nyc-data-science-academy-logo

NYC Data Science Academy

New York City, Online

NYC Data Science Academy

Avg Rating:4.83 ( 271 reviews )

NYC Data Science Academy offers 12-week data science bootcamps in New York City. In these programs, students learn beginner and intermediate levels of Data Science with R, Python, Hadoop, Spark, Github, and SQL as well as popular and useful R and Python packages like XgBoost, Caret, dplyr, ggplot2, Pandas, scikit-learn, and more. Once the learning foundation has been set, students work on multiple projects through the bootcamp. The program distinguishes itself by balancing intensive lectures with real world project work, and by the breadth of its curriculum. Throughout the program students work alone and in teams to create at least four projects that are showcased to employers through multiple channels; private on-campus hiring partner events, student blogs, meetups, and filmed presentations. 

Ideal applicants should have a Masters or PhD degree in Science, Technology, Engineering or Math or equivalent experience in quantitative science or programming. Candidates with BA’s who have appropriate experience are also considered.

Throughout the data bootcamp, students are assisted in preparing for the employment process through resume review and interview preparation. NYC Data Science Academy works closely with hiring partners and recruiting firms to create a pipeline of interest for its students.

Recent NYC Data Science Academy Reviews: Rating 4.83

all (271) reviews for NYC Data Science Academy →

Recent NYC Data Science Academy News

Read all (20) articles about NYC Data Science Academy →
  • 12-Week Immersive Data Science Bootcamp (In-person)

    Apply
    Start Date Rolling Start Date
    Cost$17,600
    Class size50
    LocationNew York City
    In this program students will learn the modern data analytic techniques and master the requisite skills, such as Python and R programming languages as well as Hadoop, to address real-world data science problems. Throughout the program, students work alone and in teams to create at least five projects that are showcased to employers. Along the way, students will have assistance in preparing for the job search through resume review, interview preparation, and opportunities to interview with our hiring partners. Successful completion of the curriculum will present a certification of graduation certified by the New York State Board of Education.
    Financing
    Deposit$5,000
    Financing
    • Climb Credit Loan $400* pm for 60 months

    • Full Tuition Total $17,600

    • Skills Fund Student Loan
    $397.88 pm for 60 months
    Tuition PlansWe have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months.
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    ScholarshipLimited number of scholarships available to qualified candidates.
    Getting in
    Minimum Skill LevelIdeal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming.
    Prep Workhttp://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/
    Placement TestNo
    InterviewYes
  • Big Data with Amazon Cloud, Hadoop/Spark and Docker

    Apply
    Data Science, Python, Hadoop, Spark, Data Structures
    In PersonPart Time5 Hours/week2 Weeks
    Start Date January 14, 2020
    Cost$2,990
    Class size10
    LocationNew York City
    This is a 6-week evening program providing a hands-on introduction to the Hadoop and Spark ecosystem of Big Data technologies. The course will cover these key components of Apache Hadoop: HDFS, MapReduce with streaming, Hive, and Spark. Programming will be done in Python. The course will begin with a review of Python concepts needed for our examples. The course format is interactive. Students will need to bring laptops to class. We will do our work on AWS (Amazon Web Services); instructions will be provided ahead of time on how to connect to AWS and obtain an account.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelStudents are expected to be familiar with using an operating system from the command line; knowledge of Python is helpful.
    Placement TestNo
    InterviewNo
    More Start Dates
    January 14, 2020 - New York City Apply by January 10, 2020
    April 21, 2020 - New York City Apply by April 15, 2020
  • Data Science with Python: Data Analysis and Visualization (Weekend Course)

    Apply
    Start Date January 19, 2020
    Cost$1,590
    Class size20
    LocationNew York City, Online
    This five week course is an introduction to data analysis with the Python programming language, and is aimed at beginners. We introduce how to work with different data structure in Python. We covered the most popular modules, including Numpy, Scipy, Pandas, matplotlib, and Seaborn, to do data analytics and visualization. We use ipython notebook to demonstrate the results of codes and change codes interactively during the class. Our past students include people with no programming experience or those who have minimal exposure to Python. Students told us our classes are very informative, engaging, and hands-on.
    Financing
    DepositN/A
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    Getting in
    Minimum Skill LevelKnowledge of basic data types (e.g. string, numeric), data structures (e.g. list, tuple, dictionary) Familiarity with concepts of list comprehension and for/while loop
    Placement TestNo
    InterviewNo
    More Start Dates
    January 19, 2020 - New York City Apply by January 15, 2020
    March 7, 2020 - New York City Apply by March 1, 2020
  • Data Science with Python: Machine Learning (Weekend Course)

    Apply
    Data Science, R, Machine Learning, Artificial Intelligence
    In PersonPart Time7 Hours/week5 Weeks
    Start Date January 19, 2020
    Cost$1,990
    Class size10
    LocationNew York City, Online
    This 20-hour Machine Learning with Python course covers all the basic machine learning methods and Python modules (especially Scikit-Learn) for implementing them. This includes linear regression, Naïve Bayes classifiers, logistic regression, linear discriminant analysis, cross-validation, bootstrapping, feature selection, regularization, model selection, SVM, decision trees, random forest, PCA, K-Means, and Hierarchical clustering. In addition, this course teaches the basics of natural language processing. After successfully completing this course, you will be able to explain the principles of machine learning algorithms and implement these methods to analyze complex datasets and make predictions in Python.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelCompletion of Data Science with Python: Data Analysis; Data Science with R: Machine Learning
    Placement TestNo
    InterviewNo
    More Start Dates
    January 19, 2020 - New York City Apply by January 15, 2020
    March 7, 2020 - New York City Apply by March 1, 2020
  • Data Science with R: Data Analysis and Visualization (Weekend Course)

    Apply
    Data Science, R, Data Visualization, Data Analytics , Data Structures
    In PersonPart Time7 Hours/week6 Weeks
    Start Date January 18, 2020
    Cost$2,190
    Class size15
    LocationNew York City, Online
    This course is designed to provide a comprehensive introduction to R. Students will practice programming and analyzing data with R. Students will learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models to data. In addition to a theoretical framework in which to understand the process of data analysis, this course focuses on the practical tools needed in data analysis. This course also covers the creation of dynamic reports with the knitr package in R as well as the creation of dynamic dashboards with R Shiny. By the end of the course, students will have mastered the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting the code.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelBasic knowledge about computer components Basic knowledge about programming
    Prep WorkNone
    Placement TestNo
    InterviewNo
    More Start Dates
    January 18, 2020 - New York City Apply by January 15, 2020
    April 18, 2020 - New York City Apply by April 10, 2020
  • Data Science with R: Machine Learning (Weekend Course)

    Apply
    Data Science, R, Machine Learning
    In PersonPart Time7 Hours/week6 Weeks
    Start Date January 18, 2020
    Cost$2,990
    Class size40
    LocationNew York City, Online
    This 35-hour Machine Learning with R course introduces both the theoretical foundation of machine learning algorithms as well as their practical applications in R. It will introduce you to data mining, performance measures and dimension reduction, regression models, both linear and generalized, KNN and Naïve Bayes models, tree models, and SVMs as well as the Association Rule for analysis. After successfully completing this course, you will be able to break down the mathematics behind major machine learning algorithms, explain the principles of machine learning algorithms, and implement these methods to solve real-world problems. Unit 1: Foundations of Statistics and Simple Linear Regression Unit 2: Multiple Linear Regression and Generalized Linear Model Unit 3: kNN and Naive Bayes, the Curse of Dimensionality Unit 4: Tree Models and SVMs Unit 5: Cluster Analysis and Neural Networks Final Project After 35 hours of structured lectures, students are encouraged to work on an exploratory data analysis project based on their own interests. A project presentation demo will be arranged.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelKnowledge of Python programming Able to munge, analyze, and visualize data in Python
    Prep WorkKnowledge of R programming Able to munge, analyze, and visualize data in R
    Placement TestNo
    InterviewNo
    More Start Dates
    January 18, 2020 - New York City Apply by January 15, 2020
    April 18, 2020 - New York City Apply by April 15, 2020
  • Data Science with Tableau (Online)

    Apply
    Data Science, Data Visualization, Business Intelligence
    In PersonPart Time5 Hours/week3 Weeks
    Start Date Rolling Start Date
    Cost$1,590
    Class size20
    LocationOnline
    This course offers an accelerated intensive learning experience with Tableau – the growing standard in business intelligence for data visualization and dashboard creation. Without prior experience, students will learn to work with multiple data sources, create compelling visualizations, and roll out their data science products for continuous, scalable outputs to key stakeholders. By building insight and weaving narrative, students will be empowered to harness data in a striking way that provides value to organizations large and small. This course offers an accelerated intensive learning experience with Tableau – the growing standard in business intelligence for data visualization and dashboard creation. Without prior experience, students will learn to work with multiple data sources, create compelling visualizations, and roll out their data science products for continuous, scalable outputs to key stakeholders. By building insight and weaving narrative, students will be empowered to harness data in a striking way that provides value to organizations large and small. We utilized 4 user cases drawn from finance (public data from major stock exchanges) and sitcom data (Game of Thrones 1 ).
    Financing
    Deposit1590
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    Getting in
    Minimum Skill LevelKnow how to use Mac, Windows. Familiarity with relational databases is preferred but not required. gain a greater appreciation for the logic underlying Tableau’s features utilize their capstone project to visualize ‘big data’
    Prep WorkBefore the course begins, pre-work will be available for students interested in strengthening their ability to access and extract data from relational databases (e.g. SQL-based servers).
    Placement TestNo
    InterviewNo
  • Deep Learning with Tensorflow (Weekends and In-Person Only)

    Apply
    Start Date None scheduled
    Cost$2,990
    Class size15
    LocationNew York City
    Via analogy to biological neurons and human perception, this course is an introduction to artificial neural networks that brings high-level theory to life with interactive labs featuring TensorFlow, the most popular open-source Deep Learning library. Essential theory will be covered in a manner that provides students with an intuitive understanding of Deep Learning’s underlying foundations. Paired with hands-on code run-throughs in Jupyter notebooks as well as strategies for overcoming common pitfalls, this foundational knowledge will empower individuals with no previous understanding of neural networks to build production-ready Deep Learning applications across the major contemporary families: Convolutional Nets for machine vision; Long Short-Term Memory Recurrent Nets for natural language processing and time series analysis; Generative Adversarial Networks for producing realistic images; and Reinforcement Learning for playing video games.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelObject-oriented programming, ideally Python (introductory course: https://nycdatascience.com/courses/introductory-python/) Simple shell commands, e.g., in Bash (tutorial of the fundamentals: https://learnpythonthehardway.org/book/appendixa.html)
    Placement TestNo
    InterviewNo
  • Introduction to Python (Online)

    Apply
    Data Science, Python, Data Visualization, SQL, Data Structures
    OnlinePart Time5 Hours/week2 Weeks
    Start Date Rolling Start Date
    Cost$795
    Class size25
    LocationOnline
    The Introduction to Python covers the basic Python programming. Graduates will be able to write Python programs that read files, manipulate strings, and perform mathematical computations. The class is hands-on; participants will learn to write Python program by practicing coding along the way. The course covers most of the basic features of the Python language, including built-in data types and control structures, Python’s featured supporting object-oriented and functional programming, intro to Pandas, and regular expression.
    Financing
    Deposit795
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    Getting in
    Minimum Skill LevelComfort with Windows, Mac or Linux environment and ability to install third-party software.
    Prep WorkThis is a class for computer-literate people with no programming background who wish to learn basic Python programming. The course is aimed at those who want to learn “data wrangling” – manipulating downloaded files to make them amenable to analysis.
    Placement TestNo
    InterviewNo
  • Introductory Python (Evenings)

    Apply
    Start Date January 14, 2020
    Cost$1,590
    Class size40
    LocationNew York City
    This is a class for computer-literate people with no programming background who wish to learn basic Python programming. The course is aimed at those who want to learn “data wrangling” – manipulating downloaded files to make them amenable to analysis. We concentrate on language basics such as list and string manipulation, control structures, simple data analysis packages, and introduce modules for downloading data from the web. This Introductory Python class runs over four weeks, with five hours of class per week (split into 2 ½ hour evening classes). Classes will be given in a lab setting, with student exercises mixed with lectures. Students should bring a laptop to class. There will be a modest amount of homework after each class.
    Financing
    Deposit$1590
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    Getting in
    Minimum Skill LevelThis Introductory Python class is designed for computer-literate people with no programming background who wish to learn basic Python programming.
    Prep WorkIn the class, we will use Python 3. If you are following this video to set up Python environment, please make sure you download the Python 3.X version starting from 1 min 23 s in the video. Link: https://vimeo.com/160172414
    Placement TestNo
    InterviewNo
    More Start Dates
    January 14, 2020 - New York City Apply by January 10, 2020
    March 9, 2020 - New York City Apply by March 5, 2020
  • Remote Immersive Data Science Bootcamp (Online)

    Apply
    Start Date Rolling Start Date
    Cost$17,600
    Class size25
    LocationOnline
    Our Remote Intensive Bootcamp is an online full-time program. We live-stream our on-campus classes to the remote intensive bootcamp students. This program was designed for students that have the time to be a full-time student, but can't commute to our school. Students will be placed on a rigorous curriculum that spans from 9:30 AM to 6:00 PM EST as well as have access to prerecorded modules with over 1000 coding challenge questions on online learning platform for additional practice. In addition, they have access to dedicated TA’s as well as the larger network of a shared slack channel between both in person and remote bootcamp students. Live Classes: You will learn real-time streamed lectures as well as have access to prerecorded modules and coding questions for additional practice. Live Communication: They will learn real-time streamed lectures as well as have access to prerecorded modules and coding questions for additional practice. Personalized Job Support: Students also have access to the full resources of NYC Data Science Academy to help them find their dream job upon graduation. Our curriculum covers the expanse of all the skills required in the data science industry. We cover both R and Python as well as Machine Learning Theory, Big Data, and Deep Learning.
    Financing
    Deposit5000
    Financing
    • Climb Credit Loan $400* pm for 60 months

    • Full Tuition Total $17,600

    • Skills Fund Student Loan
    $397.88 pm for 60 months
    Tuition PlansWe have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months.
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    ScholarshipLimited number of scholarships available to qualified candidates.
    Getting in
    Minimum Skill LevelIdeal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming.
    Prep Workhttp://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/
    Placement TestNo
    InterviewYes
  • Remote Self-paced Data Science Bootcamp (Online)

    Apply
    Start Date Rolling Start Date
    Cost$17,600
    Class size25
    LocationOnline
    This is an online part-time self-paced program. Students have 4 - 10 months to complete this program. The curriculum is the same as our on-campus program, with full-financing options, career support and with a one on one support from our mentors. This program is designed for students that work full-time and are not able to quit their jobs. Our curriculum is drawn from data science engagement with corporate consulting and training, hiring partners and active industry participation. Our remote bootcamp ensures that students achieve a very high level of proficiency. Students are expected to dedicate themselves fully to this program and fulfill all the requirements, which include completing lecture videos, daily homework, and four projects. The Remote Bootcamp is built as a collaborative environment utilizing online chat and meeting systems. Students also have the opportunity to collaborate on homework, projects, job applications, interview preparation, paired programming, and even further through our extended alumni community. We work closely with hiring partners and recruiting firms to create a pipeline of interests for students. Each student receives one-on-one support with job searching and access to all kinds of job assistance resources, including coding reviews, interview prep, resume workshop, and access to our exclusive hiring partner network.
    Financing
    Deposit17600
    Financing
    • Climb Credit Loan $400* pm for 60 months

    • Full Tuition Total $17,600

    • Skills Fund Student Loan
    $397.88 pm for 60 months
    Tuition PlansWe have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months.
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    ScholarshipLimited number of scholarships available to qualified candidates.
    Getting in
    Minimum Skill LevelIdeal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming.
    Prep Workhttp://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/
    Placement TestNo
    InterviewYes

Review Guidelines

  • Only Applicants, Students, and Graduates are permitted to leave reviews on Course Report.
  • Post clear, valuable, and honest information that will be useful and informative to future coding bootcampers. Think about what your bootcamp excelled at and what might have been better.
  • Be nice to others; don't attack others.
  • Use good grammar and check your spelling.
  • Don't post reviews on behalf of other students or impersonate any person, or falsely state or otherwise misrepresent your affiliation with a person or entity.
  • Don't spam or post fake reviews intended to boost or lower ratings.
  • Don't post or link to content that is sexually explicit.
  • Don't post or link to content that is abusive or hateful or threatens or harasses others.
  • Please do not submit duplicate or multiple reviews. These will be deleted. Email moderators to revise a review or click the link in the email you receive when submitting a review.
  • Please note that we reserve the right to review and remove commentary that violates our policies.
You must log in to submit a review.

Click here to log in or sign up and continue.

Hey there! As of 11/1/16 is now Hack Reactor. If you graduated from prior to October 2016, Please leave your review for . Otherwise, please leave your review for Hack Reactor.

Title
Description
Rating
Overall Experience:
Curriculum:
Instructors:
Job Assistance:
School Details
About You

Non-anonymous, verified reviews are always more valuable (and trustworthy) to future bootcampers. Anonymous reviews will be shown to readers last.

You must log in to submit a review.

Click here to log in or sign up and continue.

  • Korrigan • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    I attended the inaugural bootcamp in from Jan 2015 to May 2015 and loved it.  I came into the program with a programming (java, matlab) and math background and some data analysis experience and was quickly met with tons of new material and challeneges.  I loved the fast pace, yet detailed lectures.  They provide a thorough introduction to R and Python followed by lectures on machine learning, statistics, and other data science technologies.  The best part of bootcamp is working on projects of your own design under the guidance and expertise of the lecturers. Everything I learned and created directly helped me get a great internship and later a great job.  I would recommend this botcamp to anyone looking to fully immerse themselves in the field of data science in order to better themselves or land a interesting job

  • Fangzhou • Data Scientist • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:
    N/A

    I attened 2015 Summer Data Science Boot Camp with NYC Data Science Academy. It was a positive experience and I would recommend it to anyone who doesn't have data science background and wants to step in this area. Especially if you are in the middle of job searching, and have great motivation and determination to learn. The advantage of being in a full-time boot camp is that the immersive learning makes time go faster without you realizing it. You can easily spent a whole day focusing on one data problem without any distraction. Just note that this bootcamp is for people who wants to learn basics and fundamentals, not for who wants to be a machine learning expert!

  • John • Data Scientist at The Ladders • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    Before I enrolled in the Data Science Academy's 12-week data science program, I had spent nearly a year exploring data science with almost nothing to show for it. Coursera, books, Kaggle, you name it. A bit discouraged and overwhelmed, I began the data science program with high hopes for strong teachers, a great community, and a rigorous crash course on all things data science.

    I got all that and more. Proof: I recently began a new job, and was able to hit the ground running on literally every front the company threw at me. Statistics and algorithms? Check. R programming? NYCDSA took us through almost all the packages my new company uses regularly. Python? Same deal as R. Infrastructure, AWS, distributed computing, visualizations, SQL? All check. And the NYCDSA enabled all of this - brilliant, helpful professors, well-designed homeworks / lectures, and great connections to the real data science world.

    Make no mistake - you'll be working unbelievably hard. Dozens of homeworks, ~5 projects, tons of slides and material to learn. But that's what you want, right? If you're serious about boosting your career, NYCDSA is the perfect place for you.

  • Anonymous • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:
    N/A

    I took the Machine Learning with Python class to get a fast and quick intro on how to code machine learning algorithms in python. 
    Our instructor, Shu, was very good and accommodated fully the needs of the class. He knows both the theory and the coding parts. 
    I think the course strikes a good balance between over-viewing techniques  and offering hands on specific knowledge so that you
    can go away and code on your own after the class is done. 
    I would recommend this course to anyone who wants to get started as quickly as possible with Machine Learning in Python. 

  • Sebastian Nordgren • Senior Vice President, Citigroup Inc.
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:
    N/A

    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 also to anyone with an interest or stake in Big Data.

  • Jake • Analyst at Spotify • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:
    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.
  • David Comfort • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    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 learniing, in a rapid but focused manner. The NYC Data Science Academy provided the perfect oppotunity 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 challlenge 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. 

     

  • A
    - 12/13/2015
    Nate Aiken • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    I though the bootcamp was an amazing experience.  It's helped me build a stronger statistical and programming foundation to start a career in Data Science.  It taught me the most widely used statistical learning methods in both R and Python.  We also covered topics employers look for like SQL and Hadoop.  The bootcamp involved daily lecture  and homework and was punctuated by projects to apply what we were learning.  We then had the opportunity to present our work to our peers and at monthly Data Science Meetups. The brought in weekly data science speakers to give us a sense of what being a data scientist in the real world is like.  These speakers included Owen Zhang one of the top ranked Kagglers, and Kirk Borne the head of Data Science for Booz Allen Hamilton.  The last two weeks of the bootcamp involved resume review, interview prep, and final projects.  They also helped us find jobs by actually bring data science recruiters and HR people to the bootcamp.  This program will LEFT JOIN your current life with a career in Data Science.

  • JF Darre
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    I attended the data-science bootcamp offered in NYC and had a great experience! I learned a lot on every aspects of data-science and machine learning:

    • the theory
    • the tools
    • coding
    • and a lot of practice through homeworks, in-class labs and projects

    It is very intensive, you will work ~12h+/day and on weekends, but you will leave the bootcamp with so much knowledge, coding experience, practice, 5 projects added to your linked-in/resume, 5 blog posts, a github account to be proud of  and even, if you want to, a participation in a Kaggle competition.

    The team is amazing. Vivian will do everything she can to improve your experience and has a huuuuge network:

    • 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!

    Janet, also will be in charge of continuously improving the program. That girl does not need to sleep. There were nights were I would leave at 11pm+ and she would still be there. A few weekends/sundays, I came to the bootcamp to work on projects with team-mates and she was there. She is incredible and really dedicated. She organises "Therapy sessions" every Friday to make sure we address and confront every problem we have encountered during the week which is really useful.

    The instructors are friendly, professional and knowledgeable. Every class has slides and code. I saved everything. What a resource this is! I have all the theory and code right there on my computer, no more looking on google's 20th page of results to find something somewhat relevant, or reading un-understable wiki pages about all this machine learning. Here, the way we learn is:

    1. theory briefely (no proofs) but complete.
    2. focus on the different parameters, what they do, how they affect the model etc...
    3. then code and actually show how to use all this
    4. then homework to let us try to replicate what we just learned
    5. then projects to make sure it sinks in!

    rather than everything you will typically find on-line which is: theory and then more theory.

    If this was not enough, on top of all the team and instructors, you'll have access to TAs too! They are very nice, smart and competent... and especially they are veeeeery... patient with us and our questions!

    Additionally, you have projects that you have to present to the class. So you get valuable practice both in presenting and also in collaborating with peers that no amount of sitting behind your screen can bring! Everything is recorded and edited by a pro. All the classes and your presentations too!

    Finally, they will regularly bring presenters to teach us about their projects, the real-world problems they face at work etc... Our class mentor (yes we also have a mentor/sponsor) is also amazing and very helpful.

    And lastly, (I promise that's the last comment!) they will bring professionals in to help you optimze your resume, your linked-in etc... and prepare you for interviews etc...

    Overall I am really happy with the program and glad they covered both Python AND R. I know some bootcamps do not teach R and the reality is that most companies use R and R is must. I am very grateful to everyone involved and working so hard to make this bootcamp a true success.

  • Shin Chin • Data Scientist • Student
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    I am really enjoying taking the NYC Data Science Academy data science bootcamp remotely. I find their online classroom and materials very effective for learning the fundamentals of data science. The videos are very informative and the material well communicated and taught by the lecturer. The accompanying slides are clearly written and mostly self contained and you can learn a lot, just by reading them. The course is a nice blend of theory and practical programming experience using R and Python and other tools.

    The learning process is aided by doing and submitting the homeworks for the lecture materials, as well as completing project assignments.
    I interact frequently with the TA assigned to me. We often have Google hangout sessions where he helps set up my environment on my laptop like Git, R and Python. We also review my project assignments through Google hangouts where he provides valuable feedback and suggestions. The TA is very helpful, competent and knowledgable.

    I would definitely recommend the online version of this bootcamp.

  • Dani • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    I attended the 12-week bootcamp this past summer and had a great experience overall. I was able to build a solid portfolio of data science projects and got a lot of job search support. The curriculum assumes a basic level of statistics knowledge so for someone like me whose background didn't include any it could be frustrating at times. However, they are serious about student feedback so I believe the course will only continue to get better. You can expect to put in a lot of work but as always what you get out depends on what you put in. Ultimately I landed a job I'm very excited about, and I had a positive experience with the course, instructors, and fellow students so I would definitely recommend it to anyone interested in a career in data science.

  • Jason • Research Scientist • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    Now I am going to start my new career as a data scientist.  I would like to share my 2 cents for this bootcamp and hope it would be helpful for the coming students.  Also I hope through those suggestions, you can have an idea about the bootcamp.

    1.  Be open - This is a boocamp, not a usual school class or an online course.  So share your experience and expertise with others.  You will learn much more from each other.

    2.  Be in a hurry - This is a short bootcamp, whereas it covers a LOT of content.  So be ready to work hard.  You need to have a sense of urgent that you are going to jump into interviews after 3 months.  Without your own hard working, it is hard to achieve the success after the bootcamp

    3. Be brave - This is a hard bootcamp.  Some students slept less than 6 hrs per day for three months.  Does it sounds scare?  However I would like to say that be brave, after learning with others, you will see your shining point and know how to show your merits to others.  So be brave to take challenges and be brave to share with others.

    4. Be collaborative - I hope after the bootcamp, you are not only getting a good job(s) but also getting a lot of friends.

    Enjoy the bootcamp,

  • Pokman • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    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 fellow aspiring data scientists on real-world projects.

  • Punam • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    Data Science Bootcamp was the best experience in my career. Instructers 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 enviroment. 

  • Sam
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    I took both Data Analysisand Machine Learning with Python with Vivian.

    I highly recommend these classes to anyone who wants to take their analytics skills beyond Excel, pivot tables, and averages and into more advanced predictive modeling methods. Luckily, a lot of the work has already been done for us by the developers who created pandas, matplotlib, statsmodels, and scikit-learn. I didn't know anything about these tools prior to taking this class. Vivian makes machine learning easy. At work I can now stand on the shoulders of Python's giants. Pretty cool. Extremely useful.

  • Machine Learning
    - 6/30/2015
    Liz • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    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.

  • Bret Fontecchio • Python Developer • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    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.

  • Anonymous • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    I spent three months there applied my knowledge on several interesting projects, including Kaggle competition and data visualization of new york crime analysis with shiny (R).  Also the students and instructors are inspiring and motivating.  It was a nice experience for me.

  • g"R"eat
    - 5/19/2015
    Anonymous • Student
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    I sharpened my skills by using different R packages to solve realistic projects.  It is a wonderful experience to solve those unique and challenging projects.

  • current student
    - 3/9/2015
    anonymous • student • Student
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    Great course so far! 4 weeks in and we've learned version control with Git, mapping in CartoDB, visualizations with D3, and machine learning, stats, and programming in R.

    We've also gotten to network with Data Scientists at Google and Enigma and we'll be featured on Interview Jet in a few weeks!

    Smart students and interesting projects are generating many strong portfolios for students. I don't think think any will have trouble finding a job when this is all over.

     

  • Anonymous • data science / technical writing • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    NYC Data Science Academy is a great choice for anyone looking for a bootcamp.  They look for students who have a science / engineering/ math background, but they don't require a PhD (though scholarships are easier to get for PhDs).  This school really distinguishes itself partly because of the emphasis on R.  People skilled in R command the highest salaries - and for a reason.  It is the gold standard for data manipulation and for all the most cutting edge algorithms.  I looked all over for a program that taught R (as well as Python) and NYC Data Science Academy is the only one I found!  Bootcamps are 12-weeks long and cover everything a data scientist needs to know to be up and running upon graduation, included R, Python, Hadoop, Raspberry, and much much more.  Vivian Zhang, the primary teacher and founder, is a great data scientiest, statistician, programmner and teacher.  She's also a great person.  Much of the emphasis is on preparing people to get jobs in data science and there is a lot of support in recruiting - including relationships with  firms Vivian has done corporate training for and partnerships with several recruiting firms.

  • Python Intro Class
    - 4/15/2019
    Anonymous • Student
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:
    N/A

    5-week class with Anthony Schultz. Solid class in acquiring the basics of python coding. Methodical weekly build coupled with Tony's patient approach made for a good base of python knowledge to move forward. Option of extra time before class to go through assignments or ask questions was very helpful. Does require concerted personal time to solve homework assignments for those with no coding background. Overall, would solidly recommend. 

  • Anonymous • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    Tony is a great insctuctor and makes basic Python concepts very accessible. My background going into this course was primarily in SQL, but I felt that the necessary Python concepts were covered quite well in the first session.

    The course provides an overview of the various uses and popular packages in Python and each week focuses on one area. I would recommend getting as much practice as possible early on with basic concepts like for and while loops, as this will prepare you best for the later weeks.

  • Anonymous • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:
    N/A

    I enrolled in this course with some working knowledge of machine learning, but no prior experience with neural nets or coding in Python. I thought this course was a great introduction to the topic, especially given that we were able to preview the instructor's forthcoming textbook on deep learning. Being able to go back and forth between the book and the lecture notes, and walk through the code together as a class, was really useful for solidifying newer concepts. The instructor was really approachable and friendly, and was good at drawing from various strengths that were present from other participants in the class. A great course, I enjoyed it. Would recommend to anyone who wants to get a high level intro to deep learning in a more structured setting than just an online course. 

  • Anonymous • Sr Software Engineer - Machine Learning • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    Attending NYC Data Science Academy is one of the most important and accurate decisions I have made in my life. The academy provides strong training on statistical and machine learning theory. Coupled with 3 real-world problem solving projects and 1 business-oriented capstone project, I gained hands-on insight on how data science address business demands.

    With software engineering background, I always want to relate my software knowledge to solve business problem. I believe the training at NYC Data Science Academy help me step forward my career path closer to what I want to achieve.

    I wish I can attend NYC Data Science Academy at a much earlier date.

Thanks!