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NYC Data Science Academy

New York City, Online

NYC Data Science Academy

Avg Rating:4.84 ( 299 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

Shared Review

  • 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. 

  • A great bootcamp!
    - 7/14/2020
    William Ponsonby  User Photo
    William Ponsonby • Business Analyst • Graduate • Verified via LinkedIn
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    NYCDSA is a fantastic bootcamp. I picked them on the recommendation of a former student and it didn't disappoint! It was a seriously tough 3 months, I had never coded before I started the course pre-work having just finished a humanties degree and they pack a huge amount in. With their syllabus the course should really be much longer than 3 months, so you'll need to spend time on the pre-work and also consolidating post-bootcamp, but they give you a solid base to work off and plenty of material to work through even after you've left.

    You get out what you put in to this course. I was often pretty exhausted and increasingly had no weekends! It was no picnic but definitely worth it as I now have a job at a consultancy specialising in data. 

    I think the best aspects of the course were that you could ask anyone for help, both students and teachers, plus the nature of the project work where you were also judged on your presentational skills. 
  • Sammy Dolgin  User Photo
    Sammy Dolgin • Graduate • Verified via LinkedIn
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    Very fast-paced, intense experience that gave a vigorous run-through of the Computer Science, Mathematical, Statistical, and Business-oriented skills necessary to break into Data Science. You won't graduate an expert, but you'll at have at least a baseline understanding of countless tools that you can continue to develop your understanding of upon graduation. The staff is VERY dedicated to student success and will go out of their way to ensure your understanding, and even more so if you approach them first. They do a good job building a strong sense of community among the students and faculty. If you're eyeing a career change or a way of breaking into the field, I'd highly recommend NYCDSA.
  • Kailun Cheng  User Photo
    Kailun Cheng • Graduate • Verified via LinkedIn
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     I have a biomedical engineering background, and I enjoy solving complex problems using quantitative methods.  I had decided to venture into the field of data science and machine learning because I realized that there are many processes that are insufficiently modeled in a deterministic way.  When I graduated with a Master's degree in Data Science, I had acquired many tools and methods in disciplines such as computer science and applied math; however, I was lacking some experience actually "doing" data science, especially in working with real-life data.  NYCDSA gave me the opportunity to obtain hands-on experience in the model building process.  I also had a great time collaborating with other fellows, instructors, and mentors on challenging projects, which further expanded my skill set in proper data collection, data retrieval, and data visualization.  Overall, NYCDSA fosters an enriching and inclusive environment for students of all different backgrounds to gain valuable experience that's needed for a data-driven career. 

    Regarding the job prospects post Bootcamp, I find it challenging in finding a suitable position in this ever-changing career field coupled with the tough economic situation.  However, I do think that NYCDSA is a great guide in pointing me in the right direction by providing the appropriate resources.   After graduation, a couple of recruiters reached out to me, and I was able to pass rounds of interviews with the knowledge I gathered from the projects I did in the boot camp. Ultimately, I'm able to receive a full-time data scientist position offer about three months post-graduation.  
  • Jae Ko  User Photo
    Jae Ko • Student • Verified via LinkedIn
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    I recently graduated from NYC Data Science Academy in March of 2020. Before I began my cohort, my background was in finance and was a novice in the data science/coding world. Though challenging and difficult at times the staff, instructors, and the TA's really helped me to push myself and assisted me to complete the program. 

    The curriculum not only covers coding and data science but the individual & group projects, presentations, and the helpful feedback is very advantageous in the real world. Also, I really appreciated how NYCDCA went what of their way in little things that can make a big difference such as: head shots, resume reviews, interview preps, strategy in job hunting etc...They did an excellent job of covering all topics and encompassing everything that comes with either career change or building up your current career. 

    From my experience, I only have positive things to say about the staff, instructors, curriculum, job support, and the community at NYC Data Science Academy and highly recommend NYCDSA to anyone who is interested in data science. 
  • Michael Link  User Photo
    Michael Link • Graduate • Verified via LinkedIn
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    This bootcamp helped me go from code illiterate to code proficient. The curriculum at NYCDSA is amazing. Trying to become an expert at anything in 3-months is nearly impossible, but NYCDSA does a pretty dang good job of presenting all salient data science topics and pairing these with four major projects that help to solidify your understanding. I was incredibly pleased with the quality of instruction and the expertise of the teachers. It felt like the instructors truly cared about my development and reception of the material. The career services team has been very very helpful. Like many things, you get out what you put in. I highly recommend this bootcamp, but if you do decide to attend make sure to complete the prework, devote 100% of your time to it (i.e. don't work at the same time), and put your all into each project. The four major projects (R Shiny, Python Web Scraping, Machine Learning, and Capstone) are important in how you market yourself post-bootcamp and were fundamental in giving me the confidence to say that "I am on my way towards becoming a great data scientist". Listening to lectures and understanding concepts can only take you so far, so make sure to befriend stack overflow, your instructors, and your keyboard as much as possible. Best of luck in your studies!
  • True Preparation
    - 6/22/2020
    Luke Gray  User Photo
    Luke Gray • Verified via LinkedIn
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    I graduated from the NYC Data Science Academy in September 2019. Though I lived in Austin, TX - home of many data science schools -, after vetting the success of past graduates and the credentials of the instructors at the Academy, I made the decision to temporarily move to New  York to attend this school. 
    The requirements and coursework was very intimidating, but certainly appropriate given the requirements to be an effective data scientist. The typical student spent at least 12 hours a day at the classroom to meet homework and project deadlines, but those hours were well-spent. Even though the difficulty in the material ramped up, the quality of the students' projects and in-class discussions definitely became much more substantive and impressive. The devotion of the students definitely rubbed off on each other, but the expertise of the instructors definitely helped foster that growth as well. It is also worth mentioning that the close alumni network also played a part in student growth.
    Beyond the hard skills learned (Git, Docker, SQL, Python, R, ML, etc ), the program required a lot of soft-skill development as well. Between developing effective presentation skills for our projects, and collaborating with our peers, teaching assistants and instructors, you truly learn what it means to become a data scientist amongst data scientists.
    It is also worth mentioning that they play a big role in your professional development as well. They devote a lot of time to your resume building, interview preparation, and student networking, and, personally,  I found the alumni presentations they prepared were some of the most insightful presentations I've had.
    If you are serious about becoming a data scientist, you go to this school. 
  • Simon  User Photo
    Simon • Graduate Verified via LinkedIn
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    I graduated from NYC Data Science Academy in September 2019. I was recommended by a friend of this bootcamp, as he told me that I will be able to learn a full spectrum of skills needed to enter a data-related job. Having almost finished my Master in Statistics, I wasn’t sure about the tools needed in the industry, because the master program focuses very much on theory but not on the practical tools.  Hence, I was very glad to be introduced to a toolkit of data science skills, those of which will be very applicable to any data science/engineer jobs in the future. One thing I really liked about the program was its intensity. I understood that students coming to this bootcamp came from different backgrounds, some of which might find it a bit challenging. For someone who has background in statistics and a little bit of computer science, the pace was very good because I could learn a lot of things within 12 weeks, bombarded by one project after another. I really liked the instructors here, especially Luke Lin and Zeyu Zhang, as they were so knowledgeable and patient. I also made many friends here, especially for someone who just moved to New York City. 
  • Oleksii Khomov  User Photo
    Oleksii Khomov • Graduate • Verified via LinkedIn
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    NYC Data Science Academy’s program covers more material than any other leading bootcamp. Curriculum is created with long-term professional development in mind, while at the same time being incredibly “up-to-date” with all the latest developments in the industry. Thanks to the things above, bootcamp positions students for immediate success right after the completion of the program, while keeping on serving their career in the long run. In other words, NYC Data Science Academy’s curriculum includes some extra components, which are essential for getting a job at the top companies in the industry (e.g. FAANG). 

    In addition to the core of the program, NYC Data Science Academy also offers practical and extensive preparatory material (already included in the price of the bootcamp). Thanks to these materials students are capable of building a strong foundational knowledge of the core material, and as a result, have a much easier time during the program.

    One of the greatest advantages of NYC Data Science Academy’s bootcamp is the group of extraordinarily supportive teaching assistants. Since 100% of teaching assistants are former bootcamp students, they possess a unique understanding of anything that current students are going through at any given moment. 

    Another pivotal part of the program is its amazing collective of instructors, most of whom possess advanced degrees and multiple years of industry experience. No other place creates such a remarkable mix of academic and industry knowledge that allows students to not only learn how to code but to understand the underlying principles of the scientific and business processes. 

    Last but not least, is the selection of projects that students have a chance to complete during the bootcamp. These projects not only allow students to apply newly-learned coding techniques but also push them to solve “real-life” problems and to create industry-specific practical solutions. Bootcamp has a healthy mix of individual and group projects, which gives students a chance to work with different kinds of dynamics, and most importantly to learn from fellow students. 

    Overall, the unique selection of material, amazing teaching and supporting staff, along with the ability to be among a diverse group of people with all sorts of professional backgrounds is what distinguishes NYC Data Science Academy from the rest.

  • Sunny Lee  User Photo
    Sunny Lee • Student • Verified via LinkedIn
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    Before thinking about any kind of bootcamp, my background was in finance and I wanted to brush up on coding skills and my statistics knowledge. Once I decided I wanted to explore careers in data, I spent an insane amount of hours researching and talking people. I was scared to leave my job without any guarantee of getting a new job. Ultimately, I chose NYCDSA, and looking back, I am very grateful that I did. The people that I talked to from admissions were friendly, informative, and helpful. They were empathetic about the fact that this was a big step and they were not pushy or sales-y at all, which was very refreshing compared to some of the other bootcamps. During the bootcamp, the instructors and TAs were very invested in the students. They helped me think through project ideas, review concepts, fix a bug, and all of the above. I came out of the bootcamp with Python, R, and SQL skills along with a portfolio of projects that I wasn't embarrassed to talk about in interviews. The hard part of networking, interviewing, and studying for a new job doesn't go away - but NYCDSA gave me the tools and the job support to feel confident that I can do it. I've learned so much more in the 3 months than in the one year I tried self-studying for a career pivot. I've also met a great group of friends and people while doing so. Even with COVID, which forced our cohort to go online for the last 2-3 weeks, I was able to get a handful of data scientist and data analyst interviews.   I went in with the goal of making a successful career pivot and they've helped me accomplish exactly that as I accepted an offer at a new firm which I'm very excited about. 
  • David Levy  User Photo
    David Levy • Data Analyst • Graduate • Verified via LinkedIn
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    I have nothing but positive things to say about the instructors, curriculum, job support, and community at NYC Data Science Academy! 

    From day 1 I felt welcome and part of an extended family. While the curriculum is incredibly challenging; the instructors, classmates, and even alumni are ALWAYS there to help guide you through it. 

    Like most things in life, you will get what you put in. If you work hard and embrace the collaborative community NYCDSA has built, you will be incredibly well-positioned for success in the Data Science industry.

    I secured a role as a Data Analyst at FanDuel Sportsbook 2.5 months after graduating from the program. We have now hired another NYCDSA graduate and will be looking to continue to build this pipeline in the future!

    Thank you NYC Data Science Academy for changing my life. 
  • Austin Cheng  User Photo
    Austin Cheng • Student • Verified via LinkedIn
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     I picked NYCDSA because it offered the most comprehensive curriculum. Surely, the amount of content introduced was overwhelming especially in the second half of the bootcamp but with unwavering dedication and commitment, which was pretty ubiquitous and contagious in the bootcamp, the workload was just about manageable. I would describe myself as having a relatively strong quantitative background as I have a PhD in physics (though my knowledge of statistics and coding in general is abysmal), the coursework was still challenging. I would also confidently say that the coursework is taught in a way to be conceptually accessible by all. The bootcamp teaches two popular languages (Python and R, some SQL) as well as the core concepts of machine learning. The machine learning topics are taught with a good mix of qualitative and quantitative reasoning. The students are required to do four intense projects along with many exams and homework. Overall, the bootcamp sets up the students well for future success-- it gives us the foundation necessary to continue to grow as data scientists. The job support is unexpectedly great. The bootcamp works with us personally to become competitive candidates for the job market and also actively makes work connections for us. The instructors are beyond amazing as they rise above expectations always. They make you feel that they are truly responsible for your understanding of the topics and they are very open to feedback (in fact, they actively look for it). In hindsight, as a more experienced data scientist and knowing that there is only 12 weeks, I wish that we had focused purely on Python and SQL, and spent more time on coding challenges, algorithms, case studies, AB testing and big data techniques. There were duplicate content taught as we switched between Python and R though for some this may be good because repetition of topics with a different spin can help with better understanding and retention. And despite saying I wish we focused purely on Python, working with R and having the knowledge to use R Shiny was what ultimately made me more attractive as a candidate since I was able to showcase my work as an app. All this back and forth rambling probably just means that 12 weeks is very short and given that the field of data science is growing so quickly, it's really hard to gauge what exactly and what amount to master. Given this situation, if I turned back time and had to decide all over again where to invest my 12 weeks of time, I would without any doubt pick NYCDSA. With their expertise, receptiveness, hustle and attitude of wanting to do what's best for us, I truly believe that any student there will be in good hands. 
  • Jun Kui Chen  User Photo
    Jun Kui Chen • Data Analyst • Graduate • Verified via LinkedIn
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    I was in one of the online bootcamp cohorts. Before I registered for the bootcamp, I just finished my graduate school in a biomedical related major. I liked doing data analysis, but I quickly found out that there was a gap between what I knew and what the industry wanted. Therefore, I decided to choose a bootcamp to ramp up my technical skills. I decided to join NYC Data Science Academy because it offered a very competitive curriculum that included Python, R, SQL, Spark, Hadoop and Hive. The projects we did, which includes Rshiny app, web scraping, machine learning, and a final capstone project, are a good portfolio that students can present to potential employers and those skills can be directly applied to work. 

     It was hard to keep up as I was also doing a full time job while attending the online bootcamp. NYCDSA provided many service to keep students on track. One of the service I like the most is the TA assistance. I was paired with a TA and we met regularly to go over my progress and the questions I had. My TA was also a NYCDSA student before and was working in the industry as data scientist. Therefore, he not only knew what my struggles were on the course work, and he also taught me a lot of practical experience that was using in the industry.   

Thanks!