behind: there's a lot of work and learning a very rapid pace, not to mention homework almost daily
- Be proactive: reach out to the TAs or the instructors for feedback (not just help), read up on machine learning outside of the bootcamp, talk to your classmates on how to collaborate
- Manage your time: you will have to juggle many responsibilities and will most likely feel overwhelmed in general. That is also a skill you will need in the professional world
- Learn to be autonomous: don't run to the TAs or the teachers for help as your first recourse. Google, StackOverflow and other resources most likely already ahve the answer you are looking for. Only when you have made a decent attempt at figuring out the problem should you ask for help. After the bootcamp, that safety net will no longer be there so it's best to practice early
Business Intelligence Analyst
Business Intelligence Modeler
- I bought a new computer and studied statistics, R, and Python for over a month before my first day in the bootcamp.
- I worked more intensely and consistently at the bootcamp than I've worked on anything over a 3-month period, either in school or in a job.
- The staff are maybe the bootcamp's finest feature. The instructors are technically proficient, patient, and articulate. Somehow, I didn't feel intimidated, more inspired. In three months, every time I requested support, I was supported.
- The office has a simple aesthetic and is well-equipped and well-maintained. It is often crowded, but overall a space where I felt focused and could work.
- I gave the curriculum 4/5 stars. I found the material fascinating. There were many times when I simply didn't keep up. There is a lot of material. Read that sentence again. The curriculum moves so quickly that it often felt like a day-tour of Europe.
- I found my classmates highly-educated, focused, and committed. I forged some excellent working and social relationships.
- You will commit yourself to this program for 3 months. For these 3 months, this is what you will do during the day and in the evening, weekdays and weekends.
- With whatever time you have before the bootcamp, you will study statistics, R, and Python.
- You accept early on that sometimes it will be acutely stressful and overwhelming.
Lead Data Scientist
Senior Vice President
I attended the Big Data with Hadoop and Spark course, hosted and led by NYC Data Science Academy. My objective was two-fold: first, to gain a deeper and practical understanding on emerging 'Big Data' technologies, more so than what academic publications or industry white papers currently provide; and, second, to familiarize myself with the skill set and experience to expect from the new generation statisticians, or Data Scientists. With a background in Business Intelligence, Architecture, Risk Management and Governance on Wall Street, I find that foundational skills remain the same: mathematics and statistics. However, with the commoditizing of data storage and massively parallel computing, Data Scientist today are capable of solving problems reserved for an exclusive few in decades past. The course did not cover configuration of the Hadoop environment, but thanks to the engaging and knowledgeable instructor, clues on challenges and potential pitfalls were generously shared. I highly recommend this course not only to professionals or recent graduates looking to hone data analysis skills, but to anyone with an interest or stake in Big Data.
Three months ago I had no idea what I had signed up for. I wasn't even sure I had made the right choice--not just with NYCDSA, but data science in general. I didn't know how to code and all my statistics experience came from an academic setting. Three months later and I can hardly comprehend how I got to where I am now, but I know for certain I wouldn't have gotten here without NYCDSA. On the first day it was clear that I was a bit of a minority. It seemed that everyone had more experience than I did--I had been a classroom teacher for 6 years, and an English teacher at that--but this wasn't a time for excuses. No matter what level you arrive at, you can't survive the program without being all-in, and that might be its greatest strength. I (and the rest of my cohort) kissed goodbye to our social lives and fought through three of the most challenging, stressful months of our lives. Suddenly I'm a proficient coder in two languages, I understand the statistical nuance behind complicated machine learning algorithms, and most importantly, I landed a job that is wildly better than what I imagined I could get. Seriously. I took the screening interview just for the practice. And then I got another interview. And then another. And then a job offer. And throughout, I knew the answer the virtually every question they threw at me. And for that, I have to thank NYCDSA.
I had a great experience at the NYC Data Science Academy.
To give you a little background, I have a PhD in Biochemistry and did a Post-Doc in computational biology and bioinformatics and then worked in industry for a couple of years in both technical and non-technical roles. With the recent advent of data science, I made a decision to make a transition to data science and wanted to get up to speed in data science, Python and R, as well as machine learning, in a rapid but focused manner. The NYC Data Science Academy provided the perfect opportunity to do so.
The things that stand out about the Boot Camp were:
- Quality and enthusiasm of the instructors - Given the broad range of the participants, the instructors really knew how to challenge us.
- The Teaching Assistants - The TAs were patient and provided great guidance and instruction.
- Quality of the participants - It was a great experience to go through the boot camp with a really talented group of people.
- Projects - The individual and team projects really gave me the opportunity to challenge myself and stretch my abilities. It also provided with a nice portfolio which I can show potential employers.
- Vivian and Janet - The heads of the Boot Camp really showed that they cared about the participants and challenged us to work hard and remain engaged.
- Guest speakers - The quality of the guest speakers was really outstanding.
A word of caution about participating in the Boot Camp. Be prepared to work like crazy. I worked 12 to 14 hours a day, 7 days a week for three months straight.
- the theory
- the tools
- and a lot of practice through homeworks, in-class labs and projects
- This week, for example, she organized drinks with 20+ companies who came to meet with us (ranging from Guggenheim Investments, Two sigma, Goldman to Medivo, Draft Kings, About.com and many startups too).
- Last week, she got Spotify to bring in 3 speakers who then individually interviewed 15 people the rest of the afternoon!
- theory briefly (no proofs) but complete.
- focus on the different parameters, what they do, how they affect the model etc...
- then code and actually show how to use all this
- then homework to let us try to replicate what we just learned
- then projects to make sure it sinks in!
Memorial Sloan Kettering
I had an interest in data science but was making slow progress learning it on my own. This program gave me a strong foundation to build my future growth upon. It covered all the statistics necessary to apply statistically learning methods appropriately. It taught the most commonly used machine learning methods across industries. These methods were covered in both R and Python. Seeing the material in both languages was great, it gave you two chances to be exposed to each topic. All of the material was presented with clear lecture slides that will continue to be a resource. Each topic was also presented with sample code and exercises to explore the material in a hands on fashion. We also had the chance to work on real world data science projects that applied the material covered, with the assistance of our teachers and TAs. The bootcamp hosts a monthly Meetup that gave us a chance to present our work publicly. We had weekly speakers who were leaders in their respective fields come and speak to the class about different facets of data science. In some instances these speakers also had projects we could work on if we were interested in their field. The bootcamp went to great lengths to get us access to hiring partners, actually bring data science managers/HR managers to us. To be successful in this program you need to work as hard as they work for you. It wasn't uncommon to work with instructors late into the night or on weekends. This has been a great experience and I would recommend it to anyone who is serious about becoming a data scientist.
Associate - Senior Data Scientist
Booz Allen Hamilton
I attended the Data Science Bootcamp in summer 2015. It was a very enriching, useful and enjoyable experience. It offered plenty of important things that one couldn't hope to find by taking online courses or reading textbooks. The instructors possessed valuable knowledge and perspectives in the data science industry, and were able to share them with the students through various activities (e.g. lectures, invited talks, meetups, company visits, individual counseling, etc.). Also, students had a lot of opportunities to interact with established data scientists, as well as collaborate with other aspiring ones on real-world projects.
Product Growth Manager
Mount Sinai Hospital
Data Science Bootcamp was the best experience in my career. Instructors were not only helpful in teaching the regular materials but also guide you to establish your confidence in yourself to be a Data Scientist. They will help you even after completing your bootcamp. Nice and honest environment.
I took Machine Learning with R and Hadoop data engineering classes in 2015. They are all well-structured classes with extensive information coverage and concrete learning process design. All the techniques been told in the class are very practical and can be applied to work very fast. In addition, it is also a great opportunity to build your "data science" fellow network because all your classmates are "Pro" in this domain with a lot of wonderful industry experiences to share. I would definitely recommend NYC Data Science Academy to my friend!
Director of Campaign Analytics
Vivian came to our company and taught us five one-day sessions in R from entry level to intermediate level. I had no experience in R before. But I have learned a lot from Vivian and from the resources she provided, both from online and from the books. The homework and the office hour are also very helpful. After the classes, I have started to use R in my job from very basic stuff to more advanced data manipulation and analysis. Vivian is very knowledgeable in R and a warm person to work with. Thank you, Vivian.
I took Machine Learning with Python and Data Analysis with Python in the Spring. I found both course useful and informative. The courses have given me a comprehensive and yet in-depth introduction into Machine Learning and Python. And these skills turn out to be invaluable at work. Most importantly, Vivian is an excellent instructor. She is immensely helpful and supportive which makes the learning process quite enjoyable. Definitely recommend NYC Data Science Academy!
Senior Manager, Management Science & Integration
NBCUniversal Media, LLC
I took the Data Science with Python: Machine Learning course and I learned a lot. This course helped me to improve my data analysis and general Python skills. It introduced me to several new libraries and algorithms, most of which I plan to use at work. Overall, I had a very positive experience.
I took Vivian’s Data Science course and had a fantastic experience. I networked with Data professionals from the NBA, the Federal Reserve Bank, NYC startups, and more. I learned a lot very quickly and had a lot of fun. It’s a nice part of the city and the building has a great startup feel to it. …While I was still enrolled I implemented a hierarchical clustering algorithm and put it into production. I wouldn’t have been able to do that if I hadn’t learned Data Science at NYC Data Science Academy.
Basho Technologies, Inc
Thanks to NYC Data Science Academy, I was able to find a great job as a data scientist at a startup before the 12 weeks was even up. Had it not been for the Data Science Boot Camp, I would still be looking for a job. The Boot Camp builds confidence in data science through exercises, homework, lectures, and personal projects. These projects are immensely helpful when job searching, and students are encouraged to take on as many as possible. Over the 12 weeks, I gained proficiency in R, Python, Hadoop, and SQL, just to name a few. Vivian, the Program Director, is truly devoted to her students’ success. She continuously challenged us to step outside our comfort zone and dive head first into the most difficult concepts. The other staff members at NYCDSA including Bryan and Janet, are also extremely knowledgeable and helpful. Students have the full support, encouragement, and expertise of the NYCDSA staff. This experience, while extremely challenging, exceeded all my expectations. The skills and knowledge gained from NYC Data Science Boot Camp is well worth the price, and the effort.
Great class. For only a 5 week class it is very comprehensive. Covers the basics and commonly used libraries used in python for data analysis as well has how to use them. Notebooks used in the class are a great go-resource after the class ends. Also a great community of data professionals and networking if you are thinking about a new gig.
Head of Data Science
Vivian led two training sessions for our team at our company location, and covered both introductory and intermediate data analysis using R in five days. We very much enjoyed Vivian’s engaging teaching style and the hands-on exercises. She was able to draw on a broad array of real world experiences she had with clients in many different industries. This helped us feel the excitement of how data science techniques were used to solve challenging problems. I particularly like the fact that she insisted on the post-training projects that were completed by all attendees. It was satisfying for me to see what our team could do in a very short period of time using the skills gained in the training.
Senior Product Manager, Data Science
Great comprehensive course that give you a thorough overview of Python and how it can be used in the field of Data Science.
Analyst, Insights & Strategy
As a novice coder, this class was a great way to learn how I can manipulate and analyze data in Python. Would recommend for anyone interested in learning how to use python and apply to daily work.
Senior Statistical Programmer
Roche Innovation Center
Excellent 2 days of GIT and GITHUB training! The trainer, Bryan Valentini was very personable and took the time to answer everyone’s questions as well as provide desk-side assistance. Would definitely recommend to others new to GIT and GITHUB!
Cofounder & CTO
The intermediate python machine learning course was a fascinating time. It gave me a much better feel for the variety of practical techniques that can be used in the field, and I’m frankly really excited to apply what I’ve learned in the near future. Make no mistake, the course and topics are challenging, but your perseverance will be rewarded.
Data Scientist, Digital Intelligence
I found Vivian’s Intermediate Python class to be very refreshing, given the formulaic approach that most books I’ve read on Data Science tend to be. She definitely knows her subject, clearly communicates that to her students, and fosters lively debate during class. Can’t wait to see what my fellow students present for their final projects!
SVP, Intelligence Solutions & Strategy
Millward Brown Digital
As the business world becomes increasingly data-driven, the Data Sciences classes at NYC Data Sciences Academy are invaluable to driving career success, not only for actual data science practitioners, but those who collaborate with them day-to-day to execute on insights to be gleaned from data sciences. I just completed the Intermediate level Data Sciences with R class and have immediately benefited from the ability to understand the different type of advanced analytic techniques that are available to help my clients with their business issues, to better communicate and collaborate with our Data Sciences team on a tactical level and then to take their output and accurately translate it into our clients’ business language. The course was comprehensive and Vivian brings a lot of passion and dedication to the class and ensuring her students’ success.
Binocular Vision LLC
Scientist (DMPK & Safety)
It was only a four-day entry-level training, but it turned out that I made the right choice to come along, join Vivian and her talented colleagues, and benefit tremendously from the lessons, discussions and on-site exercises. What’s more, with the encouragement from the teachers, I managed to complete my own small R project, and have been interested in further my studies on R ever since. I strongly recommend any one, who is intrigued by data management, visualization, data mining, statistics, or critical thinking using mathematical tools, to learn R, or preferably, learn R with Vivian and her colleagues, to expand his or her horizon, and make use of R in many ways possible.
Product Adoption/Data Scientist
I took both the intensive beginner and intensive intermediate R classes back-to-back on weekends over a four-month period. Although 7 hours a session may feel hefty, once you’re in the class time will fly by. Sessions split time between lecture and hands-on exercises, so you have lots of time to ask questions. Homework assignments are manageable – Vivian is very accessible should you have a question by email or in-person office hours. Each class ends with a Demo Day of a project of your choice. You will access real data from the Internet using APIs and analyze this information and ways you never would have thought possible using Excel or even SQL! Because of the initiative I took to learn the material, I have accepted a position as a Data Scientist at Google. A big thank you to Vivian and the team at the NYC DSA for helping me make the leap in my career from business analyst to data scientist!
Big Data & Business Intelligence Architect
I took the Data Science by R programming (beginner level) class taught by Vivian. The class material was very well organized and consisted of tips and tricks that only someone who has worked extensively with R would know, some undocumented features included. The course, home work, and project are quite intensive, so be prepared to put the time in; but when you are done, you will be a much more valuable professional! It’s all well worth the effort and hard work. The beginner course has set the stage for me to take the next level data mining class, which I am eagerly looking forward to.
Content Researcher, TED Content
I enjoyed this class — I would give it a 4, only because it went a little too fast for me at some points. I am a beginner of the most clearly beginner level. I had played with some front end programming, but never attempted backend work. The 5 hour classes on Saturdays were tough because it required a lot of homework and studying during the week, but the instructor was good about answering questions and pushing us to keep working on new and interesting things. The program was extremely supportive of me while I was trying to learn new material, I have and will continue to recommend this class/NYC Data school.
Software Engineer, Business Systems
I took the first offering of Data Science using Python a few weeks ago, and definitely recommend it to anyone who loves hands-on learning with some guidance. Let me explain: Last year, I took Coursera’s Machine Learning/Intro to Data Science courses and did well, but did not do a hands-on project that would enable me to retain a lot of knowledge. But this course required me to pick a detailed project and present it to a live audience, who then determined whether I did well or not. So I learned how to do web scraping, extract social media API data, write object-oriented Python, utilize a NoSQL database (MongoDB) to store results, and finally create visualizations in D3 and HighCharts. And then the pressure to present well, just to pass the class. Our instructor John was competent, knowledgeable and helpful, and covered a variety of useful tools like Pandas and Scikit Learn, including machine learning algorithms. And Vivian is always pushing us harder to do better. Sounds familiar?
Healthcare and Life Science Solution Architect
Amazon Web Services
The instructor, John Downs, was very knowledgeable and did an excellent job of providing an overview in the key areas of Python. After the five week class I went from knowing essentially nothing about Python to using it as one of my “go to” tools in which I am able to accomplish tasks at work on a daily basis.
I took the beginner level Python class with John Downs and really had a great experience. John is very knowledgeable about Python and programming in general, and was able to be helpful to students of all levels in the class. The exercises in class and the homework got our hands dirty with the language and the final project was a great way to create a real result by the end of the course. Overall it was challenging, but a valuable intro to a useful tool that was easier to approach with real-life sessions than self-study demos on my own. I’ll definitely take classes with NYC Data Science Academy in the future and would recommend it to my friends.
PwC Advisory Analytics
John Down’s Python for Data Analysis class was a helpful introduction to using python toolkits such as Pandas and Scikit Learn to work with large and complex data structures. John started the class off slowly to get the group adjusted to Python syntax, but made sure to include all of the essential data management/analysis techniques to get started (e.g. dataset merging, manipulation, basic stats/regression, etc). In a short course, John did a great job of including numerous examples in ipython notebooks that he gives to the class– this approach was very helpful for exposing beginners to more complex techniques that they can go back to when they are ready. I definitely recommend this course to any beginner interested in learning how python can help make data analysis faster and easier.
Business Analytics | Data Visualization
Very informative class. Vivian uses intensive exercises and hand-on practices to make sure you understand how to use the packages she teaches!
Associate Director, Advanced Analytics
MEC Global, Rosetta
I completed the Intensive beginner course for R and I highly recommend it! I’ve learned a lot in 5 weeks and I can say that I am now an R convert (from SAS). I’ve learned so many functions and packages that I am now able to use them confidently at work. Vivian was also a great, hard working teacher who encouraged every one in the class to study harder which means she really cared that that her students would become great data scientists sooner than later. I like the class so much I am now taking the R intermediate class.
Analytics Media Group
I strongly recommend this class to all potential students who have some programming background. The pace at the beginning is necessarily rapid to cover the basics of syntax and structure, so that more time can be devoted to numpy/scipy/pandas/etc. John was a fantastic instructor, and impressively it was his first time teaching the course! Super nice/patient/knowledgeable, and he has a real knack for explaining stuff. Taking introduction to Python for Data Analysis was a great decision for me. In a relatively short period of time, I was introduced to the top analytical code libraries in Python and gained experience using them. Well worth the time and money: I’d do it again in a heartbeat.
Google for Work - Global Head of Android Operations
As an employer, I have found NYC Data Science Academy classes significantly improved the data science and visualization skill set of our research and business analyst. The courses are practical, compressed and come with lots of support. We sent a motivated team member to the Intensive Beginner R class. Previously he had no R experience and in one month’s time he was able to achieve proficiency. Since completing the course, our analyst has built, analyzed and presented data in valuable new ways.
Landscape Architect / Data Science Student
I just finished the 002 session of the beginner R class. We certainly got a lot of “bang for our buck”, because Vivian is preeminent in the field of data science, and she was able to move through a lot of material very quickly. She worked extremely hard in preparing well organized slides, and for me the key was to go through the day’s presentation, provided beforehand, during the week prior to the class, running all the code and seeing what it does. This allows you to keep up and absorb her lesson when you get into class. In addition to getting a solid start on the use of R, the class also provided valuable insight into the field of data science, which is a career into which I am interested in transitioning. Lastly, Vivian made herself available to us weekly for extra help, either in person or via web interaction, which was much appreciated. Like I said, she is very dedicated and works extremely hard at seemingly everything she does. Thanks Vivian!
I attended the beginner’s workshop for R and I found it extremely useful. The classes were very well organized. The slides were well paced with many practical examples. I especially like the hands on format of the class, you work through the slides on your laptop. I had very little knowledge of R before and I learned many tools during the course. I was particularly interested in the visualization tools. Since the course, I have used some of the charting tools that I learned in my presentations at work as well. Both Scott and Vivian did an excellent job teaching R basics. They were very helpful and answered questions in person, email and piazza (online platform where we would post our solutions). Vivian also shared with the class a lot of material and practical examples. I would highly recommend this course to users who are interested in learning R.
US Private Equity Lead
I took the initial version of this class late fall 2013 and found it to be well worth the time. The slides, examples and exercises were well organized. Scott Kostyshak’s presentation style is clear and concise. The second iteration will have twice the classroom hours and cover a lot of material that there wasn’t time for in the initial format. It’s worth the investment if you want to dive into the R ecosystem.
CCB Risk MIS Reporting & Analytics Manager
The Introductory R class covered a broad range of information, and for a statistics and programming newbie like me, was indispensable for coming up to speed on a variety of related subject matter. Vivian is passionate about R, open data, statistics, etc.. Her enthusiasm is contagious!
Super helpful. Vivian is a fantastic teacher. She really pushes everyone to dig in and start solving problems.