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NYC Data Science Academy

New York City, Online

NYC Data Science Academy

Avg Rating:4.84 ( 332 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
  • Worth It
    - 5/31/2021
    Steven Lantigua  User Photo
    Steven Lantigua • Graduate • Verified via LinkedIn
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    I graduated from the 12-week remote live program in December 2020 and I highly recommend it. The program is intensive but well worth the challenge. 

    Prior to NYCDSA, I had just finished my undergrad and was looking to break into the data science field. At the time, I had a strong quantitative background and a decent foundation in programming but was missing tangible data science projects/experience. I found myself gravitating more towards this program than any other Bootcamp because the time frame worked perfectly for me, and after cross-referencing them and their alumni, they seemed legit. 

    My overall experience throughout the Bootcamp was positive. The instructors knew what they were talking about and taught it well. Additionally, the optional homework they provide helps reinforce what they teach. One thing I want to highlight is their willingness to stick with struggling students. There were several instances where I didn’t understand a particular machine learning topic and I was able to schedule time with an instructor to hash it out. It was these talks that cemented the conceptual part and ultimately made implementing these concepts much easier. 

    However, what most impressed me was their post-Bootcamp curriculum. They don’t just take their students’ money and leave, NYCDSA provides supplemental material that helps prepare newly graduated students for interviews. Additionally, Vivian scheduled weekly zoom meetings to advise us on our job hunt and keep us accountable. It was these accountability meetings where gems lie and what truly helped me with my search. Vivian went above and beyond to make my job search more efficient and successful, taking time out of her schedule to work 1 on 1 with me as a mentor. I’m truly grateful and highly recommend this program! 

  • Shameer Sukha  User Photo
    Shameer Sukha • xVA Management Group, CIBC • Student • Verified via LinkedIn
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    After 18 years of specialist experience, I was starting to develop a FOMO with Data Science. After some research and recommendation from a friend who completed this program I decided to enroll. No doubt, this will change my life. It was liberating and the 6-month investment was well worth the tuition fees. The instructors were experienced and curriculum was cutting edge and the program 'forced' me to keep pace with my learning and successfully complete it. It was hard, because I have a demanding job on an xVA trading desk at an investment bank but this was a necessary investment in the skills for the future. There is no limit to the applications of Data Science and I encourage more executive-level candidates with strong business experience and some STEM experience to challenge themselves. You will not regret this and I suspect that it will open up many doors for your future endeavours.
  • Sita Thomas  User Photo
    Sita Thomas • Data Analytics Manager • Graduate • Verified via LinkedIn
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    I did the Interactive Distance Learning (IDL) program in 2020, so keep in mind that my experience was strongly influenced by the COVID-19 pandemic. I am a career switcher from the health services industry - this bootcamp got me into the tech industry 2.5 months after completion of the program and taught me fundamental coding and machine learning skills as well as advanced statistics skills. That said, for the IDL course, because it is relatively self-paced, you get out exactly what you put it. I am highly ambitious and set myself up for success really well. Not everyone does. The content, instruction, mentorship, and community engagement are excellent and only getting better - these people are absolutely well-versed in their fields, care extraordinarily deeply about the success of their students, and are constantly iterating. I gave the program 4 stars because I did feel like there was an institutional bias toward the Remote Live Instruction students - when I was there, those students got access to internships and other resources that IDL students did not even though we pay the same tuition. Perhaps it has changed, but if you want the best chance of being noticed, the Remote Live course is the better choice, while if you need flexibility and are okay with a little less support, IDL is still a fantastic choice. Their career and alumni services are also top-notch, but again, only if you take advantage of all the resources.
  • Xuyuan Zhang  User Photo
    Xuyuan Zhang • Graduate • Verified via LinkedIn
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    Before joining the program, I was a student majoring in Business Analytics. I had a hard time finding a data analyst position and therefore I was thinking maybe I was not qualified for a data-related job yet. My friend recommended this Bootcamp to me and when I check out the course curriculum I knew this is exactly what I was looking for. The courses are very comprehensive, covering topics including web scraping, data analysis & visualization, machine learning, and big data. I felt so lucky that I got enrolled in this program and I would never regret for this choice. Although the content of the courses is challenging, all the instructors are there to help you. I did improve my coding skills a lot through projects and I also added new skills to my profile through courses. I would recommend this Bootcamp to anyone who wants to get into the data science field.

  • Jon Harris  User Photo
    Jon Harris • Business Intelligence Developer • Graduate • Verified via LinkedIn
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    For the better part of the past decade, I worked as a medical researcher both in an academic setting and professionally for a company. While I had a strong foundation in mathematics and statistics, I lacked the rigorous coding, experience with relational databases, and machine learning knowledge to pivot towards a career in Data Science and business analytics.

    Before the Bootcamp, I tried teaching myself R through an impersonal, distant online course with limited success. While the experience convinced me that I wanted to make the career leap, the online course did not allow me to ask questions to further my understanding. In Dec 2019, I quit my job, moved to NYC, and enrolled in the NYC Data Science Academy (NYC-DSA). 

    My reason for choosing NYC-DSA was rather easy. While some boot camps offer the option to study data science among other UX, software, or cybersecurity career routes, it was important for me to know that my entire tuition would fund my data science education - that the resources would only support the recruiting of college professors and Ph.D. lecturers, career development professions, and teaching assistants. Secondly, NYC-DSA was one of the only boot camps to provide analytics on previous student cohorts, emphasizing the program's accountability to find me the best jobs, not just take my money. Additionally, NYC-DSA had a rigorous but fair selection process to ensure that the cohort had a capable background in mathematics, coding, statistics, and a wide array of professional and educational experiences. The cohort's diversity made the experience particularly valuable as each person could provide insight into how data science is applied in their respective field. Lastly, I chose NYC-DSA because they were the only boot camp that taught both Python and R, in addition to SQL. The ability to learn both languages ensures that students are not limited to certain industries because they only know one language - in fact, my current job frequently requires that I code in both languages.         

    After the 1st day at NYC-DSA, I was not disappointed in my decision to attend NYC-DSA. The instructors were beyond impressive, many with PhDs in Mathematics, Physics, or Statistics, and with professional backgrounds in Biology, Finance, and Marketing. Unlike my previous engineering or college courses,  the professors were engaging, frequently made jokes to lighten the mood, and were immediately relatable. The boot camp made an effort on Fridays to provide food and drinks at the end of the day and emphasizes socializing with other students and the instructors themselves (come to find out, they are also people, haha).  

    I decided to attend a coding boot camp because I wanted to educate myself and ultimately change careers. Finishing the boot camp in April 2020, at the beginning of COVID-19, when NYC and the economy shut down, was not easy. In fact, it wasn't easy - NYC-DSA would send out monthly job reports of NYC/SF/etc., showing 50-70% fewer job postings from the year before. Despite that, the career development team at NYC-DSA could not have been more helpful in ensuring that I had the best possible resume, cover letter, and application package for each job listing. For nearly a year, I would meet 1-2x a month with someone at the boot camp to go over my applications and how I could better utilize LinkedIn to network and reach out to recruiters. Several of my job interviews resulted from the lecturers recommending me for a job they heard about. If the boot camp knew I had an interview at a company coming up, they would get me in touch with a current or former employee to better prepare myself for the interview process. After nearly a year and hundreds of job applications, I landed two job offers on the same day for nearly $40k/yr more than my previous salary - largely through the networking I did through the boot camp. 

    The boot camp was hard; it was an excruciating three months of getting to the camp at 9 am, frequently staying until midnight, coming on the weekends, etc. But all of it was worth it, thanks to the dedication of the faculty, CEO, and students at the New York City Data Science Academy.        

  • Bootcamp Student
    - 4/7/2021
    Philippe Heitzmann  User Photo
    Philippe Heitzmann • Student • Verified via LinkedIn
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     I recently graduated from the NYC Data Science Academy online part time bootcamp program and can attest to a very positive experience with Vivian and team. In case helpful for future students considering this bootcamp program, here is a breakdown of different considerations concerning my experience at NYCDSA: 
     
    1. Why I picked NYCDSA 
    NYCDSA appeared to be the only bootcamp program that taught both Python and R at the time I was considering enrolling in a data science bootcamp program, which I expected would provide the best optionality in terms of choosing a data science framework both best fit for me and best fit for the industry I would want to integrate both graduation, as the public sector / academia generally lean towards R while private sector and tech industry broadly generally lean towards Python. The NYCDSA curriculum further appeared well structured and paced for someone in my position just learning how to code and getting a first exposure to data science concepts. 
     
    2. Overall Experience 
    Vivian & team create an incredible learning environment with in-depth & concise lectures providing detailed overviews of multiple essential data science frameworks such as Python, R, SQL, Docker, AWS, Hadoop and Spark. The team further goes above and beyond for students during the job placement process, such as for instance making themselves available to answer student questions on personal projects and case studies, promoting student projects to recruiters and alumni on their LinkedIn page or providing students with opportunities to present projects to recruiters and alumni. The mentor meeting credit system connecting students to alumni in 1-on-1 30min or 1-hour sessions is especially well designed for students just getting started in data science and provides good opportunities to ask questions and review any material with an industry professional. Overall the lectures are well-taught and provide concise overviews of the analytical frameworks and knowledge necessary to perform in a professional data science environment, while the hands-on labs and projects do a great job of providing students the opportunity to practice learned coding skills. 
     
    3. Skills learned 
    The bootcamp does a great job of providing ample opportunities to practice coding skills through projects and labs and I was able to develop strong proficiency in Python, SQL, R and Docker through these various projects, coming from a mostly non-coding undergraduate background, which I was able to apply directly after graduating working as an intern with a tech startup and finally in a full-time data scientist capacity at a large financial services firm. 
     
    4. Post-graduation plans 
    I received a data scientist job offer at a large financial services company three months after graduating from the bootcamp after initially working as an intern at a data science startup and could not be happier with the outcome. Vivian and team are truly special and I could not be more thankful for an amazing experience over the course of the past few months. 
  • Worth every second
    - 3/31/2021
    Sofia Wang  User Photo
    Sofia Wang • Business Intelligence Analyst II • Graduate • Verified via LinkedIn
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    In short, the bootcamp excels on the curriculum, providing guidance, and career services. I found this bootcamp online, and I decided to go for this one because of the curriculum and the feel of it during the assessment process - they sounded like they knew what they were doing! They provided valuable feedback on the areas I needed to improve.

    I have a math degree and was already a Sr. Data Analyst, but wanted to move a step forward in my career by learning Data Science and Machine Learning. What I liked is that the coursework is tailored to each person depending on their experience, strengths and weaknesses.

    I went for the part time program since I was also working, and I am not going to lie, it is challenging! But worth it. Throughout the bootcamp I learned of many DS/ML concepts that are widely applied across different roles and companies, the projects assigned were the best way to apply and practice the things learned, and I eventually was able to apply them in my own job. They also offer TA sessions that are very helpful to review on the parts that seem confusing. One thing to note is that because of the extensive material taught condensed in a short period of time, studying extra materials is needed in order to get the most out of the bootcamp. Upon graduation, there are helpful resources on landing the next job - mock interviews, career advising, and networking. 

    I landed a job at The Trade Desk as a Business Intelligence Analyst thanks to the stories I was able to tell of the projects I worked on in the bootcamp, the projects I worked on my previous role with the bootcamp knowledge, and with the various mock interviews (I was very bad at interviewing).

  • Hong C. Kim  User Photo
    Hong C. Kim • Graduate • Verified via LinkedIn
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    In my mind, there is no such thing as a perfect bootcamp but NYCDSA got as close to perfect as it can get for me, which is why I gave it a 4 star. The curriculum is the most comprehensive of all the data science bootcamps available and covers topics that are the most practical for job search. What students learn at schools are often not used in real world settings. NYCDSA gets this so its curriculum focuses on skillsets that graduates can apply directly at work but also offers materials for those who want to take an extra step and learn about non-practical aspects of data science. Instructors are all well qualified to teach and mostly do a great job but the only thing I would say is the pace of learning could be overwhelming for some students if they don't take the time to review the materials before and after each class. Doing the homework, which is optional, reinforces the learning. This three pronged approach of lectures, homeworks, and projects positions the students well for a data related job post graduation if they put in the work to complete all of them. Lastly, the career team does a fantastic job guiding the students through the job search process. The team knows what works and what doesn't, so as long as students follow the guidelines, the prospect of finding a data related job is very high (bootcamp has statistics on this). Overall, I'm very satisfied with the experience and would recommend the program to anyone who's looking for a new career path or looking to add a new skillset.
  • Gregory Weber  User Photo
    Gregory Weber • Data Analyst • Graduate • Verified via LinkedIn
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    Before my NYC Data Science Academy Bootcamp Experience, I was a high school mathematics teacher.  In order to make informed pedagogical decisions, I increasingly relied upon data collection and data analysis.  This sparked my interest in data science.  Since I enrolled in the Summer Session of the Bootcamp, I was able to continue to receive my teacher salary for most of the 12-weeks.  

    After making the decision to enroll in a bootcamp, New York City Data Science Academy quickly became my top choice for the following reasons:

    Multiple Languages (Python and R)
    I appreciated the emphasis on learning both Python and R.  When searching for a position, this increased the number of jobs I was qualified for, and I used both Python and R during the Technical Assessments of my job search.

    Pre- and Post-Bootcamp Support
    From my research, I was convinced I would be supported before and after my bootcamp experience...which was true!  

    Pre-Bootcamp
    I had no previous programming experience, so I enrolled in 2 helpful introductory courses at the NYC Data Science Academy, one for Python and one for R.  The price for these classes was subtracted from my Bootcamp tuition.

    Post-Bootcamp
    During the final Capstone Project, many students elect to work with outside businesses that partner with the NYCDSA.  The company I worked with offered my team an additional 2-month, post-bootcamp data science internship.   This was a great learning opportunity, plus a great addition to the resume!

    Months after my bootcamp ended, I was able to participate in a free, 2-week intensive,  marketing-focused workshop led by NYCDSA Bootcamp Founder Vivian Zhang (open to any graduated bootcamp student).  The workshop was filled with marketing domain knowledge and practical applications.

    In addition, I was also able to schedule over 10 meetings with NYCDSA Career Support, Bootcamp Alumni, and Bootcamp Faculty, allowing me to brainstorm and prepare for my data scientist & data analyst interviews.

    I am very glad I chose to join the NYC Data Science Academy Community.  
    I just landed my first job as a Data Analyst, and I believe my Bootcamp Experience was worth every penny. 
  • Khamanna  User Photo
    Khamanna • Student • Verified via LinkedIn
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     This bootcamp was suggested to me by my friend. She has done very well after completing the program. I'm a bit different to her. She has a math degree and my background is in languages and business. Also, I have zero experience in Data Science or programming as a whole. 
    The curriculum allows to build the foundation first. It's not done slowly, the program is quite intense. Somehow I found myself forgetting I knew so little and understanding the course material. 
    The three months  wouldn't end and I think you just live longer during that time as you hardly ever sleep. But ultimately it's worth the long nights as you do learn a lot. 
    After the bootcamp you're given post bootcamp challenges to lock in the knowledge. Don't skip them, they are very helpful. Also, there're helpful one-hour sessions to guide your through your job search. I find them particularly useful. 
  • It Worked!
    - 2/22/2021
    Mike Sender  User Photo
    Mike Sender • Data Scientist • Graduate • Verified via LinkedIn
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    I joined NYC Data Science Academy this summer to help me make a career transition from Material Science Engineering into Data Science, and in short, it worked! I increased my salary, easily making the Bootcamp worth it as a purely financial decision, and am starting to work in a new exciting field. 

    I chose them over others because I was impressed with their instructors and they offer continuous career support after graduating.  I was not disappointed. Their instructors are passionate and knowledgeable and seem to genuinely care about teaching and helping their students. After graduating I had two internships directly from relationships and connections I made at the Bootcamp and had many interviews from the same network.  Their career services have always been available, helping me with my resume and acting as a soundboard to help prep for interviews.  

    I only recommend getting into Data Science if you love math and coding. If you do and are willing to put in the work NYC Data Science Academy will prepare you for and help you get a job. 
  • HEY - DO IT!!
    - 2/21/2021
    Richard C  User Photo
    Richard C • Graduate • Verified via LinkedIn
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    I was in your shoes not too long ago and chose to attend the full-time program in the first quarter of 2020 due to the overwhelmingly positive reviews that I read on this page. As a career switcher from finance, I think NYCDSA does a great job of helping execute the tangible steps necessary to make a switch like mine, so at this point the ball in your court to take action to change the trajectory of your career. 

    The curriculum can be best described as comprehensive - it covers Python, R, SQL, and Machine Learning techniques to provide students with the tools needed to further develop their data science skills and ultimately become competitive job candidates. That said, I must stress the importance of putting in the genuine effort to get the most out of this program. Participation in this program isn't a job guarantee, so please don't go into this thinking of this as a shortcut towards placement in an incredibly competitive field to break into. 

    I graduated in March 2020 just as the COVID-19 pandemic was starting, so things like the job fair weren't an option for me, but I do feel that the academy made an earnest effort to make up for this through engagement. Continued check-ins from staff and complimentary workshops really gave me the push I needed to keep going through this unique time and ultimately find a role as a data consultant. 

    In short, there's no time like the present, and if you can honestly tell yourself that you are willing put in the effort to learn about this awesome field, unequivocally DO IT!

Thanks!