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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

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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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  • Great Bootcamp
    - 3/28/2019
    Chaoran Chen  User Photo
    Chaoran Chen • Data Engineer • Graduate Verified via LinkedIn
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    Great Bootcamp. 

    The program is very comprehensive and intense. The syllabus is well structured. They make sure your time is only spent on most popular and useful technologies which are needed for a Data Scientist. 

    The instructors are very responsive. They also hold events to build the relationship between you and the potential hiring partners.

  • Lukasz • Graduate
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    Instructors:
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    N/A

    I studied mechanical engineering and physics for my undergrad at a top university and work in product management with a focus on search. I took this class to satisfy a personal interest in the subject matter and familiarize myself enough with the fundamentals of machine learning to be able to explore the field more deeply on my own. I was also motivated by a career interest: the subject matter is highly relevant to my domain, and I feel that developing an understanding of the concepts and how to deploy them myself will make me better at my job long-term. Prior to enrolling in the class, I spent roughly 8-10 hours learning R and felt sufficiently prepared (I had some previous programming experience).
     
    In the end I was extremely happy with this class (Machine Learning in R on Saturdays, 8 hrs at a time). The curriculum and content were excellent, the instructor, Luke, was fantastic and the assignments were challenging and informative. 
     
    I felt the course did a really great job of driving home the core fundamentals of each subject with a focus on statistics, mathematical theory, derivations and best practices. We covered a LOT of material, yet the material had a lot of depth. I thought the sequencing of the subject matter was very well thought out as well. The class was demanding and had the caliber of a graduate-level course.
     
    The course also struck a very nice balance between theory and implementation. After learning about a new model, we would immediately implement it in class using R on our own machines. Luke did a particularly great job at relating the implementation back to the concepts and teaching us how to interpret outcomes of our analyses (I can’t stress enough how important this latter point was for me). He has a really strong grasp of the subject matter, he’s very patient and responsive to questions, offers a lot of insightful commentary on the theory, implementations and best practices, and he cares about his students a lot. The homework assignments complement the class nicely as well, helping to drive home the methods taught in class and how to interpret your work.
     
    If you’re interested in developing a strong understanding of the fundamentals of machine learning in a rigorous format, this class is for you. I also couldn’t recommend Luke as an instructor more. He’s awesome! I was also was very pleased with my choice of the R class. R reduces a lot of the friction in model implementation, which allowed me to focus on developing an understanding of the concepts and interpreting results. 
  • Lei Zhang • Data Scientist • Graduate
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    1.12 weeks' course with machine learning, spark, hadoop helped me solve almost technical interview questions. Also introduce several latest and popular topic, such as NLP, Deeplearning (CNN) and tensor flow. 

    2. This bootcamp faces people with different backgrounds, who can choose between "how to use machine learning" and "how to implement the machine learning(more math). TAs helped a lot if you wanna learn more advanced level.

    3. Chris and Vivian helped prepare resume and the interview practice, and the hiring partner event was very helpful to present myself to the hiring managers directly. 

    Great appreciate!

  • Rahul Bhat • Graduate
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    N/A

    Took the weekend course for Machine Learning with R. Course was very helpful in helping me understand the basics of Machine Learning, different models. My instructor was Luke. He was very helpful and would spend enough time covering each topic. He even took an additional class because he didnt want to rush through the material. Overall I am quite satisfied with the results. Would recommend Luke to anyone else who is interested to venture into Machine Learning field.

  • L. Kan
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    Overall:

    I will recommend this bootcamp to anyone who is eager to learn and have great passion towards data science. Before I attended the bootcamp, I received my master degree in marketing from school. I did not have a lot of math and coding background back then. With my passion towards data science, I decided to take a deep dive and applied for the NYCDSA’s 12 weeks bootcamp. Due to my limited coding background, they did not accept me at the beginning, instead, they provided one month prep course for me to get prepared for the bootcamp. I attended the September cohort after the prep course. It was one of the best decisions I have ever made. With the extensive knowledge and training, and great support in job assistance, I am able to land my dream job in 2 months after bootcamp.

    Curriculum:

    The curriculum is very well designed. I did a lot of research before I applied for this bootcamp. NYCDSA is the only program that covered data science in both R and python, big data processing tools such as Hadoop, Spark at once. I am really glad that I started my journey in data science with them, so my foundation in data science is much stronger now than I was when taking online classes by myself before. The curriculum will also help you to develop a portfolio for job hunting, however, you are the one who decide how much effort you want to put in and how far you want to go. 

    Instructors:

    The instructors and TAs are the best part of the bootcamp. You will never receive this kind of learning experience through online courses. They are all very knowledgeable in computer science, statistics, and machine learning. They are so passionate, and so willing to help each student. There were so many times that they stayed after 7pm, came in during weekends, answered slacks questions at 11pm to provide extra helps. They are far more than just instructors and TAs, but also supportive friends after I finished the program.

    Job assistance:

    I got hired by a major ad agency as a data scientist within two months of completing the bootcamp.

    The hiring team put the best effort to help their students. They hosted awesome hiring partners event, which the students got to make connections and talk to some great companies, such as IBM, citi bank, Mindshare, Publicis and so on. During my job hunting process, Vivian tried her best to provide any connections with the companies that I really wanted to get in. I also received a lot of helps and mentorship from Chris. The way he helped me to prepare for net-working and interviews are very strategic, systematic, and effective. I learned so much and I won’t get this far without him. You can learn all the hard skills anywhere else, but this kind of support and mentorship is hard to find even if you have a lot of money.

    They provide as many helps as they can, but you have to be proactive and eager to learn to take everything in! 

  • MDS • Researcher • Graduate
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    This bootcamp is no longer the great place it used to be. Vivian Zhang (the crazy CEO) has made the curriculum into a joke, and you waste a lot of time on nonsense apps like shiny, blog posts because she thinks that's what employers want. It is not. No one in the industry pays attention to the things she believes they do, which is 1 reason why it has been so difficult to place all candidates in a job. Do not believe for 1 minute she will help you get a job. Only your true qualifications will help with that. 

    Her TAs are wonderful and brilliant. It is not their fault that she bulldozes their efforts. But she has complete control of the camp. 

    It is very difficult to watch her cheapen the brand of what started out so great, and single-handedly destroy the hard work of everyone who works for her.

    She let in people to the camp who were completely unqualified to be there, including non-STEM bachelors, or MBAs with no technical background whatsoever, who were a huge burden on the class. If you are a STEM phd, you had better go to Insight or Ivy Data Science if you want an intensive course in ML and statistics. "Data science" is a marketing phrase for analytics. If you do not have a technical background, you should know that the 16,000$ package Vivian is selling you is too good to be true. You cannot be made a data scientist in 3 months, and there is no way she will be able to place you in a data science job. Most people from cohorts 5 and above are still looking for jobs months afterwards. The ones that do find jobs 6 months-1 year afterwards, do so without any help from Vivian.

    I work for a media company that is transitioning to Python. They were made aware of Vivians reputation and decided to send all their data analysts for corporate training in Metis. I was asked for my recommendation and I have to agree that the quality of teaching is better at Metis, since Vivian has fired most of her good teachers, and the median quality of students can be terrible, since she lets in who ever applies, regardless of their technical skills. I also spoke to several prospective students who told me they pulled out of DSA because they heard that Vivian was letting in anybody who wanted to become a data scientist, even business analysts, and was unable to get most people a permanent job. She lists "internships" as permanent jobs, and cannot support the candidate when those internships terminate. The people in my office who know Vivian do not think that DSA looks good on my resume mainly because they think "she is trying to industrialize data scientists like a factory".

    She also expanded the bootcamp from 20 students to 80 students, which should be a good indication of the quality you can expect.

    Some things Vivian has done:

    1. Lied by saying her acceptance rate for students is 10%. It is 100%. Maybe even 200%, if you consider all the people she tries to recruit. Do you know someone who want to be a data scientist? Tell them to send their 5000$ deposit!!
    2. Fired her main lecturer and dedicated TAs, but not before working them like slaves.
    3. Turned shiny app, visualization, web development and A/B testing into parts of the curriculum because she heard from 1 employer that they like it. It has nothing to do with "data science". She will just throw everything at a wall and see what sticks
    4. Focus first on the jobs for chinese, american, or PHD students to improve her job ratio. The way she makes ''tailored recommendations'' is to put all 100 students CVs into a ZIP file, email this zip file to HR/the HIRING MANAGER and ask if there are any jobs for people in the 'awesome' 5GB of cvs she is sending. With many exclamation points!!! 
    5. is so aggressive with employers and contacts that she scares them away. See 4.
    6. If you want to work in finance she will tell you that finance is dead in New york and no one is hiring in there anymore. You should work for a start up instead, preferably one on her list
    7. If you are coming from outside New York she will send you back there and let you find a job on your own
    8. Her main advice is: send your CV to 10 companies every day on linkedin and hope someone replies. This advice costs approx. $16,000. Do you want a mock interview from someone not from the same company you applied for? That will cost $50.
    9. If you do get a job, be prepared for an awkward phone call about how you should hire data scientists from her when you join your company
    10. Even if you are not interested in the job, she will sign you up to interview with everyone in Manhattan that she knows. Do you know this self employed guy Ben Reid or Snakes and ladders? Let them interview you for a job you don't want just for fun. Ben loves interviewing! 
    11. If you are a scientist, this is probably the worst one of all. The way Vivian prepares students for interviews is by having them memorize thousands of interview questions, categorized by company. This does two things: hide a lack of deep understanding with shallow memorization, and fool interviewers into thinking that a candidate who has memorized the entire interviewbook is more qualified than one who hasnt. It is as close to cheating as you can get, and the most obvious manifestation of the data science mass industrialization and over saturation: forget about understanding deep scientific concepts, just make sure you know what your interviewer will ask you before the interview. She is a shameless cheater.
    12. This is related to 11. If you are Chinese, Vivian will prep you before and after for the interviews. If not, she will tell you that giving you answers to interview questions is "unfair to other students."
  • Mr.
    - 1/31/2017
    Abhishek Desai • Student
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    I took the DATA SCIENCE WITH PYTHON: DATA ANALYSIS AND VISUALIZATION (WEEKENDS), with Aiko Liu.  Aiko is an excellent teacher, who taught methodically and progressively.  The course was extremely well designed, and elevated my skilset by building my understanding step by step in a structured fashion. I would highly recommend the instructor and the class if you want to truly develop a solid foundation to build your skills on.

  • peng wang • Student
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    I graduated summa cum laude from a top college and attend a top Economics PhD program. I attended a boot camp at this institution to boost my empirical research skills. To be honest, even though I've been receiving America's best education, I was still really amazed by the high quality of the education it provided.

    The coursework is highly organized with crystal clear logic flow. The faculty here are super competent and very approachable. At this program, you will learn TONS of very interesting and practical skills, build an impressive resume and open many doors in industry.

    The job placement support here is fantastic. I attended this boot camp to gain empirical research skills for academia and thus did not actively look for industry jobs, but I saw that my classmates have benefited tremendously on job search from this program. Starting from week 3, the program prepares you for professional development. Many HR's from different industries are invited for talks/info sessions/networking events. Students have many opportunities to build connections and to prove themselves. 

    You will have to work hard as the boot camp is very intensive, but that's exactly why it can give you so much and prepare you so well for your future.  

    I would highly recommend this program to anyone!

  • Spencer Stebbins • Data Scientist • Graduate
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    Preface:

    I attended the July cohort and was then a Data Science in Residence at the NYCDSA prior to accepting an offer for a Data Scientist role at a consulting firm based in NYC. I will do my best in this review to be as straightforward about my experience and address a lot of questions I had prior to the program and have understood a lot of incoming students to have had through prepping them for the program. 

    My Overall Opinion:

    Lets start with this: get over your hesitation, take a leap of faith, and you surely will not regret your decision to attend the NYC Data Science Academy 12 Week Bootcamp. Whatever reservations you have, you are not alone; almost all graduates have felt that prior to attending the program. You may be wondering about if this program will really teach me the necessary skills to get a job, am I prepared enough for this, will the program be rigorous enough, and most pivotally; is this the right decision for me? I cannot speak for you, but I can attest to my own experience and I graduated this program with no regrets, soak in a waterfall of new knowledge and skills, and have walked away a smarter, more capable, more confident professional now employed Data Scientist in field. The program is amazing, and the instructors are passionate, and you will learn a lot, but that also being said, you get as much as you put in and the first step is trusting in yourself to join and commit to the three rigorous and insightful months ahead of you. 

    My Background:

    Prior to attending NYCDSA, I was a software engineer at a large shipping company for almost 2 years focusing primarily on front end development. Before that I attending another bootcamp called Hack Reactor, similar to NYCDSA, to study software engineering and javascript. It was growing interest in machine learning, the success of my experience at Hack Reactor and the thirst for that similar immersive and intensive program that led to me to the NYC Data Science Academy. In another life, I graduated from NYU with a degree in Music Business.

    Common Questions:

    Do you need a masters or a background in a quantitative field?

    The answer is no. No, you do not need a masters degree or professional experience in a quantitative field. During my cohort, I thought some of the best and most creative presentations and chosen topics by students were from some that had no prior coding or heavy math experience. That being said, coming in with a math or software engineering background will definitely allow you to vamp up your projects flashiness and you may have an easier time understanding some of the formulas associated with the advanced machine learning algorithms. 

    Will I get a job from this program? What are the job stats? etc.. 

    Although I can't attest to job stats, I received my first offer less than 6 weeks after the program ended. I met the firm at the Career Day at the end of the program. Vivian, the CEO of NYCDSA, is the job placement tsar and wizard and without her and her relationships with so many great firms there would not be as many companies at the career day as there are: Spotify, JP Morgan Chase, MindShare, etc.. Vivian will do every in her power to connect you with your dream job. That being said, getting an offer is entirely on you. You must have great visual and complex projects, you must interview well, and you must be actively job seeking and cultivating relationships on your own. Vivian and the team will do everything they can to prepare you and connect you with your dream job, but you need to show up with the bus fair to ride the bus. I cannot stress this enough. 

    How does this compare to other bootcamps?

    I am actually in a unique position to answer this question. A few years prior to graduating NYCDSA, I graduated Hack Reactor, which is a similar 12 week bootcamp, but for software engineering. Prior to that I took web development course at General Assembly, Coursera Machine Learning courses, Harvard Extension School’s Intro to Data Science class to name a few. Needless to say, I’m hungry for knowledge and a challenge. I can’t speak to the other Data Science bootcamps out there like Metis or Galvanize, but I can say that there is nothing like 3 months of learning something at a such a rapid pace. The sum of its parts is greater than the whole and you can spend years learning on your own secondary to whatever else you are doing or you can jump in the deep end. I did before with Hack Reactor and walked away amazed and the same held true for NYCDSA. 

    Inside Tips:

    Pick good project topics. Your projects will be portfolio to potential employers and if your project outshines the other students, employers will take notice. 

    Pick good project team mates. I didn't have a poor experience with anyone I worked with, but it goes without saying that if you pick bright, easy to work with project partners, you'll be able to build a better end product.

    If you don’t know how to code in R or Python and have no prior experience code - Learn now. Codeschool.com is an excellent introductory resource. 

    DO NOT think you will have a social life. This is only 3 months of your life, but 3 very important months, so give it your all and don't expect to get as much out of it if you don't.

    Comments to the Academy:

    Scaling the program will require more job assistance personnel.

    Increasing the amount of coding done in the program may be beneficial as most jobs now require coding every day and are rarely purely theoretically

    Additional content on computer vision would be fun

    More TAs and one on one knowledge quizzes (like done as a group at the end of the course)

  • Shuheng Li • Data Science Analyst • Graduate
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    *MY BACKGROUND:
    I had a Master in Business Analytics before joining NYCDSA, with a knowledge of programming and data science/machine learning. Though I knew how to make graphs and build models with R and Python, and knew some concepts learned from the online course on EDX and Coursera, this bootcamp was still truly helpful for me.

    My goal was to explore more deeply the big data techniques including Hadoop and Spark and get a chance to review data science and machine learning stuff in a systemic way. This bootcamp gave me almost everything I desired, with so many unexpected benefits.

    It was seriously life-changing for me. I achieved something that would otherwise never be possible had I just stuck with online courses. Read on for more detail.

    *COURSES:
    All the courses were well-designed. They covered everything I needed in my data science journey. Some might wonder why I chose to spend money on this bootcamp to learn something that seems available online. The reason for me was that I feel my time is quite valuable. For me, the efficiency really matters. Rather than spending an hour searching for the right function or parameter and ending up being confused, I wanted to have professionals help me going through the relevant resources systemically. I also found that when confused by problems after the fact, I would open the slides, code, and my repo for that topic instead of having to jump online and wade through Stack Overflow. 

    What’s more, the curriculum covered topics such as Unix, Bash, Git and version control, which seem necessary for a data scientist/programmer but which I never paid attention to when I was teaching myself.

    *INSTRUCTORS AND TEAM:
    They are so great. Everyone is kind and willing to help you and share their experience and approach with you. In my humble opinion, there is a huge difference between teaching yourself programming or machine learning and learning with instructors and advice. Especially when you are putting things into practice. I saved tons of time.  The NYC Data team is really curious and love to try new techniques with the students.  

    They are a caring bunch, and it was great to become friends with the people who participated in and ran the program.

    *JOB PLACEMENT:
    I got hired by Aetna as a data science analyst within three months of completing the Bootcamp.

    The job search is intense but Vivian and the hiring team were always there trying their best to help us. There is a room set aside for graduates to work in when on the job hunt, which made for easy access to staff.   During the Bootcamp, we had several courses about how to sell yourself which was especially important for people who are new to the U.S. job market. From teaching you how to impress your interviewer to helping research relevant details about a target company, the hiring team was very dedicated to providing the necessary support to help me succeed. Also, Vivian seemed to have a contact at almost every company I wanted to apply to, which was a real plus.

    I’m glad I made the decision to do this, it was worth it for me.

  • Charles L. • Graduate
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    I recommend this bootcamp to anyone who wants to transition into the field of Data Science. Before this bootcamp I was a process engineer for a large North American steel company. With the rate of growth in the technology industry, I knew it was time to transition to a new career, and I could have not chosen a better place to do so than NYC Data Science Academy.
    Instructors:
    The Instructors were amazing. Chris is extremely knowledgable in statistics, and his passion for teaching really shines through. With every lecture, he not only shows mastery of the material but also the best way to teach complex materials to a class of non-programmers.
    Luke goes above and beyond to describe the theory behind the algorithms. His work ethic is shown through the countless hours he has stayed to review lessons with students and belief in continuous improvement.
    The TAs (Shu, Zeyu) were immense help, and had very good knowledge of big data applications (Hadoop ecosystem, front end work, SQL database design, etc.)
    Curriculum:
    The bootcamp offers a good basis for understanding prediction models and when to use which types of algorithms. There just isn't enough time to cover all aspects of statistics and the many branches of prediction models. Both R and Python are taught here, which allows for great flexibility. While this bootcamp is rigorous, self discipline is required to fully delve into algorithms and build impressive products for your portfolio (natural language processing, image recognition, recommendation engines, etc. ; these advanced topics are covered briefly but enough for you to take the reins). All in all I believe the bootcamp set me on the right foot into the industry.
    Job Assistance:
    While there is some assistance, the majority of the legwork work is still on the student to be duly diligent - sending out applications, getting interviews, networking and working their way up towards their dream job. There is no easy formula for this, and you MUST continue learning (Algorithms, data architecture, and more advanced ML topics etc. ; network to find out what people in your ideal companies expect you to know) and reviewing material even after the bootcamp to prepare for interviews. 

  • David Steinmetz • Machine Learning Data Engineer • Graduate
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    Attending the NYC Data Science Academy 12-week Data Science Bootcamp was one of the best decisions I have made. It was instructive and rewarding. It provided a speedy career transition and enabled me to get a job within two months of graduation as a Machine Learning Data Engineer at Capital One. I will summarize my background and describe my experience at the bootcamp and why I recommend it highly.

    I have a PhD in materials science, which is a blend of math, chemistry and physics. I had programmed models and simulations in Matlab, but have no formal computer science education. I switched to management consulting after the PhD to apply my analytical skills in the business world and quickly realized there is a great need for data analysis at companies. After taking the complete Data Science Specialization on Coursera, I knew I wanted to switch to data science and found the NYCDSA bootcamp to be the most comprehensive, teaching R, Python, and Big Data technologies.

    I recommend this bootcamp for three reasons: quality of teachers and materials, structure, and networking, both at the bootcamp and in job placement.

    It takes a lot of knowledge, experience, and hard work to distill complicated and complex topics and communicate them in a simple and understandable way. The materials presented in this bootcamp were presented that way. When I can understand statistical concepts which I had tried to understand for a long time in a matter of minutes, it means the quality of teaching and materials are excellent. During the job search, I also realized that the correct balance between breadth and depth had been selected to give us a very solid foundation on which to start a job in data science.

    The teachers were exceptional. Their passion and dedication to the students were visible from day one. This was shown again and again in how hard they worked to constantly improve and expand lecture materials to how much support they gave to each individual’s success outside of class. Having them as teachers was an honor.

    The structure of the bootcamp allowed an incredible amount of materials to be covered in a short amount of time. Particularly, it used both R and Python for statistical concepts and machine learning. In addition, we learned about many other tools in extra sessions designed to round out our knowledge. Big Data technologies such as Hadoop, Hive, and Spark were covered toward the end of the bootcamp. Spark was asked for often in interviews, and familiarity with it was helpful. Having five projects under your belt is exactly what you need when interviewing. I always had an example I could use to answer questions. The value of this is not to be underestimated.

    Lastly, the opportunity to network was incredible. You are beginning your data science career having forged strong bonds with 35 other incredibly intelligent and inspiring people who go to work at great companies. The value of those friendships and the ability to create a strong network at the beginning of your data science career will become evident a couple years down the road.

    I was fortunate enough to meet and give a presentation to managers at Spotify, at Meetups, and get connected to many hiring partners. Vivian, the founder, is a strong proponent and has an incredible network. She seemed to have a contact at almost every company I wanted to apply to. Her one-on-one evaluation of interview performance with me was very helpful. She and the rest of the staff are very dedicated to each student’s success, being clear in their purpose that this experience will change both you and your family’s lives for the better. Their hearts are in it and their dedication is clear.

    If you are considering this bootcamp to get more into data science, it is exactly the accelerator you need to get your career in this field off the ground. I cannot recommend it enough.

  • Nada Kumar • Graduate
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    My background is in Data Engineering and Analytics and I have been consulting for the Banking and Financial Services clients. I strongly believe that Machine Learning is the key to the Artificial Intelligence and decided to embrace this emerging trend and immerse myself in the field of Data Science.

    Although there are several Data Science bootcamps that are available, NYC Data Science Academy stood out for me because of their curriculum and the strong portfolio of projects they help and empower the students to build. The portfolio of projects, Github code and the corresponding blog posts definitely help make a good impression with the interviewer and showcase the great work accomplished during the 12 week period at the academy.
    It has been a truly amazing learning experience for me and definitely worth the investment that helped me advance to my next stage of career growth.

    To begin with, the curriculum is quite comprehensive covering all the important Machine Learning algorithms and their fundamentals, detailed working of the algorithm,assumptions, diagnostics, pros and cons. There are regular homework exercises that allows the students to apply the knowledge that they learned in the class and solidify their understanding of the concepts. The class was very diverse and represented students who hailed from various backgrounds - Finance to Engineering to Medical sciences.

    I would like to highight the quality of instructors here: All the instructors were extremely professional, technically strong and quite articulate in explaining the concepts. They were also available after hours and helped clarify the questions pertaining to homework, projects and software installation.

    Regarding career development, Vivian and her team have made great efforts to help the students reach out to hiring managers and have arranged internal referrals at the firms. The Academy also provides a strong support system for the students as they start looking out for career opportunities as a Data Scientist. 

    At the end of the day, You'll form great relationships not only with the instructors but with other talented students as well as everybody learns together about this exciting field. If you are thinking about uplifting your career to a whole new level and set your feet into the fantastic world of Data Science, I strongly recommend NYC Data Science Academy.

  • A Good Start
    - 12/20/2016
    Jonathan • Graduate
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    This 12-week data science bootcamp is great. The faculties have created an excellent curriculum to help you get in touch with almost everything you need to be a data scientist/engineer. Sure they did not cover every relevant theory, but remember this is only a 3-month bootcamp, which is designed to give you a "jump start," not a full-time college degree.

    Besides the curriculum, most of the faculties are brilliant and always willing to help. Also, more importantly, you will make friends with people from many different backgrounds, which in my opinion is even more valuable than the course itself.

    Regarding the career development, Vivian and her team have made a great effort to help us to reach out to hiring managers and arrange internal referrals. However, unlike most of my fellows in the cohort, I have a pure business background (bachelor in accounting & master in analytics). Therefore even though I have been studying DS and programming through online courses for about one and half years before joining this bootcamp, I still ended up taking a Data Analyst position instead of continuing my job hunting for the Data Scientist jobs.

    At the end of the day, the cold fact is that most of the "real" data scientist positions require years of academic training and domain knowledge. The skills you have learned here at NYCDSA is definitely enough to grant you for an entry-level analytics position. However, if your target is the sexy DS title with six-digit salary, then unless you have a STEM Ph.D. or advanced degree in Computer Science / Statistics, this bootcamp will just be the start of a long journey.

  • Zachary Escalante • Data Scientist • Graduate
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    My background consists of undergraduate degrees in Math, Finance and a Masters in Financial Engineering. I found this 12-week intensive bootcamp to be extrememly valuable. Due to my academic background I was already familiar with some more technical concepts, but what NYC Data Science Academy did was to provide practical, hands on training in Python and R as they pertained to Data Analysis and Machine Learning. Following my time at NYC Data Science, I had intensive interviews for Data Science - focused roles in the finance community and I felt very well prepared. The staff is knowledgeable and routinely go above and beyond the contractual teaching time in order to ensure that each student receives the most instruction for their money. 

     

     

  • Frank Wang • Data scientist
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    I completed the Data Science bootcamp during the Spring of 2016. I enjoyed the Data Science bootcamp very much. It was a great experience overall.

    My background is PH.D in Physics and I has more than ten years research experience as research scientist.  I am probably the most senior person in the class.

    The course is very intensive and comprehensive. It covers most machine learning(ML) and data science skills:   ML in R and Python, website scraping, data visualization, big data with Spark and AWS. It is great to learn ML with both R and Python there. As I know, most boot camps don’t offer R. The school teaches a lot of stuff. It can be little overwhelming at the beginning. Everything I learned there is useful and helpful in my work. Just mention a few small things: Git, Mongodb, web scraping, AWS. I used all these skills in my work from day one.

    There are enough TAs there and they are consistently available to offer help on homework, projects and software. I used windows system, the installation of some software is not straight forward.  Their great supports saved me lot of time in that way, and I can have focused on my projects and homework.

    The instructors there are excellent too. They come from different background: statics, physics, and EE. Since the students come from different background, it is challenge for the lectures to deliver complicated pictures in clear way for most students.  They can present the material in a clear and logical sequence, explain complicated things in a simple way. I believed they did great job.

    NYC Data Science Academy have a lot connection from local companies and this can add great values for the job seeking. I live in west coast and still got continuous supports. I worked at a start-up right after the bootcamp and then went to another  larger company a few months later.

    Data Science is largely different from other science. It requires many skill sets and focuses on application much more than pure science. NYC Data Science Academy offer great opportunities for people who are seeking new career in data science in a quick way :  learn the fundamental skills of data scientist in the real world in 12 weeks.  I fell fully supported and encouraged from day one to the final job hunting.  

  • Chuan Jerry Sun • Data Scientist • Graduate
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    I have a Ph.D. in computer science, and I worked in tech industry for nearly two years. One thing I learned was that, great companies come and go, rise and fall, shine and fade. History repeats itself. However, no one can and shall beat the trend, since nothing is immortal. 

    With a strong belief that machine learning is the key to the ultimate Artificial General Intelligence (AGI), I decided to embrace emerging trend and immerse myself in the field of data science, the field in which a critical piece is machine learning. In joining the NYC Data Science Academy, my motivation was simple: refresh my eyesight, build the intuitions, solidify my understanding, and meet with talented people.

    It was a fantastic and rewarding journey with my fellow data scientists at the bootcamp. I will mainly concentrate on three aspects here: the curriculum, the instructors, and the like-minded peers. By no means they are complete, but hopefully they are useful for some people.

    Firstly, the curriculum is comprehensive and well-tailored to balance both the breadth and depth of the data science field. Although each year there are perhaps hundreds of new machine learning algorithms devised in academic world, the essential ones are no more than ten and still widely applied in industry (see here for full list: http://www.datasciencecentral.com/profiles/blogs/top-10-machine-learning-algorithms). Almost all of them, including their nuances, nuts and bolts, pros and cons, were covered in the curriculum and explained well by instructors who really know them.

    Secondly, the team is very efficient and professional. The instructors are technically proficient, articulate, and beyond my expectations. The lecture materials were self-contained, and covered related points that a data scientist should know. Especially, I was truly impressed by Luke’s passion in preparing useful materials and zestfully articulating his topics (such as sklearn framework, pandas, EM algorithms, or math, etc), by Zheyu’s professionalism and dedication in helping cohort to fix head-scratching problems and made their life easier, and by Shu’s enthusiasm in designing high-quality materials (sorting, hadoop, spark, etc) to broaden cohort’s skills. Besides, statistics was once a somewhat mysterious subject in my knowledge sphere. For a long time, I wanted to step my feet into its door to systematically cover it but I never managed to. I believe that if people want to explain something very easily without pain, they have to understand it deeply from beneath the bottom. It was Chris who unfolded the foundations of statistics and distilled many useful gists in my head within very short period of timespan. And he truly knew his subject inside out. I gained the gists, built the statistical intuition, and I am now more comfortable than ever before on this subject. 

    Thirdly, most importantly to me, the feeling of spending three months with a group of talented people is simply awesome. There is a saying that, “if you are in a room and you are the smartest one, then you are in the wrong room” (https://www.quora.com/Who-can-this-quote-be-attributed-to-If-youre-the-smartest-person-in-the-room-youre-in-the-wrong-room). There were many smart people in that cohort so I was sure I was in the right room. I felt that sharing the joy of enlightenment (when somebody/team achieved high scores in Kaggle leaderboard) or sadness of frustration (when somebody’s code did not work no matter what) with other talented minds was unique and unforgettable experience. Besides, through brainstorming with like-minded, new insights were sparked and new ideas were transferred. Eventually those ideas were distilled into my projects and morphed into my sixth sense of mental muscles. I felt that I was fortunate to be amongst a group of great fellows: there was no bullshitting, no day dreaming, and people were nice and nobody wanted to waste time. They all knew what they were after and worked extremely hard. I am sure I will miss them from time to time.

  • Joe Keepers • Fixed Income Quantitative Analyst • Graduate
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    This course was a masterpiece.  Derek Darves the instructor, quickly brought us to competency with the R programming language.  Then he expanded the course by introducing the packages used for analysis and visualization, progressing through introductory use to somewhat elegant and sophisticated programming challenges. Ultimately Derek brought us to a self-sufficiency level for continuing our R education. The course was a pleasure as Derek is clearly an R expert and aficionado weaving many practical tips and historical insights into the lectures.  His programming experience, statistical insights and extensions of the course materials gave it a graduate level feel, while never ignoring the fundamental skills being taught.  I highly recommend it.

  • Intro to R
    - 12/5/2016
    Ethan Weber • Student
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    In October, I signed up for the 12 week bootcamp which starts in January.  They recommended I take this course (free of charge) in preparation for the bootcamp to prepare myself in the language (I'm already comfortable in Python).

    I'm giving this course 5 stars because, for the format, I think they did a perfect job.  The instructor, Derek Darves, was definitely qualified and a nice guy in general.  They gave the tools to learn the basics of data analysis, manipulation and visualization.  

  • Sandra Barral • Assistant Professor Neurogenetics
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    Great course to get started with R programming. Convenient location in the city, nice classroom mates with very different backgrounds, and an amazing instructor, Derek has an impressive deep knowledge of R and he is a very talented and dynamic teacher

    Totally recommended to gain beginner understanding of this language

     

  • Vinod Shekar • Sr. Analyst, Marketing Analytics & Insights • Graduate
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    This was a great class that I truly enjoyed attending every Saturday for 5 weeks.  The class had a pretty steep learning curve but the slides and the homeworks did a good job of teaching the material.  Our instructor, Derek, was an R guru and could answer any queston we threw at him.  I definitely plan to continue learning R and I can attribute my enthusiasm to having taken this class.

  • Carlos S. • Fund Manager / Sr. Equity Analyst • Student
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    I attended NYCDSA 5-week course (5 full-time days, one per week) in 4Q16 as part of my preparation to start the same school bootcamp. This was a great introductory start to learn R due to the comprehensive syllabus and dedicated teacher effort. About the syllabus, you will learn Base R syntax and principal data structures identification and manipulation plus a bunch of other packages (e.g. DPLYR) that will make your life easier when treating data sets. The instructor was a Sr. Data Scientist that really gave us two sides: theoretical and hands-on day-to-day professional experience views. This was very helpful. I found that there're lots of courses out there but most of the times taught by recently-graduated teachers that haven't applied a lot of the syllabus to real-life professional situations. This for me was a plus. The only soft point of the course was that I would have liked to go more deeper into web scrapping, yet it's true this course name is 'data analysis and visualization in R' and not 'Web scrapping using R'. One advice only for prospect students: block your agendas during five weeks since you will need a lot of time to review the materials and deliver exercises, which after all it's not  a bad thing as it makes you feel good as you feel you have learnt a lot. Highly recommended.   

  • Bernard Ong • AVP, Head of Data Science & Application Architecture • Graduate
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    I would highly recommend the NYC Data Science Academy bootcamp. I have been an IT Executive for many years and wanted to supplant and round out my experience with skills in data science and machine learning, as it is my belief that these are one of the most critical technologies of our times. While I did try lot of the online courses, the academy brought a more organized, regimented, and immersive track that allowed me to not only learn and absorb the materials quickly, but also engage in real world projects and applications that would elegantly blend theory and practice.

    The quality of both the instructors and course materials is high. It has been an amazing learning experience for me and definitely worth the investment that helped me get to my next stage of career growth. Regardless if you are trying to supplant your post-graduate degree, thinking of doing a career switch to data science, or wanting to supplant your skills, the bootcamp offers that opportunity to push yourself to reach your maximum potential.

    That said, this bootcamp requires that you bring your A-game into the arena. This is not an easy course to take, and for good reasons. The bootcamp will stretch you to surpass what you think your limitations are and push you to be at your best at all times. This requires 100% commitment from your part. Anything less will not be good enough. If you fully commit yourself, you will emerge from this course with a renewed sense of passion in this exciting field. If there is one regret, it would be that I should have done this bootcamp sooner.

    The job opportunities for data science and machine learning specialists are just amazing. Since getting the certification (even before then), the contacts and network I have made in the data science community have accelerated at a rapid pace. The reachout from recruiters have also increased significantly. The demand for data scientists continues to climb. In hindsight, it was a great decision for me to have made the jump to go through the bootcamp, as I am now working on numeorus opportunities that allow me be more creative and innovative.

    The academy is managed and run by an amazing team of people who have helped me through the many months of learning and growth. They have been such a strong support system for me as I take the next journey through my career as a Data Scientist. The academy has also opened my eyes to so many wonderful experiences and allowed me to validate the opportunities and potential of this exciting field I am in. I have learned so much and the real skills I have acquired will be of tremendous value as I embark on pursuing my passions.

    As the saying goes... "Never give up on a dream just because of the time it will take to accomplish it. The time will pass anyway." I pursued mine and living it, now it's up to you to pursue yours.

  • 12-Week Bootcamp
    - 11/30/2016
    Linlin Cheng • Data Scientist • Graduate
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    The bootcamp provides an extensive overview of the most used Machine Learning algorithms in addition to RShiny, visualization and webscrapping (using Python). Like any classes in college and graduate school, instructors are there to walk you through the basics and it really is up to you on how much effort you would like to put in. However,  the TAs and instructors are far more accessible than any class I've taken so far!!! Ode to the TAs! In addition, the fellow students at NYCDSA are really nice people in general. And knowing that you are not alone really helps during those late nights at the bootcamp!

    I would recommend the bootcamp to anyone in need of a career transition into Data Science, willing to go above and beyond, and are comfortable with either statistics or basic programming. 

  • Joseph Wang • Senior data scientist • Applicant
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    I was an experienced academic professional with one-year experience in the oil-gas industry. After I joined the oil industry with a big oil company, the oil price started to go down till now. This caught me out of guard.  As I expected, I was laid off  at the end of 2015 .

    By checking with other programs, I realize NYC DATA SCIENCE ACADEMY will provide the necessary tools and the big pictures about the emergent field of data science.

    The instructors and TAs from the school are from diverse backgrounds including statisticians, physicists, mathematicians, and computer scientists. They make Ph.D. students feel comfortable to ask more technical and fundamental questions without feeling being discouraged.   They also let you be responsible for choosing your own projects to enhance your practice in data science in general. If you are a person who is very solid in any programming languages in the past, this is the place for you to learn the fundamentals of machine learning and statistics. In the end, you can put these skills together to be confident to attack data science problems in general. You will have a very strong foundation to jumpstart your new career in data science.

    The program is very intense and I was constantly trying to catch up with the learning, homework, and projects. There is no time to think about negatives. This was also good once you find a new job you can handle the pace from the new job better. I strongly recommend particularly the students with excellent postdoctoral experience to make a career transition to join this program. Consider this as an investment for your career. (The tuition potentially can be offset by signing bonus from your future employers).  

Thanks!