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NYC Data Science Academy

New York City, Online

NYC Data Science Academy

Avg Rating:4.83 ( 265 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 (265) reviews for NYC Data Science Academy →

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  • 12-Week Immersive Data Science Bootcamp (In-person)

    Apply
    Start Date
    Rolling Start Date
    Cost
    $17,600
    Class size
    50
    Location
    New 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 monthsFull Tuition Total $17,600Skills Fund Student Loan$397.88 pm for 60 months
    Tuition Plans
    We have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months.
    Refund / Guarantee
    NYC 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.
    Scholarship
    Limited number of scholarships available to qualified candidates.
    Getting in
    Minimum Skill Level
    Ideal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming.
    Prep Work
    http://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/
    Placement Test
    No
    Interview
    Yes
  • Big Data with Amazon Cloud, Hadoop/Spark and Docker

    Apply
    Data Science, Python, Hadoop, Spark, Data Structures
    In PersonPart Time5 Weeks
    Start Date
    None scheduled
    Cost
    $2,840
    Class size
    N/A
    Location
    New 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
    Deposit
    N/A
    Getting in
    Minimum Skill Level
    Students are expected to be familiar with using an operating system from the command line; knowledge of Python is helpful.
    Placement Test
    No
    Interview
    No
  • Data Science with Python: Data Analysis and Visualization (Weekend Course)

    Apply
    Start Date
    October 27, 2019
    Cost
    $1,590
    Class size
    20
    Location
    New 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
    Deposit
    N/A
    Refund / Guarantee
    NYC 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 Level
    Knowledge 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 Test
    No
    Interview
    No
    More Start Dates
    October 27, 2019 - New York CityApply by October 25, 2019
  • Data Science with Python: Machine Learning (Weekend Course)

    Apply
    Data Science, R, Machine Learning, Artificial Intelligence
    In PersonPart Time7 Hours/week5 Weeks
    Start Date
    October 27, 2019
    Cost
    $1,990
    Class size
    10
    Location
    New 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
    Deposit
    N/A
    Getting in
    Minimum Skill Level
    Completion of Data Science with Python: Data Analysis; Data Science with R: Machine Learning
    Placement Test
    No
    Interview
    No
    More Start Dates
    October 27, 2019 - New York CityApply by October 25, 2019
  • Data Science with R: Data Analysis and Visualization (Weekend Course)

    Apply
    Data Science, R, Data Structures, Data Visualization, Data Analytics
    In PersonPart Time7 Hours/week6 Weeks
    Start Date
    September 7, 2019
    Cost
    $2,190
    Class size
    15
    Location
    New 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
    Deposit
    N/A
    Getting in
    Minimum Skill Level
    Basic knowledge about computer components Basic knowledge about programming
    Prep Work
    None
    Placement Test
    No
    Interview
    No
    More Start Dates
    September 7, 2019 - New York CityApply by September 5, 2019
    October 26, 2019 - New York CityApply by October 24, 2019
  • Data Science with R: Machine Learning (Weekend Course)

    Apply
    Data Science, R, Machine Learning
    In PersonPart Time7 Hours/week6 Weeks
    Start Date
    October 26, 2019
    Cost
    $2,990
    Class size
    40
    Location
    New 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
    Deposit
    N/A
    Getting in
    Minimum Skill Level
    Knowledge of Python programming Able to munge, analyze, and visualize data in Python
    Prep Work
    Knowledge of R programming Able to munge, analyze, and visualize data in R
    Placement Test
    No
    Interview
    No
    More Start Dates
    October 26, 2019 - New York CityApply by October 24, 2019
  • Data Science with Tableau (Online)

    Apply
    Data Science, Data Visualization, Business Intelligence
    In PersonPart Time5 Hours/week3 Weeks
    Start Date
    None scheduled
    Cost
    $1,590
    Class size
    20
    Location
    Online
    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
    Deposit
    1590
    Refund / Guarantee
    NYC 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 Level
    Know 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 Work
    Before 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 Test
    No
    Interview
    No
  • Deep Learning with Tensorflow (Weekends and In-Person Only)

    Apply
    Start Date
    October 19, 2019
    Cost
    $2,990
    Class size
    15
    Location
    New 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
    Deposit
    N/A
    Getting in
    Minimum Skill Level
    Object-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 Test
    No
    Interview
    No
    More Start Dates
    October 19, 2019 - New York CityApply by October 15, 2019
  • Introduction to Python (Online)

    Apply
    Data Science, Python, SQL, Data Structures, Data Visualization
    OnlinePart Time5 Hours/week2 Weeks
    Start Date
    None scheduled
    Cost
    $795
    Class size
    25
    Location
    Online
    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
    Deposit
    795
    Refund / Guarantee
    NYC 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 Level
    Comfort with Windows, Mac or Linux environment and ability to install third-party software.
    Prep Work
    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.
    Placement Test
    No
    Interview
    No
  • Introductory Python (Evenings)

    Apply
    Start Date
    October 21, 2019
    Cost
    $1,590
    Class size
    40
    Location
    New 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 / Guarantee
    NYC 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 Level
    This Introductory Python class is designed for computer-literate people with no programming background who wish to learn basic Python programming.
    Prep Work
    In 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 Test
    No
    Interview
    No
    More Start Dates
    October 21, 2019 - New York CityApply by October 18, 2019
  • Remote Immersive Data Science Bootcamp (Online)

    Apply
    Start Date
    Rolling Start Date
    Cost
    $17,600
    Class size
    25
    Location
    Online
    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
    Deposit
    5000
    Financing
    Climb Credit Loan $400* pm for 60 monthsFull Tuition Total $17,600Skills Fund Student Loan$397.88 pm for 60 months
    Tuition Plans
    We have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months.
    Refund / Guarantee
    NYC 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.
    Scholarship
    Limited number of scholarships available to qualified candidates.
    Getting in
    Minimum Skill Level
    Ideal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming.
    Prep Work
    http://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/
    Placement Test
    No
    Interview
    Yes
  • Remote Self-paced Data Science Bootcamp (Online)

    Apply
    Start Date
    Rolling Start Date
    Cost
    $17,600
    Class size
    25
    Location
    Online
    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
    Deposit
    17600
    Financing
    Climb Credit Loan $400* pm for 60 monthsFull Tuition Total $17,600Skills Fund Student Loan$397.88 pm for 60 months
    Tuition Plans
    We have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months.
    Refund / Guarantee
    NYC 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.
    Scholarship
    Limited number of scholarships available to qualified candidates.
    Getting in
    Minimum Skill Level
    Ideal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming.
    Prep Work
    http://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/
    Placement Test
    No
    Interview
    Yes

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Shared Review

  • Melanie • Data Science Modeler • Graduate
    Overall Experience:
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    Best decision I have ever made for my career. If you also have realized that the way we collect, analyze, understand, and utilize data will determine the future and potentially your career path too, this boot camp is what you need to do. I came in expecting a strict syllabus and skilled instructors but what I got was so much more. 

    My experience with the NYC Academy for Data Science was fascinating, exhausting, humbling, and rewarding. I learned more than I could have imagined and I made new life-long friends. Your fellows will be a colorful mix from across degrees, disciplines, and nationalities. That also means that you will hear and learn from different perspectives, which will expand your horizon significantly. All instructors and TAs (highly skilled, smart, funny, friendly, and fantastic) are there to support and help you with whatever problem you have and the syllabus is business-oriented to prepare you the best way possible for your future endeavors. After 12 weeks, you will know how to code, how to tackle data science projects, and how to communicate your findings effectively. You will also know how to manage Big Data or how to build complex Deep Learning algorithms.

    It won't be easy though and although they give you all the resources you need, it will be up to you how much you get out of it. So expect all-nighters, some frustrating and seemingly hopeless moments combined with desperate runs to the coffee machine. BUT IT IS WORTH IT. You can do anything for 3 months and if you put all you have into it, you won't regret a single minute. 

    I would do it again. Like I said, best decision I have ever made for my career. 

     

  • Dav D. • Graduate
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    I joined NYCDSA in late 2016, and there is no doubt about that the Data Science Bootcamp had helped me a lot in achieving my career goal. I was looking among several data science bootcamp back then, and my primary concerns were job placement rate, background of people who might join the bootcamp, and what industries had the alumni been working for. I decided to join NYCDSA because it gave me statistical answer of my concerns, not to mention how resourceful it would be speaking of its alumni network. 

    The only thing that I felt they could do better, well in 2 yrs ago, would be the career service, and the design of project groups. It would be helpful to arrange people with working experience with those who may not.

     

    The best thing about this program is its brand. I had several final-round interviews and some of the interviewers were from NYC. These interviewers, they know about NYCDSA, how the curriculum is organized, and how much practice students would receive from the bootcamp, so it is not challenging for me to leave some impression on them.

    If you are thinking about a career switch, enrichment of experience on resume, or just an investment towards personal skillset, NYCDSA is definitely the place where you would wanna go.

     

  • Anthony Tagliente • Data Associate
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    This is the second course I've taken with NYC Data Science Academy, they continue to offer excellent courses and materials.

  • Lee S-K • Student
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    I really enjoyed the Data Analysis and Visualization course.  I took the Intro to Python class with Tony a couple months ago, and this course (also taught by him) was a great next step in my journey towards hopefully becoming an expert in Python.  Whereas the first course gave us a great background in the basics, this one gave us a more concentrated ability to apply what we had learned to real-world problems (analyzing data and being able to display the results, which is more what you would do in a work environment).  Also, the opportunity to put together our own project at the end of the coures is extremely useful.  Highly recommend this course!

  • Raj Atri • Student
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    I've taken both the introductory and Data Science course with Tony and it's been an incredibly effective and fruitful introduction to coding. I'm at the point now where I am working on a different project with python everyday and am greatly looking forward to the next class i will be taking. 

  • Deekshita Amaravadi • Web/Mobile Engineer • Graduate
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    I took the Deep Learning Course from July - August 2018. This is a part time course for 5 weekends. Jon Krohn is an amazing instructor. I am a Web Engineer and have zero to little idea about Deep learning. For me to sit in class and not be intimidated by the course and fundamentals of Deep learning is a testament to Jon's teaching. The course is a really good starter kit for anyone looking to get into Deep Learning and AI in general. There is some knowledge of python that might be useful to have prior to taking this course as there are many live exercises worked on python. You will be given an opportunity to complete a project during the course which I suggest you do as it will make you apply the skills you review right after class that will make learning the concepts more enjoyable. All in all, I will 100% recommend this course for anyone who is looking to get a thorough overview of the fundamentals and philosophy of Deep Learning and its future.

  • Intro to Python
    - 7/24/2018
    Lee S-K • Student
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    The Intro to Python course was great!  Tony is a fantastic teacher who really took the time to get us acquainted with a new programming language, while simultaneously making the course challenging through both the in-class exercises and the homework assignments.  I felt the course was especially well structured, as each part really built on top of the last to provide us with a clear understanding of the basics of Python.  I highly recommend this course to anyone interested in starting on a path towards Python fluency.

  • Raajiv R • Graduate
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    I did not have experience in programming before this course. Had taken some courses in Java and pearl almost 9 years ago. I have a healthcare background and I was worried if this course will be advanced for an entry level. I can say now with confidence that this course not only taught me the basics of python and data analysis but also established a foundation to which I will be able to add advanced concepts in the future. I like the way the course was structured. Tony was punctual and the class always started on time. Tony encouraged us asking questions and was patient in explaining the concepts. Overall very happy with my decision to take this course and would recommend to anyone who is ooking to jump into the field of datascience.

  • Vera Feng • Student
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    As a Math major interested in Data Science, I've benefited tremendously from this course. Tony is a structured, detailed instructor. The course materials are practical and handy; and the lectures were helpful in both understanding the materials and honing up a programming mindset. I walk away from this class, feeling ready for challenges in my future job. I would strongly recommend this course with Tony to anyone who is new to programming and wants to have a head start. 

  • Dean Goldman • Data Engineer • Graduate
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    I could not be more satisfied with my experience at NYC Data Science Academy. I met incredibly impressive and interesting people, learned more than I ever thought I could, made friends, and worked very hard. Within a few weeks after graduating, I was offered my first full-time job as a data engineer. (I do not come from a CS, math or stats background).  

    NYCDSA is very succesful at getting their students fluent in the tools and technologies of data science, and prepared for finding great jobs in the field. The bootcamp is exhilerating, and the people are truly the best. By the end, you will be ready to for a data science position, and you will have broadened your horizons.

  • Lakshmi Prabha Sudharsanom • Data Scientist • Graduate
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    I took the 12-weeks bootcamp at the NYC Data Science Academy. I am a postdoc in India. I had been writing graph algorithms for social network analysis and analyzing data using MS-Excel. I decided to extend myself to data science from data analysis.

    I researched for about six months to choose a proper academy to learn data science. I came up with a decision to join NYC Data Science Academy, because I can learn both R and Python within three months. But, I learnt more than I thought. I gained hands-on experience in Python, R, SQL, Spark, deep learning, Hadoop and Hive.

    The materials are technically sound for job interviews. Many experienced professors and industry professionals design and teach the materials. The course laid a solid foundation in data science. The people in the academy show keen interest in every student to understand the concept, in resume writing and above all, to get a job.

  • Yisong Tao • Graduate
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    I attended the 12-week boot-camp at NYC Data Science Academy from Sep. 2016 to Dec. 2016. Before that I got my PhD in Chemistry and worked 6 years' as a Post-doc in biochemistry. 

    The curriculum was well organized. 12-week courses covered R and Python programming, statistical analysis and machine learning. During the last few weeks, big data tools like Hadoop and Spark were also covered. For one coming from academic background, the breadth of topics and difficulty level felt just right. The boot-camp courses weren't supposed to teach you everything, but they did prepare me very well if I wanted to explore further data science topics.   

    The boot-camp was intense. I was only sleeping for 4 hours during boot-camp days. It was demanding both physically and mentally, but I wasn't alone in the journey. The instructors, TAs and classmates were all amazing. This boot-camp takes students from very different backgrounds, which I think is a unique advantage. I was able to see people applying data science tools to their own expertise brilliantly, fashion, marketing, IT, health care... It was very helpful for me who was looking to step outside of academia. 

    The job assistance is good. There is networking, resume-editing and mock-interviews. Vivian also personally helps students tracking their job hunting status. I wasn't able to use lots of their services due to my personal situation, but for the one position I applied for I was able to impress the hiring manager with the machine learning knowledge and skills I acquired at NYCDSA and got an offer the same day. 

  • Great class!
    - 3/3/2018
    Chris
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    Great class. The instructor did a great job of keeping us on track and packing a lot of content into 20 hours. 

  • Mustafa Koroglu • Post-Doctoral Fellow • Graduate
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    The motivation in attending a data science bootcamp generally starts with reading testimonials, which are the experiences and thoughts of past fellows. I believe that my experience as a remote participant in the Summer 2017 bootcamp is unique as the NYC Data Science Academy made it live stream to me throughout the bootcamp. This is totally different experience than doing bootcamp online as I was able to join lectures, industry expert speaker sessions, and workshops as the fellows did in person. This was indeed great opportunity for me as I was able to ask my questions during the lectures and seminars and participated actively with my comments. The crucial point here is that live streaming the bootcamp and communicating through Slack channel made it possible for the team at the Academy to track my progress in the assignments and projects daily and encouraged me to participate fully in the bootcamp. 
     
    I can definitely say that attending the NYC Data Science Academy bootcamp was one of the greatest investments in my life. I learnt how to code efficiently in R and learnt coding in Python with real life projects. I am hundred percent sure that my attendance to the bootcamp let me to find my current data science related post doctoral position. I could suggest future candidates to take some initial online courses for machine learning and deep learning, where they will find themselves more comfortable while approaching highly-technical projects in the bootcamp. 
     
    One of the strongest side of this bootcamp at the NYC Data Science Academy is the time and effort that the hiring team spends on. For remote participants, this is much more valuable than any other thing as you are receiving constant help in finding best job depending on your portfolio. And you feel that you are a member of an excellent group of data scientist. As an active learner of data science field, I recommend the NYC Data Science Academy with full of confidence.
  • Al Mercado • Student
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    The approach in this course was more different that what I've seen in most workshops on this topic. It was more visual because Deep Learning sometimes requires mathematical derivations to understand the algorithms. I have read a few seminal Google papers on the topic and they're not alwasys easy to follow. John did not dive too much into this area and preferred to use powerpoint slides and diagrams by hand to explian it before we looked at the code.

    Overall the coding portion was made easier by John's coding style and we were able to follow along with the Keras modules. However, we did not get to cover all the topics (like autoencoders or deep belief networks) that I've seen other presentations get into and I would have liked to learn more. But the foucs on NLP and the last topic on GAN got me more curious about those topics. I would recommend it to those who want to learn it more and I would even be willing to talk about what I tried as a result of taking the course in any future session that he runs with a new group.

     

  • Former Alumni from Cohort 003 • Data Scientist • Student
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    I was previously a student in one of the early cohorts of for the 12-Week Data Science Boot Camp, and it was one of the best experiences for my career.

    Before going into lengthy detail, I will break this up into three sections: Before, During, and After in the hope of conveying a more comprehensive experience. 

    Before:

    Before attending the NYCDSA, I had just finished my undergraduate degree in an engineering field.  After taking an Intro ML course my senior year, I grew increasingly interested in the applications of AI and Machine Learning in industry.  When I discovered the field of data science, I was instantly hooked, but I knew I needed to learn more. 

    I had a decent amount of programming experience, mostly with low-level languages and systems, but lacked statistical intuition and experience with scripting langauges.  After some more digging, I knew that my skillset at the time would not be competitive for the actual job market.  While my undergraduate education was excellent, the curriculum was reasonably classic, most of my courses focused on theory and textbook problems and what I lacked was skills and experience for real-world applications.  While graduate school was an option, at the time I wasn't sure if Data Science was a field I wanted to commit more formal education to without experiencing it first hand.  So after applying to various boot camps, I chose the NYCDSA to jumpstart my career. 

    The interviewing process for the NYCDSA was simple and effective and included phone screens, code exercises, and some Q&A.  I chose this program because the company was relatively new and small and felt more like a community rather than a factory to churn out data scientists like other boot camps I came across.  After making my decision, I promptly moved to NYC after graduating and began my journey into data science. 

     

    During:

    The company was relatively new at the time I attended, but the caliber and experience of their faculty were top-notch, and it was transparent how passionate the staff was about developing the best and most efficient curriculum.  Within another couple of years, they were able to scale up, expand, and further improve their curriculum and course content at an exponential rate.

    It is important to note that your mileage may vary with any boot camp.  This program offers awesome resources, but ultimately it's up to the student to determine how much he or she will get out of it.  I spent an average of 60~90 hours a week on campus for the 12-week program.  The course is still manageable for people who have families or other commitments, and I have seen many successful part-time students graduate from my cohort.  I just wanted to note that this was particular to my experience.  

    The curriculum covers various aspects of data science and offers a cutting-edge foundational overview of stats, machine learning, and programming.  The core languages are R and Python.  The philosophy of spreading the breadth of languages rather than just choosing one is reflective of the fact that the tools in Data Science are highly mutable.  Rather than memorizing a single programming paradigm, the goal is to expand your programmatic and discrete logic intuition so that you can pick up other languages if needed.

    After class, the projects were engaging, and it was enjoyable to engage with other data enthusiasts and attend data science meetups and conferences together.  I still keep in touch with many of my cohort mates years after the program. 

    Moreover, Vivian and company have a robust network of many NYC companies and quickly expanding to other areas of the country.  By the 9th week, I've already had a couple of interviews lined up at top firms in the area and was able to practice and refine my onsite interviewing skills.  

    Three months after the boot camp, I landed my dream first job at a fast-growing tech-startup in Chicago after receiving multiple offers.

     

    After:

    After landing my role as a Data Scientist, I still maintained a close relationship with the NYCDSA.

    The support of the NYCDSA does not terminate at the end of the cohort, and they do a phenomenal job of providing ongoing support for their alumni and students.  After the boot camp, I've continued to receive ongoing help (practice interviews, coding exercises, access to review course content, network events, resume editing) which were crucial to my future employment.

    Not only do they offer support for students seeking employment but they provide support for education as well.  I was actively interested in an advanced degree in a field that leverages machine learning, and my experience at the boot camp only affirmed this for me.    Many of the faculty come from incredible backgrounds and are very willing to share their experiences.  Their advice and transparency were constructive in my choice of graduate program.  Currently, I am a part-time Masters candidate at a top data science program with a focus on Machine Learning and Data Ethics while working full-time as a data scientist at my current company. 

    The skills that I learned from the NYCDSA and later refined at my current company significantly prepared me for my graduate courses, allowing me to test out of basic classes and attend advanced topics in machine learning and statistics.   The skills from the boot camp carry over very well for most data science roles or education programs.

    In short, what I wish to convey is that a career in data science is a journey of continual learning and NYCDSA does everything they can to optimize the learning experience for their students.

    However, please note that the Data Science Bootcamp is tailored to provide balanced curriculum among programming, stats, and machine learning and is meant to be a program to strengthen core skillsets rather than a masterclass for already experienced data science veterans.  Although the company does offer more specialized classes in more targeted areas. 

    If you are looking for a program that will teach you everything there is to know about data science within a mere few months, then I'm afraid that those may be in general hard to find since data science itself is both a hybrid of multiple subjects and growing as a professional field. 

    On the other hand, if you are serious about transitioning into data science as a career and if you are seeking a program that offers competitive curriculum, a strong alumni network, and a community of data enthusiasts to engage with, I would strongly recommend looking into this program to jumpstart your career.  I cannot emphasize enough how much this program has benefitted my professional development both during and after the boot camp. 

     

     

     

  • Kathryn Bryant • Data Scientist • Graduate
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    Attending the NYCDSA 12-week bootcamp is the best career decision I've ever made. I came to it after finishing my PhD in math and working for a year in academia. I wanted to get into data science for lots of reasons (leveraging my background, interesting problems, ample job opportunities, interest in coding, good pay, etc.) but after spending six years in graduate school, the last thing I wanted to do was go back to school for two years to learn basic data science skills.

    This program allowed me to do this career change quickly without compromising the quality of the material I learned. The program emphasizes sound foundations in coding in R and Python and in both the theory and application of machine learning. The pace is very fast but you learn and do an incredible amount in those 12 weeks. Even when full absorption of the material isn't possible, the bootcamp does a great job of exposing you to tools and concepts you'll need to be familiar with later. 

    The projects are incredibly valuable for building skills and exposing future employers to your work. You would be spending your money wisely just to come and complete the projects.

    The bootcamp students and the TAs/instructors have varied backgrounds, which also makes for a great environment because you can learn from everyone. The entire company - from fellow students to TAs to instructors to the CTO and COO - is filled with smart, hardworking people who are pushing to help you reach your potential. 

  • W. Zhou • Informatics Specialist • Graduate
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    WHY Data Science and WHY NYCDSA: I had no idea about data science until 2016 Feb when Alphago defeated Li Shishi and it was the first time for me to get to know what is Artificial Intelligence and what is machine learning. Bringing my huge curiosity, I self-learnt an online Machine Learning course on Coursera and was able utilize the skill , for the first time, in my working project and had a positive outcome. Being proud of my achievement, I also realized there was still a long way down the road.  This is actually the reason why I decided to join bootcamp -  fully armed myself with comprehensive data science skillset and then shifting my career towards a new page. NYCDSA is a perfect choice for me as it teaches anything you need to know to work as junior data scientist and allows you to keep full time job as the same time.

     

    Experience: Even though it is an part-time online bootcamp, I was investing 40+ hours / week on studying slides, having office hour with TA and doing projects with current full time students. The bootcamp starts with an introduction Toolkits (Unix,Git,SQL,etc.), followed by introduction to R/Python, then followed by statistics and machine learning immediately applied using R and Python. The comprehensive curriculum is completed by an introduction to Big Data tools. I was able to finish a strong portfolio with 4 projects in Shiny App, Web Scraping, Kaggle and Capstone. I learned a lot especially by collaborating with full time students and TAs, so I would strongly recommend those online students who are physically in NYC, walk in the classroom and collaborate with full-time students on your last two projects.

     

    In terms of job assistance, NYCDSA can provide tremendous assistance on your job hunting after your graduation. Vivian and Chris know what you need to have on your resume to catch HR’s eye and get an interview, and they have a strong network which can expose you to much more opportunities.

     

    Outcome: I finally received offer from 2 Top insurance companies, 2 Top hospitals, and 2 boutique consulting companies. I feel my investment of 7 months of study and $16K totally worth as it allows me to finally launch my dream job. Thank you New York City Data Science Academy and I would recommend it to anyone who has same dream to be a data scientist.

     

  • Andrew Rubino • Data Lead • Graduate
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    I came to New York City Data Science Academy because I wanted to become a better coder, to  become more knowledgeable about machine learning, and to get a better job. Having completed the bootcamp in the Spring of 2017, I can say that through the Data Science Academy, I was able to accomplish all three.

    Before the bootcamp

    Previous to the bootcamp, I had a job as a data analyst which gave me the exposure SQL, Linux, Hadoop, and some Python - all tools that are taught in the academy. I knew I wanted to improve my overall problem solving approach, specifically using Python and R. After a few years as an analyst, and many months of debating if enrolling in a machine learning bootcamp was worth the time and money, I decided to go for it. Although I do not have a masters degree like many of my fellow cohort members, I knew that I could use my work experience to my advantage in preparing for the bootcamp. Like many others have stated, giving yourself enough time to go over the 100+ hours of prep work before the bootcamp is highly advised - being able to perform the basics of Python and R will set you up for success.

    Preparing before the bootcamp is also crucial in another way. As you spend more time studying, you spend less time doing all the other normal things you’re used to doing in your life. In order to make the most out of the bootcamp, sacrifices must be made, from your social life, to your eating and sleeping habits, and to the amount of coffee you normally drink. If you don’t get used to it before, adjusting to these changes midway through the bootcamp can be a challenge.

    During the bootcamp.

    If you spend enough time preparing before the start of the bootcamp, then the first month or so should not be too challenging (but still very useful). Many of my fellow cohorts actually became nervous, thinking that our investment in the bootcamp might not have been worth it. Don’t fret. After going over the basics again, the fun truly begins.

    After the first month, you will spend every day learning machine learning concepts, applications, statistics, and then applying these techniques in both Python and R. This is no easy task in a few short months, which is why the instructors, teaching assistants, and Vivian, deserve so much credit in churning out so many qualified data scientists in such short time. The instructors are always, at all times, helping and guiding you in the right direction. On top of that, you have the additional resource of working with your fellow cohort members, all who have unique backgrounds and always willing to help.

    In the end, the journey would not be worth it without days of extreme struggle and frustration. Some days I felt really confident in the material, other days I did not think I had what it takes to be successful. What I believe the instructors are best at is instilling the confidence in each and every student, spending as much time with you as needed to successfully complete the projects.

    The last few weeks are spent on tidying up your resume, github, blog posts, and interview skills. Aside from learning both R and Python in the bootcamp, one of the reasons why I chose the Data Science Academy was because of the strong professional connections that Vivian and the team have developed over time. The final day is dedicated to a networking event, where the ratio of companies to students is almost 1 to 1. Although it can be a bit nerve wracking, Vivian and the team do a good job of preparing you on what to expect.

    After the bootcamp

    I was lucky enough to land an internship at a startup as a data science intern from one of the participating companies at our networking event. I have to give my experience to the bootcamp all the credit for this. Had I not had relevant experience and projects to speak of, I would not have been able to land the job. As my internship was coming to an end, I spent more time with Vivian and the team doing mock interviews, going over practice questions, asking for help on take home assignments, and constantly reviewing. Without a doubt, I can say that the three months of the bootcamp was the second hardest thing I’ve ever done - the first hardest thing was getting a job afterwards.

    Vivian and the instructors have the uncanny ability of knowing what specific skills you need to improve on, based on constant back and forth communication based off of past interviews, as well as the interviews you eventually take. You will fail, and fail a lot. Most data science interviews are designed to test you on the very limit of your knowledge on data science subjects. With practice, you will answer the questions confidently, and even if you are unsure of a question, you will be able to communicate a thorough data science process on how you think the question could be answered. If you fail an interview, it’s another lesson on how to improve for your next interview, which Vivian will most likely have helped you set up already.

    After months and months of dedicating my life to all data science related activities, I have landed a job as a data lead at a media company, and have the entire NYC Data Science Academy program to thank for it. If you are seriously considering a future career in data science, then I can 100% vouch for the academy, so long as you are ready to work harder than you have ever worked in your entire life. At the end of the day, it’s all worth it.

     
  • Shivakumar Ranganathan • Graduate
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    Machine Learning is transforming the world at an incredible pace and I felt it was imperative for me to acquire new skills in order to be professionally relevant. The summer bootcamp fit my schedule perfectly and I decided to enroll to better understand this exciting new field. With a PhD in Engineering from a top-five ranked school and significant background in Computational Materials Science, I felt that I had sufficient background to be successful in the bootcamp. Due to my hectic schedule, I was unable to complete all the pre-work prior to the bootcamp and I believe that this had an impact in my learning experience at the later stages of the bootcamp. In my opinion, pre-work is analogous to binary decision trees—you are trained to be independent weak learners ahead of the bootcamp. The actual bootcamp is more like a random forest where individual students work alongside other students as well as Teaching Assistants and Course Instructors to significantly contribute on a variety of real world projects related to Data Visualization, Web Scraping, Machine Learning and Big Data. The course is fast paced and students are exposed to a variety of technologies relevant to Data Science. The instructors are knowledgeable and fellow students in the cohort are sharp. It is not surprising that NYC Data Science Academy is one of SwitchUp’s Top Bootcamps of 2017. I strongly recommend this bootcamp to individuals who are seriously interested to pursue a full-time career in Data Science.

  • Samriddhi Shakya • Data Scientist at QxBranch • Graduate
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    Going to NYCDSA is one of the best decisions I’ve ever made. Data science was completely new to me and I didn’t have a vey good programming background.  At NYCDSA, i was able to master both my data science and programming skills with the help of ever-present instructors, TA’s and friendly classmates. The curriculum was well balanced with all important data science topics, lab practices and mandatory individual projects included. In addition, they also had weekly coding challenges and professional development courses which teaches you how to  deal with interviews and present your self in the real world. The three months program was intense but is doable if you put in effort and dedication.  After the course, the academy also help you with your resumes and get interviews with companies within their connection. I highly recommend NYCDSA to all aspiring Data Scientist as this program helped me achieve my dream of becoming Data Scientist within 3 months after graduating.

    Cheers NYCDSA

  • Worth the effort
    - 11/7/2017
    Chris Lian • Graduate
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    I am a recent NYCDSA graduate. Before the retrospect. The outcomes first:  Know myself better, made great friends, landed a great job within 3 months, came back to the dream land……

    My story is a little different. The pre-DSA career is not bad at all.  I have had worked for a couple of top companies in the pharma and health industry for several years after getting my PhD. For some reasons, I am always thinking of expanding and tuning my fields. Life is quite dynamic that I recently moved to the east coast and happened to get stresses from various parts of the life. Rather than hanging there, I decided to challenge myself and make changes. I have thought of schools but it is not realistic for my situation.  I have studied some bootcamps and visited NYCDSA last year. The people there were very kind and down to the earth. I was not too confident at first but I would like to give a try. Therefore I gave up what I was doing, which was pretty risky and got a lot of doubts from people around me.

    But I always know very well and anyone should keep in mind that 3 months can hardly make one totally expert in data science, otherwise I will be willing to pay 10 times more. We should always keep learning; the effort will pay back.

     

    The course designs are up to date. They focus on practical data science skills.  The first month is about coding and analysis in R and python, which I found helpful in my case. After that, machine learnings have been emphasized on both python and R, then the big data part. Most of us are not directly from cs or math backgrounds. We had to work very hard for the classes in the morning, the homework at night and most importantly, the 4 projects with different emphases. We were pushed by the deadlines and harsh schedules, like the real world, have to come out the results before knowing everything.  I was the humblest guy during the 3 months in my entire life J. The instructors are very kind, helpful and always there to help. During the process, I have made some great friends, knowing people from such diverse backgrounds and also know myself better. Although I got my job on my own search according to my specialized interests and desires. The NYCDSA tried its very best to connect alumni and companies for the hiring. They have great connections. There are many alumni get jobs from the network.

    Suggestions and lessons: Once you have made the decision to attend the bootcamp, forget the past and dedicate yourself.  Always focus, do not doubt your decision for one second or look back.

    Skill is very important, but that’s not everything. Try to communicate, make friends and find out your strength well during the bootcamp. Design at least 2 of your 4 projects well, you know yourself the best, interact with the instructors frequently but do not solely rely on their ideas.  Do not live far, I burned myself out on the long trip every day. For the projects, try to team up with members most accountable, fair and those with high integrity and work ethics. If you share the common interest, that’s even better.  Do not judge others only by the technical or coding skills, it’s a teamwork, cultural fit is critical.  Last but not the least, we do pay a lot and might give up what we already have for the bootcamp. But when you get the quick reward in life, these pains with hope are abosultely worth it.

     

  • Dave L • Graduate
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    I came to the NYCDSA after having spent several fruitless years on the academic job market with a Ph.D. in English.  I was depressed and didn't really know where to redirect my career.  I had a background in math and a strong enough interest in data, but I knew that I needed to skill up, because that no one was going to take me seriously without another credential. 

    Despite my unusual background, the NYCDSA was very welcoming and helped me get unstuck.  I'm in a new, fulfilling career, and I couldn't have done it without this program.  By the end of the first year in my current job, I'll recoup the investment with respect to my prior earning power.

    The Good:

    1. The cohort my term (and, I suspect, for most) is a really excellent mix of people.  You have ex-academics, mid-career folks who are trying to reskill, fresh B.A.s who need to weaponize their math/CS skills; you have people from the sciences, from finance, from advertising; you have representatives of over half a dozen countries.  They bring a variety of talents, and you learn a lot from seeing what problems they want to approach and how to approach them.

    2. I've been in my current job about ten weeks, and I've already used most of the curriculum.  I use R every day, Python frequently, and a fair amount of SQL and Mongo. Good BI visualization can really set you apart, so the early part of the course has been most valuable. I've already done a fair amount of scraping, too, and occasionally contributed on some machine learning.  The only thing that would be useful for my job that the program didn't cover was JavaScript, but that's really more relevant to my field (advertising) than data science.

    The Solid:

    3. The instructors are all very committed.  There's a lot to learn, and they work hard to see that you get it absorbed.  I'm not wild about the setup pedagogically--three-hour lecture blocks make it easy to lose focus--and sometimes the instructors are not the easiest to follow as lecturers, but they put tons of work in, and it's appreciated.

    Could Be Improved:

    4. I know they try on job assistance--there's some work with resumes and interview prep, and they set up some interiews for you with their assorted hiring partners--but they don't seem to have the staff they need (at least as of my job run) to supervise it as well as they could.  To give an example, they didn't have a dedicated placement officer when I was there.  Job hunting is always terrible and unpredictable, but my impression is that some of the other camps (e.g., Insight) do a better job of minimizing the aimlessness and frustration it can incur. 

    Still, after three months in the program and three and half on the market, I got a job, and I wouldn't have done it without the academy.  It was an important stage in my life, and I'm happy I made the decision to go in.  It's let me move on with my life.

  • Katie • Data scientist • Graduate
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    What impressed me most about my experience at NYCDSA was that it exceeded all of the expectations I had from speaking with the instructors and researching the program online. The entire team truly went above and beyond and I have only positive things to say about the instructors, the curriculum, and the way the experience changed me personally.

     

    I found the instructors at NYCDSA to be not only incredibly knowledgeable, but approachable, thoughtful teachers. They seemed to really care about each student’s development and regularly stayed late in the evenings to offer help. If they could not be present in person, the instructors were always an e-mail/Slack message away and made it a point to check in with students and offer additional resources. I also liked that they not only taught the theory behind machine learning algorithms, but explained their most common applications and pitfalls to watch out for.

     

    The curriculum at NYCDSA is constantly updated to reflect the most valuable skills for the real world. I found during interviews that whenever I was asked whether I had experience with a certain data science technique or language, I could either say “yes” or show a project to demonstrate my skills directly. What I was taught always matched up with what was requested of me in the interviewing or working world. Even after the end of the bootcamp, I kept my slides and materials for review, and was provided with hundreds of interview questions to help me succeed going forward.

     

    Most importantly, the NYCDSA provided an amazing support group and helped me transform myself during a critical point in time. The other students were dedicated, kind, and came from all different backgrounds. I learned a huge amount from them and the instructors about the process of learning a skill like data science/programming and collaborating successfully. Apart from teaching the curriculum, instructors also provided resume reviews, listened to elevator pitches, and made themselves available to discuss interview experiences. I felt as though I had a whole village behind me, rooting for my success.

     

    I would without a doubt recommend NYCDSA to any friends or colleagues looking to learn data science. It was an exceptional experience and I feel grateful to have found it.

  • Yabin Fan • Data Engineer • Graduate
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    I would highly recommend anyone who wants to switch career to data science or strengthen data science knowledge to apply NYC Data Science Academy.

     

    Before I joined the Boot camp, two of my close friends already graduated from the program and landed their dream jobs. So unlike most of people who don’t know too much about this program and have to do some research before applying it, I applied the program without a hesitation and also had a high expectation as well.

     

    The curriculum design was excellent and really taught you how to learn new tech skills, frameworks quickly. It could be hard for people who are not exposed to programming or statistics to keep up the pace. Make sure to go through all the pre work and learn basic statistics before attending the boot camp. Once you started to work on your final project, you will notice that you’ve learned so much.

     

    All the instructors are very talented and very patient to students.  

     

    Vivian and Chris work hard to help you to find a good job once you’ve graduated. After you graduate, NYCDSA sticks with you.  Vivian and Claire emailed us frequently with new job opportunities and openings.

     

    It’s not going to be easy. You will have nights you have to stay up to finish the project, missed parties that you don’t have time to attend to. But it will be worth it! The knowledge that I’ve learned in 3 months are way more than my two years master degree and I got my dream job too.

    I’ve never regretted to attend NYC Data Science Academy. I’ve met so many amazing friends in the boot camp. It’s a very valuable experience to me in terms of career development and personal growth as well.

    If you are passionate about data science and big data and you are willing to put hard work to achieve the goal in a short time of period, there is no better place than NYC Data Science Academy to learn data science skills.

     

  • Andrew • Quantitative Programmer • Graduate
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    I went into the bootcamp with little more than a liberal arts B.A. and some online self-training. Within 6 months of finishing the bootcamp, I received multiple job offers and landed a dream job on the strength of my data science skills. The employer found me through the NYC Data Sceince Academy job network-- in that sense, the Academy continued paying dividends well after I had finished. 

    It is hard. When I read reviews that speak negatively the program, I suspect that they are from students who didn't put in the work themselves to take the many learning and job opportunities that NYC DSA provides. If you are willing to devote your time and effort to developing a new skill, you will be rewarded by this program. 

Thanks!