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NYC Data Science Academy

New York City, Online

NYC Data Science Academy

Avg Rating:4.83 ( 274 reviews )

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

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

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

Recent NYC Data Science Academy Reviews: Rating 4.83

all (274) reviews for NYC Data Science Academy →

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

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    Start Date January 6, 2020
    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
    More Start Dates
    January 6, 2020 - New York City Apply by December 17, 2019
    March 30, 2020 - New York City Apply by March 18, 2020
  • Big Data with Amazon Cloud, Hadoop/Spark and Docker

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    Data Science, Python, Hadoop, Spark, Data Structures
    In PersonPart Time5 Hours/week2 Weeks
    Start Date January 14, 2020
    Cost$2,990
    Class size10
    LocationNew York City
    This is a 6-week evening program providing a hands-on introduction to the Hadoop and Spark ecosystem of Big Data technologies. The course will cover these key components of Apache Hadoop: HDFS, MapReduce with streaming, Hive, and Spark. Programming will be done in Python. The course will begin with a review of Python concepts needed for our examples. The course format is interactive. Students will need to bring laptops to class. We will do our work on AWS (Amazon Web Services); instructions will be provided ahead of time on how to connect to AWS and obtain an account.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelStudents are expected to be familiar with using an operating system from the command line; knowledge of Python is helpful.
    Placement TestNo
    InterviewNo
    More Start Dates
    January 14, 2020 - New York City Apply by January 13, 2020
    April 21, 2020 - New York City Apply by April 20, 2020
  • Data Science with Python: Data Analysis and Visualization (Weekend Course)

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    Start Date January 19, 2020
    Cost$1,590
    Class size20
    LocationNew York City, Online
    This five week course is an introduction to data analysis with the Python programming language, and is aimed at beginners. We introduce how to work with different data structure in Python. We covered the most popular modules, including Numpy, Scipy, Pandas, matplotlib, and Seaborn, to do data analytics and visualization. We use ipython notebook to demonstrate the results of codes and change codes interactively during the class. Our past students include people with no programming experience or those who have minimal exposure to Python. Students told us our classes are very informative, engaging, and hands-on.
    Financing
    DepositN/A
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    Getting in
    Minimum Skill LevelKnowledge of basic data types (e.g. string, numeric), data structures (e.g. list, tuple, dictionary) Familiarity with concepts of list comprehension and for/while loop
    Placement TestNo
    InterviewNo
    More Start Dates
    January 19, 2020 - New York City Apply by January 18, 2020
    March 7, 2020 - New York City Apply by March 6, 2020
    April 19, 2020 - New York City Apply by April 18, 2020
    June 13, 2020 - New York City Apply by June 12, 2020
  • Data Science with Python: Machine Learning (Weekend Course)

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    Data Science, R, Machine Learning, Artificial Intelligence
    In PersonPart Time7 Hours/week5 Weeks
    Start Date January 19, 2020
    Cost$1,990
    Class size10
    LocationNew York City, Online
    This 20-hour Machine Learning with Python course covers all the basic machine learning methods and Python modules (especially Scikit-Learn) for implementing them. This includes linear regression, Naïve Bayes classifiers, logistic regression, linear discriminant analysis, cross-validation, bootstrapping, feature selection, regularization, model selection, SVM, decision trees, random forest, PCA, K-Means, and Hierarchical clustering. In addition, this course teaches the basics of natural language processing. After successfully completing this course, you will be able to explain the principles of machine learning algorithms and implement these methods to analyze complex datasets and make predictions in Python.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelCompletion of Data Science with Python: Data Analysis; Data Science with R: Machine Learning
    Placement TestNo
    InterviewNo
    More Start Dates
    January 19, 2020 - New York City Apply by January 18, 2020
    March 7, 2020 - New York City Apply by March 6, 2020
    June 13, 2020 - New York City Apply by June 12, 2020
    April 19, 2020 - Online Apply by April 18, 2020
  • 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 January 18, 2020
    Cost$2,190
    Class size15
    LocationNew York City, Online
    This course is designed to provide a comprehensive introduction to R. Students will practice programming and analyzing data with R. Students will learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models to data. In addition to a theoretical framework in which to understand the process of data analysis, this course focuses on the practical tools needed in data analysis. This course also covers the creation of dynamic reports with the knitr package in R as well as the creation of dynamic dashboards with R Shiny. By the end of the course, students will have mastered the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting the code.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelBasic knowledge about computer components Basic knowledge about programming
    Prep WorkNone
    Placement TestNo
    InterviewNo
    More Start Dates
    January 18, 2020 - New York City Apply by January 17, 2020
    April 18, 2020 - New York City Apply by April 17, 2020
  • 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 January 18, 2020
    Cost$2,990
    Class size40
    LocationNew York City, Online
    This 35-hour Machine Learning with R course introduces both the theoretical foundation of machine learning algorithms as well as their practical applications in R. It will introduce you to data mining, performance measures and dimension reduction, regression models, both linear and generalized, KNN and Naïve Bayes models, tree models, and SVMs as well as the Association Rule for analysis. After successfully completing this course, you will be able to break down the mathematics behind major machine learning algorithms, explain the principles of machine learning algorithms, and implement these methods to solve real-world problems. Unit 1: Foundations of Statistics and Simple Linear Regression Unit 2: Multiple Linear Regression and Generalized Linear Model Unit 3: kNN and Naive Bayes, the Curse of Dimensionality Unit 4: Tree Models and SVMs Unit 5: Cluster Analysis and Neural Networks Final Project After 35 hours of structured lectures, students are encouraged to work on an exploratory data analysis project based on their own interests. A project presentation demo will be arranged.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelKnowledge of Python programming Able to munge, analyze, and visualize data in Python
    Prep WorkKnowledge of R programming Able to munge, analyze, and visualize data in R
    Placement TestNo
    InterviewNo
    More Start Dates
    January 18, 2020 - New York City Apply by January 17, 2020
    April 18, 2020 - New York City Apply by April 17, 2020
  • Data Science with Tableau (Online)

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

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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
  • Introduction to Python (Online)

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

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    Start Date January 14, 2020
    Cost$1,590
    Class size40
    LocationNew York City
    This is a class for computer-literate people with no programming background who wish to learn basic Python programming. The course is aimed at those who want to learn “data wrangling” – manipulating downloaded files to make them amenable to analysis. We concentrate on language basics such as list and string manipulation, control structures, simple data analysis packages, and introduce modules for downloading data from the web. This Introductory Python class runs over four weeks, with five hours of class per week (split into 2 ½ hour evening classes). Classes will be given in a lab setting, with student exercises mixed with lectures. Students should bring a laptop to class. There will be a modest amount of homework after each class.
    Financing
    Deposit$1590
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    Getting in
    Minimum Skill LevelThis Introductory Python class is designed for computer-literate people with no programming background who wish to learn basic Python programming.
    Prep WorkIn the class, we will use Python 3. If you are following this video to set up Python environment, please make sure you download the Python 3.X version starting from 1 min 23 s in the video. Link: https://vimeo.com/160172414
    Placement TestNo
    InterviewNo
    More Start Dates
    January 14, 2020 - New York City Apply by January 13, 2020
    March 9, 2020 - New York City Apply by March 8, 2020
    April 20, 2020 - New York City Apply by April 19, 2020
    June 2, 2020 - New York City Apply by June 1, 2020
  • Live Online Data Science Bootcamp (Online)

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    Start Date January 6, 2020
    Cost$14,960
    Class size25
    LocationOnline
    Our Live Online Bootcamp is an online full-time program. We live-stream our on-campus classes to the remote intensive bootcamp students. This program was designed for students that have the time to be a full-time student, but can't commute to our school. Students will be placed on a rigorous curriculum that spans from 9:30 AM to 6:00 PM EST as well as have access to prerecorded modules with over 1000 coding challenge questions on online learning platform for additional practice. In addition, they have access to dedicated TA’s as well as the larger network of a shared slack channel between both in person and remote bootcamp students. Live Classes: You will learn real-time streamed lectures as well as have access to prerecorded modules and coding questions for additional practice. Live Communication: They will learn real-time streamed lectures as well as have access to prerecorded modules and coding questions for additional practice. Personalized Job Support: Students also have access to the full resources of NYC Data Science Academy to help them find their dream job upon graduation. Our curriculum covers the expanse of all the skills required in the data science industry. We cover both R and Python as well as Machine Learning Theory, Big Data, and Deep Learning.
    Financing
    Deposit5000
    Financing
    • 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
    More Start Dates
    January 6, 2020 - Online Apply by December 17, 2019
    March 30, 2020 - Online Apply by February 15, 2020
    March 30, 2020 - Online Apply by March 18, 2020
  • Part-time Online Data Science Bootcamp (Online)

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

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  • Ben Rosen  User Photo
    Ben Rosen • Graduate Verified via LinkedIn
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    Curriculum:
    Instructors:
    Job Assistance:

    This bootcamp completely exceeded my expectations. The curriculum was challenging and thorough. The instructors were intelligent and very helpful outside of the classroom. My classmates were very bright, helped foster a fast paced program, and I never expected that we’d have a lot of fun together too. Of course the bootcamp helped with my Python, R, and SQL skills, but I also gained public speaking and teamwork skills from the project-focused curriculum. The career advice given to us about job-searching, communication skills, and analytics in the workplace were valuable too. 11/10.

  • Life Changed
    - 5/26/2017
    Mayank Shah  User Photo
    Mayank Shah • Data Scientist • Graduate Verified via LinkedIn
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    This course was the best thing to ever happen to me. In 20 weeks (4: pre work, 12: course, 4 job hunt) I went from someone who couldn't write 'Hello World' in python to a full blown Data Scientist, making six figures, with multiple companies vying for my interest. 

    What you should know:

    You will get as much out of this course as you put in. I had many, many days where I was working well past midnight and back in class by 9:30am. You learn how to learn, which is THE skill required for any coding job. The curriculum is intensive, and a lot of times I couldn't totally complete the homework without checking for answers from my peers, and that's okay! In the real world, much of your job will be interacting and working with a team. 

    Course:
    Go every day, work hard, finish the projects on time, and hold yourself accountable. The lecturers do a great job, but ultimately when you're 24+ years old, nobody is going to spoon feed you. The homework is great, but when you try to put everything you've learned together into a well rounded project (there are 4-5 projects), that is when you really understand what is going on. Throw yourself full bore into the projects, and take pride in your work. 90% of what I learned, no exaggeration, was in the 3-5 days before projects were due. Its one thing to figure out homework by looking at the example sets, and a different thing entirely to apply those concepts to a data set with different structure and goals. If you are proud of your projects at the end, you will get a job. Period.

    Job Hunt:

    The job is the ultimate goal for 99% of people entering the camp. Unfortunately, there is some confusion about how the search will work. For one, you will not be "given" a job. For most people, the job search will take 1.5-3 months. Vivian has excellent contacts but she also has 40+ students. In order to guarantee yourself a job, you need to approach the process like a data science project. For me, I did "easy apply"s on LinkedIn, 50 a day. These take literally 15 seconds each. I then selected 15 companies a day with a more formal interview process, and sent them a variation of a pre-written cover letter. For my top picks, I tried to find a hiring manager or data scientist on the team, and add them on LinkedIn. I put my name on AngelList, and got many companies reaching out. I humbled myself and told everyone I was more interested in a great learning position, not a great salary. I iteratively changed my own interview methods, including voice tone, inflections, negotiations, honesty levels, until I found a balance that worked for me. You cannot just apply and hope. That is not a method.

    Basically, the bootcamp is the first big step. The second big step is learning how to apply and interview. Many people send out 5-10 applications to their top picks (who are often everyone else's top picks as well) and then sit on their hands and wonder why they haven't gotten a job. When entering a new field, you have to make concessions about your salary and place of work, in order to reap the rewards down the line. Also, without multiple options, you will not be able to negotiate because you'll feel this is your only chance. BROADEN YOUR HORIZONS!

     

    Overall:

    The camp was the best decision I ever made. I read a book called Design Your Life, which basically said take how you want your life to be, then decide what is necessary to get it there.

    I wanted to live in NYC, with a six figure job, working in an office with low stress, and love what I do. NYCDSA made all of that possible. If you have gotten a degree that isn't taking you where you want to be, but you know you're smart and can work hard, I strongly urge you to apply to NYCDSA today. 

  • Amazing Bootcamp
    - 11/2/2019
    zhuoyi liu • Data science fellow • Graduate
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    I graduated in end of June(Cohort 17). Right now I'm a Data engineer at top tech firm in China. 
    The bootcamp materies encompass big data, machine learning, and data analysis tool such as Python, R, SQL.
     This include all the to-go package to be a Data Scientist. I'm so grateful that I attended this bootcamp. Peoples in the bootcamp are very nice and helpful. 
    This is the big community for every people that want to be a data scientist, come and join us! 

  • Josh • Data Scientist
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    I attended the in person 12 Week Bootcamp during the end of 2017 and I am working as a Data Scientist at a highly recognized tech startup!  For those considering studying data science I highly recommend NYC Data Science Academy.  The main differentiator of NYC Data Science Academy from all the competitors is the curriculum.  The founder herself(Vivian) was one of the first era of data scientists who studies statistics and programming before "data science" got popular.  So the curriculum reflects this in that the bootcamp knows what it takes to succeed in data science in the real world.   The 12 weeks consist of SQL, R, Python, Machine Learning Algorithms, and Bid Data/Deep Learning with the emphasis primarily on practical aspect of these tools.  After the 12 weeks I wasn't a master of all things data science, but the bootcamp really equips you to be able to find your own answers to any data science question (engineering as well!) and make yourself a highly sought after candidate.  

    The only "con" I guess is that you have to work your butt off! You're cramming years worth of an equivalent master's degree into 12 weeks, so you really have to be able to focus and have a passion for data and learning.  But as an encouragement,  all the people that worked hard ALL ended up with a really solid data job that they are proud of. You don't have to take my word for it, check LinkedIn to verify that NYC Data Science Acadey worked for a lot of great students

  • SEAN SW LEE • Graduate
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    Before I attended NYC data science academy bootcamp, I already had chances to take some short introductory courses in R, Python, and machine learning at other institutes. But even after taking such courses,  my skills  and understanding were very limited, and I actually had difficulties doing researches. This is why I came to attend the NYC data science bootcamp.

    During the bootcamp, we learned data science/machine learning not only in R but also in Python. The codes that I got from lecture codes and  homework are valuable, and I find them  very helpful for conducting my research. In particular, since R and Python have their own highs and lows, I'm able to use both R and Python in complementary ways in my researches, which are actually very good points of the bootcamp program.

    When I conmpare the lecture notes from NYC data science bootcamp with lecture notes obtained elsewhere, I find that the lecture notes from NYC data science bootcamp are well organized to successfully explain fundamental theories.

    I think the teachers here are very knowledgeable, and their lectures are very  efficient. Many of the teachers also shared their experience in the data science industry and gave us ideas about what it is like to work in the data science industry, which was another good point of this program. When students needed helps, TAs, managers, or teachers were available either in person or on slacks for discussions.

    I think this is a highly recommendable program for anyone interested in data science. But, before this program starts, enrolled students are highly recommended to do their best in the preliminary lectures to be better prepared. In addition, students need to work really hard in lectures, homework, and projects.

    I'd highly recommend this program.

  • Paul C • Data Analyst • Student
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    I recently completed two NYCDSA courses: 'Python Introductory' and 'Python Data Visualization & Analysis' taught by Tony Schultz in July 2019. First, the courses provide a really great foundation to learn python and bulding out your technical skills for applications. Second, Tony is a great instructor and walks you through everything. He takes the time to explain difficult concepts and provides simple explanations to understanding code. Highly recommend to those who are looking to build out their technical skills.

  • A+ Bootcamp
    - 7/22/2019
    David Levy • Data Analyst at FanDuel Sportsbook • Graduate
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    Amazing bootcamp and experience! The teachers and TA's are extremely knowledgable and caring- going over and beyond in their support of students. The program is also exceptionally well-managed and upper management genuinely cares about the success of their students; both throughout the bootcamp and after graduation.

    As in most things in life- you will get what you put in. Be prepared to work really hard- you will learn a TON and set yourself up for success in the data science field. You will also build an outstanding network and support system of like-minded, good people!

    HIGHLY recommended!

  • Devika Pradhan • Graduate
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    I took the "Data Science with Python: Data Analysis and Visualization" class taught by Tony Schultz this summer.  The course content is thorough, well formed and covered a lot of areas within the short amount of time. Tony was great with explaining all the concepts. Often times he covered more than just one way to solve a problem and encouraged us to develop our own coding styles. Definitely recommend this  class to all working professionals interested in learning Data Science using Python. 

  • Good and Difficult
    - 6/13/2019
    Adrian Gillerman • Global Data Analyst • Graduate
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           The bootcamp offers even seasoned machine learning practitioners something new, and everyone (regardless of their coding background) can get something out of it.  The instructors are nice and want you to succeed but there is so much information packed into such a short amount of time. I liked this bootcamp but found it difficult.

           On a more personal note, I would not have gotten the job that I have now at Bloomberg without this bootcamp. I received letters of recommendation from two instructors as well as a practice interview with one of the camp’s alumni who had recently gone through the same interview process. The interviewer mentioned that the bootcamp made me stick out as an applicant and was part of the reason why I got this position. As I reflect on this experience though, I felt like I was floundering the entire time and overall the experience was not enjoyable because of the magnitude of work. However, I ended up learning so much about R and the different machine learning techniques. Even though I came from a mathematical background with some machine learning experience I was not able to comprehend some material during the program.

            Some of you reading this review may be thinking in a strictly cost-benefit mindset. For me, the financial benefit has outweighed the cost especially because I am at the beginning of my career. Because of the quality of the instructors, the opportunities the bootcamp unlocks, and the interesting subject material I would recommend this bootcamp to anyone looking for a challenging way to jumpstart their machine learning adventure.

  • Jane Li • Student
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    I took the Python course about Data Analysis and Visualization. Tony taught everything in a very clear and organized manner. Highly recommend the course to anyone who are interested to learn more about data analytics and pursue the data scientist career.

  • Leona Isabelle • Graduate
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    I attended the Introductory Python course at NYC Data Science Academy taught by Tony Shultz. I really appreciate his style of teaching - it was a great balance of theory and practice. He also brought a lot of energy to the class which made a big difference especially as it was in the evenings after work. He also takes the time to go through the HWs and clarify students' questions - he is clearly very engaged in teaching and makes a lot of effort to support his students. 
    I highly recommend this class.

  • Dmitri Levonian • Graduate
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    Jon Krohn gave a wide overview of basic deep learning models - convolutional, recurrent, some unsupervised learning approaches, etc. This is obviously a lot of material and there are only 5 sessions, so discussion was typically sacrificing depth for breadth.

    As a starting point to understand DL, e.g. for someone with traditional stat/quant background, this is a great course. Jon explains the basic mechanics of a neural network down to matrix transformations. 

    On the other hand, if you already understand the basic DL and are looking to develop practical application skills including TensorFlow, this course may be a slight disappointment. 

  • Great Experience
    - 5/20/2019
    HF • Student
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    The course “Data Science with Python: Data Analysis and Visualization” is perfect if you are fairly new to “Data Science”. It begins with a general overview of basic knowledge in python before going to the analysis content. You will learn Numpy, Pandas, Visualization and Seaborn after you finish the course. The instructor Anthony Schultz introduced every chapter in a slow and comprehensive pace. The course notes are well organized. You can ask any questions during the class and Anthony will explain your question with great amount of details. I would love to recommend to take this class if you are planning to pursuing your career in Data Science. Five Stars!!

  • Julio Villar • Graduate
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    The teacher was able to properly explain all the concepts. Very easy to follow and understand. Homework looks challenging but if you listen in class, it's doable. Would definitely recommend. 

  • Marius P. • Graduate
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    You can read books about deep learning and in fact the instructor Jon Krohn has a new book out as well. However, there is a gap between reading and understanding conceptually and writing code to solve a real-world problem. This course completely fills the gap.

     

    The instructor does give you the conceptual foundations, assuming no prior knowledge. I did have some prior knowledge, but still the class is self-contained.

    I would say 30-40% of class time is spent discussing code that solves a practical problem. I think this is the perfect balance: you can't delve more into code without a global understanding why all those parameters may be required and you can't delve deeper into theory without neglecting the practical question of "where do I begin".

     

    The instructor is very personable and easy to approach about his own experience in the industry.

  • Manjula
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    I came across NYC Data Science Academy when I was looking for certification courses with classroom learning and I am glad I made a decision to take it up. It was a well planned course which was spread over five Sundays. Our instructor, Anthony Schultz, was extremely knowledgeable and passionate about teaching Python which made the whole course a very enjoyable experience. The course content had in depth coverage with examples to elaborate each concept, giving us the opportunity to learn as we progress. By the end of this course, you would get a good grip of Python which you can apply in your daily work.

  • 74066366EB14503E0F379266E1EFA24EFB3C29F54BD0751E50E8025293CD82A8
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    I took Data Science with Python: Data Analysis and Visualization with Tony Schultz. The course was a wide-ranging overview of basic Python, Numpy, Scipy, Pandas, and Matplotlib (and a little Seaborn) that managed to fit into 5 sessions. The materials were organized and gave nice opportunities to practice. Tony was extremely helpful and made all questions welcome.

  • Naveen Ramachandran
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    The class was concise and impactful. I really enjoyed the topics covered and thought that the homework was really beneficial in driving home the coursework. The pace of the course was pretty reasonable and I was able to follow the curiculum very well.

  • Great course
    - 4/14/2019
    Erinc Eyuboglu
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    I really enjoyed the contents and the samples that Anthony gave us. If you have some background about coding and maths this course is for you to start to build up your skills with phython.

  • Lukas Frei • Graduate
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    I chose the NYC Data Science Academy over other bootcamps mainly because of its outstanding reviews as well as the fact that it offers its courses simultaneously in R and in Python. 
    After working through the extensive prework in Python, R, and SQL (an absolute must if you do not have any previous coding experience), I was perfectly prepared to attend the bootcamp.

    The bootcamp itself offered far more than I had expected. Phenomenal teachers that will give their everything to help you understand the topics, TA's that are always there to help with smaller questions as well as great classmates that made studying a lot easier. Nevertheless, you should not come here expecting a relaxed ride. Teaching data science in twelve weeks requires a fast pace and it will be up to you to put in those hours to complete the homework and review lectures.

    The curriculum itself is centered around four projects that deal with all aspects of the data science process, from gathering data (web scraping) over creating a dashboard to working on machine learning group projects. My initial intention coming here was to learn as much as possible as fast as possible and this bootcamp turned out to be everything that I had hoped for.

    On top of that, Vivian and the team offered several job search and interview preparation lectures and talks that I have not seen anywhere else. If you are looking for a data science bootcamp that covers all data science topics from start to finish and you are willing to put in the work, this bootcamp is the best decision you can make.

  • Great teaching!
    - 2/3/2019
    Ilya Fischhoff • Postdoc • Graduate
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    I took NYC Data Science Academy's deep learning course, taught by Jon Krohn. Jon is a terrific teacher, and I would heartily recommend this course! Jon had tremendous enthusiasm and patience for questions while still keeping us on track with the schedule. He really broke things down into bite-size, understandable pieces, while still covering a lot of breadth and depth. I appreciated Jon making available his draft book, this really complemented the lectures. I liked the format of once-a-week lessons because it gave time for concepts to sink in and to practice things with my own data in between sessions. I appreciated that Jon made time to troubleshoot challenges we experienced in our own projects. The course was both a great introduction to concepts and to some of the ways people are applying deep learning; here examples from Jon's day job were valuable. One aspect of the course that was very helpful was that Jon set up a Docker environment for us, and shared very clear instructions for getting our computers set up with it in advance. We were all ready to go from the start. I'm all the more grateful for Jon having set that up after recently spending half of a workshop (run by a different data science academy) wrestling with Anaconda. The Jupyter notebooks all just worked, so we could focus on learning. 

  • Amazing Program!
    - 1/11/2019
    Shiva Panicker • Graduate
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    I entered the bootcamp with a background in Mathematics and some previous exposure to machine learning theory. Programming was relatively new to me at the time, so my first course of action was to familiarize myself with Python and R. Thankfully, NYC Data Science Academy provided over 30hrs of pre-bootcamp material (video lectures, in-person lectures, and textbooks), which included coding in Python, R, and some introductory statistics. The program kicks off with a small overview of the tools needed to begin studying data science (mostly to bring everyone up to the same page), and then dives right in to data visualization as the first major topic of study. There is a strong sense of camaraderie with students throughout the program, and there is a strong family-like atmosphere in the space. Most importantly, the curriculum is very strong, and the instructors have deep practical and theoretical knowledge on the material covered. I found it a privilege to study under some of NYCDSA's staff, as they really are the cream of the crop. On top of a strong curriculum, there are many career workshops during and after the program is complete. Some of the workshops include professional development, discussions with industry leaders and practitioners (Kirk Borne spoke to my cohort), and interview/case study prep. The post-graduation network is incredibly strong and supportive for alumni seeking jobs, with frequent interview and networking opportunities provided. Vivian (the program founder) has a vast professional network, which she utilizes for student and alumni needs.  I'm incredibly happy to have completed the program, and to have worked with such a terrific set of instructors, teaching assistants, and classmates during that time. I couldn't have asked for a better start to my data science career.

  • Sunanda Mishra
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    I went to NYCDSA in hopes of changing careers. My undergraduate degree was in statistics, and I worked as an actuary for 6 years and earned my actuarial credentials in this time. I was bored of actuarial work and was looking for a change into data science since my background was related. While I had the statistics knowledge, I needed to beef up my coding experience.
     
    After reading tons and tons of reviews of bootcamps, I narrowed it down to NYCDSA, Metis and Galvanize. NYCDSA had the most comprehensive syllabus and it looked like students found jobs relatively quickly after the bootcamp ended.
     
    NYCDSA lived up to my expectations with respect to how comprehensive the program was. The projects really helped me solidify my knowledge in Machine Learning techniques and my practice with coding. I will say, as an actuary and statistics major, my knowledge of statistics was already pretty decent. NYCDSA went through a semester's worth of course material in 1-2 days at times- this may be too fast to get a thorough understanding, however it's up to the student to study more outside of the bootcamp if needed.
     
    After the bootcamp, NYCDSA helped a ton with finding a job. After the hiring partner event, I had 5 interviews lined up with well established companies. Further, Vivian has connections with TONS of companies in NYC and her connections helped a lot with securing interviews beyond those at the hiring partner event. Vivian would reach out to us regularly to see how our job hunt is progressing and even offerred to have 1x1 sessions to make sure there was a constant pipeline of interviews.
     
    After 2 months of interviewing, I received 2 job offers. Both offers were from insurance companies that valued my actuarial background and my newly acquired data science skills. I can definitely say, I wouldn't have been able to land these jobs without being able to speak to the projects I did at NYCDSA during those interviews.
  • Katie Sohn • Graduate
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    NYCDSA is definitely a great program for anyone looking to get into data science. I can honestly say it was one of the most challenging and rewarding things I have done. Despite not coming from a STEM background or having any sort of relevant experience initially, the bootcamp still prepared me to be able to land a data science job after. 

    Prior to deciding to join the bootcamp I was referred by a friend who also did not come from a STEM background that highly recommended the program. I decided to try a part time Python course that was offered by the academy to see if this was something I could continue to pursue while also doing more of my own research. After the class I applied and got into the January cohort but decided to defer my acceptance to the following cohort. I think that if anyone is considering the bootcamp and does not have any sort of applicable experience like myself, I highly recommend giving yourself time to complete as much of the pre-work as possible before diving in. Between Python and R, I would try to get as familiar with Python as possible through the pre-work and even beyond that if possible. The staff emphasized this during the interview process and after being accepted, but this became even more apparent once the bootcamp started. The first few weeks of the cohort were more of a review from the pre-work and the class I had taken as we quickly learned both R and Python. However, because I had completed the course and completed a good amount of pre-work, I was able to focus more on solidifying concepts rather than struggling to understand and keep up with learning the code on the fly. This also helped towards the end when completing more complex projects, but I think that if I had dedicated an even greater amount of time beforehand, this could have helped me to push myself even further during the bootcamp. 

    The reason I picked NYCDSA was because it had the best overall reviews and I wanted to learn both Python and R (I noticed some other bootcamps focused only on Python). The whole program was well structured and organized, but quickly became very intense once we started going into completely new material. It is all definitely manageable however, and what you get out of it really will be what you put into the bootcamp yourself. The staff also makes sure to simultaneously help you get your resume ready by the time you graduate and prep you for what to expect for interviews. 

    In terms of my experience post bootcamp, the staff still does everything they can to support you in the job hunting process which I really appreciated and have a pretty large network to tap into. For myself, there was a lot of work to be done in terms of networking and preparation given that I was pivoting into an entirely different field, but I found that domain experience definitely helped in my case in terms of getting some interviews. 

    When I look back on the bootcamp I'm really amazed at all we accomplished and learned in a relatively short time. I also made a lot of close friends in my cohort given that the majority of our time during the three months was spent together. It was great  to learn alongside people with diverse experiences/backgrounds and I feel that for the most part everyone was supportive of one another. If you're interested in the field, willing to sacrifice the time, and want to challenge yourself, then I highly recommend signing up!

  • Introductory Python
    - 11/20/2018
    Americo Pietropaolo • Applicant
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    This course has been my first attempt to learn how to code. I have enjoyed it a lot. Very interesting, and I would recommend it to anybody that, as myself, has no prior experience with coding. Among other things, our teacher ( Tony Schultz) was outstanding. He is extremely well prepared, very focused on actually making us learn and like Python, is well organized, and has a very engaging way of running his lessons. Overall it has been a great experience, and it's very likely that I will take other classes at NYC Data Science Academy.

  • Michelle Vu • Director of Business Operations
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    This review is for the Introduction to Python course. My background is in business intelligence, business process and data governance. I use SQL at my job daily but have had no formal programming training.

    The introduction Python course was perfect for beginners. Tony, my instructor was extremely knowledgeable and did a fantastic job explaining concepts clearly.  I was very impressed with the number of topics that were covered in 8 sessions and how organized the course and the communication was. For an evening class after a full work day, his personality kept the class lively and interesting.

    If you’re like me and coming in with no programming background, I highly recommend reading up and taking some free online Python courses beforehand. Overall, this was a great learning experience and I highly recommend NYCDSA.

Thanks!