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NYC Data Science Academy

New York City, Online

NYC Data Science Academy

Avg Rating:4.84 ( 289 reviews )

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

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

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

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  • 12-Weeks In-Person Data Science Bootcamp

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    Start Date July 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
    July 6, 2020 - New York City Apply by June 19, 2020
  • Big Data with Amazon Cloud, Hadoop/Spark and Docker

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    Data Science, Hadoop, Spark, Data Structures, Python, Cloud Computing
    In PersonPart Time5 Hours/week2 Weeks
    Start Date None scheduled
    Cost$2,990
    Class size10
    LocationNew York City
    This is a 6-week evening program providing a hands-on introduction to the Hadoop and Spark ecosystem of Big Data technologies. The course will cover these key components of Apache Hadoop: HDFS, MapReduce with streaming, Hive, and Spark. Programming will be done in Python. The course will begin with a review of Python concepts needed for our examples. The course format is interactive. Students will need to bring laptops to class. We will do our work on AWS (Amazon Web Services); instructions will be provided ahead of time on how to connect to AWS and obtain an account.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelStudents are expected to be familiar with using an operating system from the command line; knowledge of Python is helpful.
    Placement TestNo
    InterviewNo
  • Data Science with Python: Data Analysis and Visualization (Weekend Course)

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    Start Date June 13, 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
    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, Artificial Intelligence, Machine Learning
    In PersonPart Time7 Hours/week5 Weeks
    Start Date June 13, 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
    June 13, 2020 - New York City Apply by June 12, 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 None scheduled
    Cost$2,190
    Class size15
    LocationNew York City, Online
    This course is designed to provide a comprehensive introduction to R. Students will practice programming and analyzing data with R. Students will learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models to data. In addition to a theoretical framework in which to understand the process of data analysis, this course focuses on the practical tools needed in data analysis. This course also covers the creation of dynamic reports with the knitr package in R as well as the creation of dynamic dashboards with R Shiny. By the end of the course, students will have mastered the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting the code.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelBasic knowledge about computer components Basic knowledge about programming
    Prep WorkNone
    Placement TestNo
    InterviewNo
  • Data Science with R: Machine Learning (Weekend Course)

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    Data Science, R, Machine Learning
    In PersonPart Time7 Hours/week6 Weeks
    Start Date None scheduled
    Cost$2,990
    Class size40
    LocationNew York City, Online
    This 35-hour Machine Learning with R course introduces both the theoretical foundation of machine learning algorithms as well as their practical applications in R. It will introduce you to data mining, performance measures and dimension reduction, regression models, both linear and generalized, KNN and Naïve Bayes models, tree models, and SVMs as well as the Association Rule for analysis. After successfully completing this course, you will be able to break down the mathematics behind major machine learning algorithms, explain the principles of machine learning algorithms, and implement these methods to solve real-world problems. Unit 1: Foundations of Statistics and Simple Linear Regression Unit 2: Multiple Linear Regression and Generalized Linear Model Unit 3: kNN and Naive Bayes, the Curse of Dimensionality Unit 4: Tree Models and SVMs Unit 5: Cluster Analysis and Neural Networks Final Project After 35 hours of structured lectures, students are encouraged to work on an exploratory data analysis project based on their own interests. A project presentation demo will be arranged.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelKnowledge of Python programming Able to munge, analyze, and visualize data in Python
    Prep WorkKnowledge of R programming Able to munge, analyze, and visualize data in R
    Placement TestNo
    InterviewNo
  • Deep Learning with Tensorflow (Weekends and In-Person Only)

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    Start Date None scheduled
    Cost$2,990
    Class size15
    LocationNew York City
    Via analogy to biological neurons and human perception, this course is an introduction to artificial neural networks that brings high-level theory to life with interactive labs featuring TensorFlow, the most popular open-source Deep Learning library. Essential theory will be covered in a manner that provides students with an intuitive understanding of Deep Learning’s underlying foundations. Paired with hands-on code run-throughs in Jupyter notebooks as well as strategies for overcoming common pitfalls, this foundational knowledge will empower individuals with no previous understanding of neural networks to build production-ready Deep Learning applications across the major contemporary families: Convolutional Nets for machine vision; Long Short-Term Memory Recurrent Nets for natural language processing and time series analysis; Generative Adversarial Networks for producing realistic images; and Reinforcement Learning for playing video games.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelObject-oriented programming, ideally Python (introductory course: https://nycdatascience.com/courses/introductory-python/) Simple shell commands, e.g., in Bash (tutorial of the fundamentals: https://learnpythonthehardway.org/book/appendixa.html)
    Placement TestNo
    InterviewNo
  • Full-time Online Data Science Bootcamp

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    Start Date July 6, 2020
    Cost$17,600
    Class size25
    LocationOnline
    This program was designed for students that have the time to be a full-time student, but can't commute to our school. Students will be placed on a rigorous curriculum that spans from 9:30 AM to 6:00 PM EST as well as have access to prerecorded modules with over 1000 coding challenge questions on online learning platform for additional practice. In addition, they have access to dedicated TA’s as well as the larger network of a shared slack channel between both in-person and remote bootcamp students. Classes: You will learn streamed lectures as well as have access to prerecorded modules and coding questions for additional practice. Personalized Job Support: Students also have access to the full resources of NYC Data Science Academy to help them find their dream job upon graduation. Our curriculum covers the expanse of all the skills required in the data science industry. We cover both R and Python as well as Machine Learning Theory, Big Data, and Deep Learning.
    Financing
    Deposit5000
    Financing
    • Full Tuition Total $17,600
    • Climb Credit Loan $400* pm for 60 months
    • SkillsFund Student Loan $397.88 pm for 60 months

    Tuition PlansWe have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months.
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    ScholarshipLimited number of scholarships available to qualified candidates.
    Getting in
    Minimum Skill LevelIdeal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming.
    Prep Workhttp://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/
    Placement TestNo
    InterviewYes
    More Start Dates
    July 6, 2020 - Online Apply by June 19, 2020
  • Introductory Python (Evenings)

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    Start Date June 2, 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
    June 2, 2020 - New York City Apply by June 1, 2020
  • Part-time Online Data Science Bootcamp

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    Start Date July 6, 2020
    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
    More Start Dates
    July 6, 2020 - Online Apply by June 19, 2020

Shared Review

  • Anonymous • Graduate
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    This bootcamp differentiates itself in its teaching of the important theory and statistics. Christopher Peter Makris does an exceptional job of boiling down complex topics into understandable concepts without sacrificing rigor. If CPM is there, you'll learn a lot. I left with a real love of statistics and machine learning theory.

    Without him, there isn't much offered here that you couldn't get on Coursera. The job placement is helpful if Vivian decides she can help you. She basically helps the PhDs get good jobs so she can post the success story, but doesn't spend as much time helping the younger students get admittedly less sexy jobs. 

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

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

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

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

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

     It was hard to keep up as I was also doing a full time job while attending the online bootcamp. NYCDSA provided many service to keep students on track. One of the service I like the most is the TA assistance. I was paired with a TA and we met regularly to go over my progress and the questions I had. My TA was also a NYCDSA student before and was working in the industry as data scientist. Therefore, he not only knew what my struggles were on the course work, and he also taught me a lot of practical experience that was using in the industry.   
  • Aparna Sundaram  User Photo
    Aparna Sundaram • Graduate • Verified via LinkedIn
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    I took the 2019 summer bootcamp at the Academy, and chose it over other bootcamps based on the excellent reviews and ratings. I was not disappointed. Aiko, Luke, Alex, Drace and Michael were terrific teachers, and taught us Python, R and Machine Learning from scratch. The bootcamp is three months long, but because there is a lot of material to cover, it is incredibly fast paced. The material was however covered in a thorough and accessible manner. The Academy also does a nice job of preparing us ahead of time for the volume of work to come, by having the students do a lot of prework before the first day of class. In addition we get excellent and detailed course notes (which I refer to all the time). Overall it was a fantastic experience, and I strongly recommend it to anyone looking to build their skills in data science.
  • NYCDSA Bootcamp
    - 2/28/2020
    Tomas  User Photo
    Tomas • Data Scientist • Graduate • Verified via LinkedIn
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    I chose NYCDSA because of its focus on data science applications in both R and Python and because of the quality of the faculty. The program lived up to every expectation. I came from a quantitative background, but the program did an excellent job of providing material so that it was accessible to people with a less quant heavy background, while also allowing people with a quant background to take a deeper dive. I was looking to switch from finance to a data science role, and this program helped me bridge the gap. The program is intense but deeply gratifying.
  • Edward Tong, PhD  User Photo
    Edward Tong, PhD • Data Scientist Lead • Student Verified via LinkedIn
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    The Deep Learning course at NYC Data Science Academy provides a solid introduction to the fundamentals and application of the suite of deep learning models. The instructor, Dr Jon Krohn (DPhil, Oxon), has a talent for teaching deep learning in an accessible, conceptual manner and for demonstrating the wide range of applications that benefit from these neural network architectures. The course content covers the basics of neural networks from the basis of neurons, activation functions to shallow / dense layers and to more advanced models including convolutional neural networks (CNNs), long short-term memory (LSTMs), auto-encoders, Generative Adversarial Networks (GANs) and reinforcement learning. Course readings are taken from the recently published Deep Learning Illustrated book, co-authored by the instructor. There is heavy emphasis on coding using TensorFlow 2.0 and Keras in Jupyter Notebooks along with an introductory lesson on PyTorch. Dr Krohn has a very extensive code repository featuring a myriad of deep learning architectures. The lessons guide us through model code line by line, gradually building up in model complexity across the weeks. Dr Krohn discusses model tuning and addresses common model fitting pitfalls including preventing over-fitting and exploding / vanishing gradients. By the end of the course, the students are able to showcase projects fitting several advanced architectures including CNNs, RNNs and LSTMs to interesting datasets for image recognition, speech recognition and natural language processing. This course is highly recommended if you are looking for a comprehensive and stimulating face-to-face introduction to one of the most revolutionary methodologies in machine learning today.

  • A Rare Experience
    - 12/22/2019
    Justin Ng  User Photo
    Justin Ng • Student • Verified via LinkedIn
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    I took Jon Krohn’s deep learning course in the fall/winter of 2019.

    Jon is that rare communicator with the aptitude to succinctly explain rigorous and complex topics in a digestible fashion. His course is an ambitious undertaking, but Jon makes the subject matter as accessible as it’s likely to be. After the course, you’ll not only possess a foundational understanding of neural nets, but also Jon’s compilation of resources for your continued self-experimentation. Jon’s approachability as an instructor, his unabashed love of this cutting-edge science, and his genuine interest in seeing his students advance their understanding could not place you in better hands.

  • Totally worth it!
    - 12/18/2019
    Mario Valadez Trevino  User Photo
    Mario Valadez Trevino • Graduate • Verified via LinkedIn
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    I have more than 15 years of experience working in supply chain and I took the bootcamp with the idea of updating my data analysis skills and obviously also learn about machine learning, clustering, algorithms, etc. and I can say that it was totally worth it. The material, explanations and projects are really very interesting and challenging.

    The main reason I choose this school was because it was the most professional one, most of the teachers had been there for a long time and they don't switch instructors in the middle of the cohort as most other schools.

    A normal day is, usually, theory for about 3 hours in the morning and then practice and homeworks in the afternoon.

    The part that I liked more is that the school really support the students in making sure we learn but also are able to create a very friendly and collaborative environment. I made really great friends!!

  • 5-Star Experience
    - 12/17/2019
    Xavier  User Photo
    Xavier • Graduate • Verified via LinkedIn
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    The reason I picked this Bootcamp over the other's was that after talking to the admission office they seem to be really serious about what they were teaching and the people they admit to their program. In my case, I was looking for a challenging environment where I could develop my programming skills and learn new skills in the data science world and the academy helped me achieve what I was looking for and much more.


    The academy instructors are very well prepared and passionate about what they do. The only downside is that given only 12 weeks is hard to understand every single thing they are teaching, for example, one day you are learning Random Forest and the next day you are learning something different. But something that they planned really well and is really helpful is that since you are learning Machine Learning in R and Python when switching to the other language the theory remains the same only the code changed, so in a way, you are reviewing theory twice.

    The whole experience was incredible, the people that attended my cohort were very smart people coming from different backgrounds like finance, physics, business, engineering, to name a few and from top universities like Harvard, Oxford, Cornell and also different countries which made the whole experience much more interesting. What I enjoyed the most was that working with these different people made you look at data from very different perspectives and in result have a richer analysis of a simple dataset.

    After the Bootcamp feel ready to start looking for a data science job, I was already in a quantitive field but this program has really helped me gain that confidence I needed to have a career change.

  • Aaron Festinger  User Photo
    Aaron Festinger • Graduate • Verified via LinkedIn
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    NYC Data Science Academy was my first choice because of my interest in data science, and their reputation as the best data science program. They did not disappoint.

    As a recently separated veteran with a master's degree in physics, I was looking for a way to renew my credentials for employment in the technology sector. A friend of mine told me about his successful full-stack engineering boot camp experience and subsequent employment, so I began doing some research. I did not know what data science was, at the time, but I read about it on Course Report, and it seemed like a perfect fit for me, so I signed up. 

    NYCDSA is exactly as advertised: an intensive program on data science methodology aimed at students from a wide variety of backgrounds. With my background in physics, math, and C++ and Java coding, I felt that the Python and R syntax taught at NYCDSA was not too difficult. Other students were less prepared but often did okay anyhow. The course began with Python and R syntax for handling and visualizing data, and then continued with machine learning methods in both languages as well. SQL and Docker were also covered, but rather briefly. At the end of the course, deep learning and Tensorflow were introduced, as well as Spark and Hadoop. I would have preferred that more time be dedicated to those topics, but this is a three-month boot camp, so time is limited. Nevertheless, given the allotted time, I feel that I have achieved an incredible amount, and I'm very happy with my experience. Boot camp is not cheap in either time or money, but this one was well worth both. I intend to continue building on the knowledge, experience, portfolio, and network that I have accumulated at NYCDSA as a professional data scientist.

  • Michael Dollar  User Photo
    Michael Dollar • Credit/Fraud Risk Analyst • Graduate • Verified via LinkedIn
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    I needed the shortest path to pivot from a research position in physics to a career in data science.  I considered grad school, but I have a family, and I need to be there for my kids during their developmental years.  NYC Data Science Academy offered an effective restructuring of skills over the course of three months.  Not only did I learn skills in data sctructures, statistics, coding, and machine learning, but I also learned skills necessary in the job-hunting process.  The support that was given to me during my time at NYCDSA was instrumental in receiving a job offer from a well-stablished company in financial services.

Thanks!