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NYC Data Science Academy

New York City, Online

NYC Data Science Academy

Avg Rating:4.85 ( 300 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.

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  • 12-Weeks In-Person Data Science Bootcamp

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    Start Date None scheduled
    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
    $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

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    Data Science, Hadoop, Spark, Data Structures, Python, Cloud Computing
    In PersonPart Time5 Hours/week2 Weeks
    Start Date None scheduled
    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
  • Data Science with Python: Data Analysis and Visualization (Weekend Course)

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    Start Date None scheduled
    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
  • Data Science with Python: Machine Learning (Weekend Course)

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    Data Science, R, Artificial Intelligence, Machine Learning
    In PersonPart Time7 Hours/week5 Weeks
    Start Date None scheduled
    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
  • Data Science with R: Data Analysis and Visualization (Weekend Course)

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    Data Science, R, Data Visualization, Data Analytics , Data Structures
    In PersonPart Time7 Hours/week6 Weeks
    Start Date None scheduled
    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
  • Data Science with R: Machine Learning (Weekend Course)

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    Data Science, R, Machine Learning
    In PersonPart Time7 Hours/week6 Weeks
    Start Date None scheduled
    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
  • Deep Learning with Tensorflow (Weekends and In-Person Only)

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    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
  • Full-time Online Data Science Bootcamp

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    Start Date None scheduled
    Cost$17,600
    Class size25
    LocationOnline
    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. Classes: You will learn 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
    • Full Tuition Total $17,600
    • Climb Credit Loan $400* pm for 60 months
    • SkillsFund 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
  • Introductory Python (Evenings)

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    Start Date None scheduled
    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
  • Part-time Online Data Science Bootcamp

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    Start Date None scheduled
    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
    • Full Tuition Total $17,600
    • Climb Credit Loan $400* pm for 60 months
    • SkillsFund 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
  • Nikhil Krishnan  User Photo
    Nikhil Krishnan • Student Verified via LinkedIn
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    Anthony was great - really got into the practical uses of python for data analysis and had really useful analogies to understanding different topics and concepts. Really enjoyed the class and felt like I could take something practical away from it.

  • Aungshuman Zaman  User Photo
    Aungshuman Zaman • Data Scientist • Graduate Verified via LinkedIn
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    First, a little about my background. I have a PhD in physics. In the years I spent in graduate school I had gained some experience in coding, statistics and data analysis. I did not have industry experience and was not really sure how to switch to the field of Data Science after so many years in academia. In the spring of 2018, when I was looking to join a Data Science bootcamp, I searched for programs which would put strong emphasis on both Python and R, and also provide me with ample opportunities to do project work, i.e., let me build a data product from scratch. The project part was particularly important to me because I felt that will be extremely valuable when interviewing for jobs. NYC Data Science academy seemed to fill the bill prefectly, so I decided to join them for the summer 2018 cohort. I will admit that I was a little sceptical about the utility of a 12-week bootcamp. But four months on, after graduating and now landing a data scientist job, I can unequivocally say that joining the bootcamp turned out to be a great decision for me. Of course in any intense bootcamp like this, it depends largely on you what you are going to get out of it. The thing the bootcamp does really well is to provide you with great resources-- very knowledgable and approachable faculty, a very good team of teaching assistants, good course materials, and excellent level of job assistance. Last but not the least, I had the chance to make a bunch of very close friends, who will form the backbone of my data science network for many years to come. I highly recommend this program specifically for people who are switching from academia.

  • Sophie Geoghan  User Photo
    Sophie Geoghan • Data Scientist • Graduate Verified via LinkedIn
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    I came to this program with a background in neuroscience, lots of coding in MATLAB, and lots of statistics but NO experience with Python, R, or most Machine Learning techniques. And I got exactly what I wanted to get out of it: lots of great practical experience in R, Python, various machine learning/statistics, and a confidence in approaching technical interviews. The program starts slow with Prework that is essential especially if one has never coded before, but also very useful even if you have experience in a different language (like me in MATLAB), and then it ramps up fast. By week 6 you've completed two aggressive projects in a data visualization app and web-scraping. The last two projects are ML-related and boosted my confidence in applying, evaluating, and discussing these techniques (very important for interviews). By the end, you are ready for the job search, and they were very helpful in getting us to make as many connections as possible. This program can be as challenging as you want - the materials and the instructors are there to help you succeed with as ambitious a project as you might want. Unlike university/regular school, they are not there to handhold or even grade you. They set the expectations and are there to help you meet or surpass them. I was mostly motivated by myself and my peers, who were a diverse and impressive bunch. I was happy to note that our cohort had a gender ratio of about 50/50, although depends from group to group. I ultimately chose NYCDSA because I wanted experience in both R and Python, and I am glad that I did. Overall, it was exactly what I wanted it to be, and I am very confident in my data science skills because of it.
  • Tracey  User Photo
    Tracey • Financial Engineer • Graduate Verified via LinkedIn
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    I have worked in financial services for 8 years and realized how technology has changed this industry so I decided to learn data science. With master in economics and CFA,  I think my weakness is programming and modeling, getting a proper training would be the most efficient way to make me a data scientist. While comparing a few bootcamp programs, I chose NYCDS for 3 reasons: 1. Great content: teaching both R and Python, also include hands on sessions for SQL, AWS, deep learning, NLP etc; 2. Great teacher and students: the founder and fellow teachers, guest teachers all worked on or currently working on data science projects in different industry, students having strong background with different domin knowledge; 3. The online full-time program fits my schdule after discussion with my manager.The skills I learned by completeing the 4 projects could be directly apply to my work.

    The 12 week bootcamp was intense, but I learned so much by pushing myself to my limit. I am not only self-motivated, but also motivated by my peers. I felt so exctied about the synergy between my and my teammates in group projects while working hard together. While achieving my goel of improving programming and modeling skills, I also becoming much more open-minded and not afraid to start from begining learning new technical skills at any time. After completing the bootcamp, I applied the skills I learned and created an application at work which is becoming a popular tool.

    NYCDS is very supportive, teachers, TAs, fellow students, alumni as well as the founder of the school can provide you any resource you need to help you achieve your goal. If I can redo this program again, the only change I will make is applying earlier. In this way, I can prepare myself longer in the pre-bootcamp training so that I can explore more during the bootcamp. This bootcamp is a life change experience for me. I highly recommend this program!

  • Alex Baransky  User Photo
    Alex Baransky • Graduate Verified via LinkedIn
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    Summary

    The NYC Data Science Academy is a wonderful organisation comprised of passionate and deeply knowledgeable people. Their curriculum is top notch, fast but fairly paced, and teaches the skills needed to be successful in any data scientist position. The course requires completion of four major projects which not only gives you real coding experience, but enables you to walk away from the program with solid evidence that you have the coding skills and knowledge of theory required to be successful in the field of data science. Along the way, you will make many new friends and you will expand your network of data scientists to help in your job search. If you work hard to make the best effort you can, three months from now you will be writing a review just like me about how you made the right call to join the NYC Data Science Academy.

    My Background

    I graduated with a bachelor's in Biology from an Ivy League school in December 2017. While looking for jobs, I realized that if I wanted to land the kind of research position I wanted I had a much longer road in academia than I had originally anticipated. I ran into an old friend who had completed a web development bootcamp and he told me to look into similar programs. After speaking with another friend who is a CTO of a startup, he suggested that I look into data science programs because of the increasing demand in the field. I had some experience coding in Java, but nothing crazy and I hadn't really coded in years. I have always had an interest in computers and I really enjoy the problem solving aspect of data science, so I figured I'd take the risk to change career paths.

    The Course

    I had three specific things in mind when searching for the right program for me. These were:

    1. Multiple projects throughout the program
    2. Reviewed highly by graduates
    3. Programming languages taught include Python, R, and SQL

    I think these are important qualities for any data science program, but they were specifically important to me because I was making the switch from a non-technical field.

    First, the projects were a must because I wanted to leave the program knowing I had something concrete to show employers. NYC Data Science Academy has 4 dedicated projects so that when you graduate from the program you have solid evidence of your skills as a data scientist. The last is a capstone project which allows you to work with a real business on a real business problem. This is a great opportunity to prove your worth as a data scientist.

    Second, I wanted to find a program that was rated very highly by its graduates. NYC Data Science Academy has some of the best reviews I've seen of any data science program, and for good reason. The instructors have a deep understanding of the material and they are both friendly and professional. The curriculum is as hard as it needs to be for a 12-week program, but the pace the instructors set is fair. The TAs are a tremendous resource and they are available for a reasonable amount of time to get your questions in. The course explores the most important aspects of data science and challenges you with case studies and coding challenges so that you can get a good idea of what to expect when you enter the industry.

    Third, I was looking for a program that taught Python, R, and SQL. These three languages are the most highly saught after in data science jobs I have seen, so learning them gives you a solid base for most opportunities out there. Many bootcamps offer Python, R, or SQL, but few offer all three. NYC Data Science Academy is one of those few.

    The Result

    I was originally thinking about using free online resources to teach myself data science techniques, but after going through the bootcamp process, I am extremely glad I made the investment. I was able to accomplish in 3 months what would have taken me over a year to do by myself. I was also pleasantly suprised at how close I became with my fellow classmates. They were all wonderful and intelligent people and I now have a close network of capable data scientists who I can call upon in the future if I find myself in a rut. This is a massively valuable resource that I didn't even consider when applying for the bootcamp.

    The job preperation workshops were also immensely helpful when preparing for the job search. Things like resume reviews, mock interviews, and coding challenges helped to ease me into the world of professional interviewing. I am now on my way to becoming an expert interviewer. There is also a networking event at the conclusion of the program which allows you to get in touch with a diverse group of companies looking to hire. The very next week after graduating from the bootcamp I was actively talking with multiple employers.

    I remember reading in a lot of bootcamp reviews that what you get out is what you put in. I will reiterate this because it is absolutely true. This program is not a day care, its purpose is not to motivate you or convince you that this is your path. This program is meant to supply you with all the resources and tools you need to be successful in a data science career. If you go in with the mindset that you will work hard and do your best to learn more material than you thought you could, you will be successful. NYC Data Science Academy has everything you need to be a success, you just need to make the effort to reach out and take it.

  • Silvia  User Photo
    Silvia • Data Analysis Intern • Graduate Verified via LinkedIn
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    The experience in NYC Data Science Academy is life changing for me. I am a graduate student in New York University studyng Psychology. Before I entered the bootcamp, I had almost none exposure to coding, programming, not to mention machine learning.

    The instructors are professional and helpful. Six weeks into this bootcamp, I found my current internship for a data analyst position. What I have leanred in the bootcamp helped me pass the technical interview and got me the job. I do appreciate it a lot. 

    If you come from a background that is barely related to data science, programming or statistics, this bootcamp will get you started on a career for a data scientist. Other than technical skills, the bootcamp will also provide you with an approachable platform for job opportunities. At the end of the bootcamp, there will be a hiring event where over 100 recruiters will come and talk to you. About 30-50% of the students will find a job on that event. Most of my cohort got an on-site interview from at least one company. 

    If you are looking for a job, then this bootcamp will be a perfect fit for you. 

  • Wenchang Qian  User Photo
    Wenchang Qian • Graduate Verified via LinkedIn
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    First of all, unlike many bootcamp students, I didn’t come from a background with coding or science, nor do I have a master degree. And I am currently a data scientist working at a startup, helping brands to understand their customers better through an emotional lens using Natural Language Processing. This definitely to certain extent proves not only the rigorousness of the course disciplines and the willingness from the bootcamp to go an extra mile to help the students who don’t come from a ‘regular’ background to succeed.

    I picked NYC DSA as the academy’s overall rating was simply the best across all data science bootcamps on the East Coast and the backgrounds of the instructors listed on the website were impressive to me. Coming from a business and consulting background, I consider myself very hardworking and competitive - I only wanted the best and NYC DSA was simply just it.  

     

    What I Loved about the Bootcamp:

    • The Depth of knowledge of the instructors, especially Aiko Liu (Aiko really influenced the way how I think about data science problems and he paved a really good knowledge foundation for us)
    • The Rigorousness of the course disciplines
    • The fantastic quality of classmates (they will be your best friends and your network after you graduate in three months)
    • The emphasis on solving practical business problems with data science skillsets (this is critical for you to find a job on the East Coast)
    • The partnership with big corporations for capstone projects

     

    Some Suggestions:

    • I wish the academy could focus less on R and more on Python. Maybe they have changed the balance currently. During the time of my enrollment, it was 50% R and 50% Python. Although R is a very useful programming language for statistical analysis and visualization, Python is the dominant language in the data science field. If you are just about to attend the bootcamp, I would suggest you place a larger focus on Python and practice data science problems with Python as much as possible.
    • I wish the academy could test or at least walk through some interview-level challenges/case studies methodologically to the students during the three months of experience. I believe this will not only prepare the students better in terms of what to expect from a data science interview, but also help the students start formulating thought processes related to solving data science problems.

     

  • Great Experience
    - 10/27/2018
    William Kye  User Photo
    William Kye Verified via LinkedIn
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    My experience with N?YCDSA with great. No bootcamp is perfect (there's a lot of information to pack in 12-15 weeks), but I thought NYCDSA did a great job of providing the teaching, resources, and curriculum to be a competitive job candidate after graduating.
     
    The atmosphere is very collegial where student and teaching assistant constantly are trying to help eachother and make sure everyone is getting the most out of the program. That being said, there is a lot of variance in where each student is coming from beforehand. So its important for each individual to seek help when necessary (which isn't very hard given how friend and accomodating the instructors are)
     
    After the bootcamp, Vivian and the others put a strong emphasis on putting us in the best position to succeed. Whether that was prep interviews, sending job postings, or just checking up. Overall would recommend!
  • Michael Chuang  User Photo
    Michael Chuang • Graduate Verified via LinkedIn
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    To begin, my experience with NYCDSA was excellent. The curriculum was comprehensive, instructors were knowledgeable,and my cohort-mates, friendly. I set out to attend a data science bootcamp after spending several years in tech consulting and at a marketing startup as an implementation and integration lead. I decided to attend NYCDSA particularly because it looked to have the most rigorous curriculum and advanced student projects compared to other camps I had looked into. With that, it was definitely a challenging and time-consuming experience but one that I am grateful for going through.
     
    On the whole, I thought the material was very practical and accommodated the wide spectrum of experience levels that my cohort contained (from fresh college grads to experienced PHDs). The course covered broad topics in data science with enough depth to be applied in the real world, so I now feel empowered to further my learning and tackle even harder data/tech problems after the camp. The instructors are all capable and are more than willing to help troubleshoot technical problems that will inevitably come up. The cohort is 40+ students so their time is obviously at a premium and you should expect to drive a lot of your own learning. However this actually made for stronger connections within my cohort as well since we were able to rely on each other to review our understanding of concepts, collaborate on projects, and have fun after hours. 
     
    After the bootcamp, NYCDSA notified me of many potential job opening as well as acted as a recommendation. I felt as though they were always prepared to support me given that I had everything prepared on my end as well. Obviously not every student will have a completely smooth experience with the job search process, but I’m confident that anyone who is willing to put in the effort and dedication in learning the material and crafting their applications will be able to advance a career in data after attending. Since graduating, I started a contractor role at Spotify, which eventually lead me to secure a full-time position at Facebook several months later. And while I put in considerable personal effort to secure these roles, I also know it would not have been possible with the skills and support I received (and continue to receive) from NYCDSA. 
  • Fan Zhang  User Photo
    Fan Zhang • Graduate Verified via LinkedIn
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    I had a truly rewarding experience at NYCDSA. The staff is professional and friendly, and the material is relevant for a wide range of data professions.

    Before I joined NYCDSA, I had researched and reviewed several other similar boorcamps. I think NYCDSA really cares and help you to success.

    The program helped me to open the doors to several opportunities for me and the staff sets time aside to help you position and present yourself well for job interviews. I have accepted good amount job interviews since I have graduated from NYCDSA, and felt very well prepared for the interview process. Five stars!

    If you are less familiar with coding (which I was), then you really need to do your pre-course very well. Because once the bootcamp starts, the foundation is very important. Patience and getting comfortable with the process of coding is absolutely essential.

  • Zhenggang Xu  User Photo
    Zhenggang Xu Verified via LinkedIn
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    1. Why NYCDSA:

    Before I made the decision, I did some research online (course report and switchup). I chose a few bootcamps with highly positive reviews and visited all of them. Finally I picked NYCDSA because the curriculum is comprehensive and the instructors are very nice to me during my visit. 

    2. My overall experience with the bootcamp

    1. The curriculum covers most of the items listed in the typical job descriptions/requirements of a data scientist. As long as you are good at these skills, you should be confident in the job hunting. Of course you need to put a lot of effort on developing the skills, and the bootcamp can give you a clear roadmap from programming 101 all the way to deep learning algorithms. Besides the regular coursework, you are required to finish 4 projects in which you can practice what you learn during the class, and get a good sense how to deal with real-life data. If you put enough time on it, you will be proud of yourself and impress other people by what you have done. They are not just some bullet points on your resume.
    2. The instructors are incredible. They have a deep understanding about what they are teaching, in both theory and practice levels. Students are always encouraged to ask questions during the class or outside of the classroom. Whenever I had questions they can give me quick answers almost all the time.
    3. I learned a lot from my classmates. The class profile of my cohort is highly diverse, from math PhD to Harvard MBA, from psychologist to investment banker. The common interest in data science gave us a chance to sit in the same classroom for 3 months. I made friends with many classmates, especially the ones I did group projects with. We learn from each other, share job information and interview experience with each other. I feel very privileged to study and work together with so many smart and interesting people here.
    4. The career assistance is great. The bootcamp did many different things to help us on job hunting, including job placement workshop, resume review, hiring partner event, alumni referral, even some online webinars when the bootcamp is over. I received several emails from the bootcamp regarding open positions every week. They also provide mock interview on both HR and technical sides. You job hunting will be much different if you make fully use of these resources.

    There are still more good things about the camp than I listed here. For people who want to switch careers to data science I sincerely recommend this bootcamp for you. Just make sure you spend enough time on the pre-work before you come to the class.

  • Xu Huang  User Photo
    Xu Huang • Data Scientist • Graduate Verified via LinkedIn
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    I learned about NYC Data Science Academy (NYCDSA) by googling. I was searching for more systematical training and professional hring guide in Data Science after taking numerous online courses by myself. I chose on-site NYCDSA bootcamp because 1. More efficient than Master Degree, 2. High reputation and reviews received from NYCDSA alumni, and 3. A perfect match for me who has advanced degree in STEM and wants to switch career. I'm so glad that I made the decision to join NYCDSA.

    One of the best things about the NYCDSA is that you are required to finish 4 intense main projects that cover nearly all the key skills you'll need for Data Science jobs and job searching: Python, R, Machine Learning, Big Data, Deep Learning, etc. I needed to show the best of what I'd learned and my coding skills to present, to learn how to collaborate with teammates who have different background and ideas, and more importantly, to meet deadlines! 

    After the bootcamp, I'm well equiped with an 'arsenal' for job searching: polished resume highlighting my Data Science projects & experience; professional links as your show case: GitHub, NYCDSA blog posts, etc; interview questions & exams, including one-on-one mock interview practice; connections with hiring partners and a whole set of job searching follow-ups and support...... I'm so lucky to have those helps from NYCDSA, and entire cohort of friends and connections.

    I highly recommend NYCDSA bootcamp to whoever want to seek/switch to career in Data Science.

Thanks!