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NYC Data Science Academy

New York City, Online

NYC Data Science Academy

Avg Rating:4.83 ( 266 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)

    Apply
    Start Date
    Rolling Start Date
    Cost
    $17,600
    Class size
    50
    Location
    New 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
    Climb Credit Loan $400* pm for 60 monthsFull Tuition Total $17,600Skills Fund Student Loan$397.88 pm for 60 months
    Tuition Plans
    We have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months.
    Refund / Guarantee
    NYC 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.
    Scholarship
    Limited number of scholarships available to qualified candidates.
    Getting in
    Minimum Skill Level
    Ideal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming.
    Prep Work
    http://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/
    Placement Test
    No
    Interview
    Yes
  • Big Data with Amazon Cloud, Hadoop/Spark and Docker

    Apply
    Data Science, Python, Hadoop, Spark, Data Structures
    In PersonPart Time5 Hours/week2 Weeks
    Start Date
    January 14, 2020
    Cost
    $2,990
    Class size
    10
    Location
    New 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
    Deposit
    N/A
    Getting in
    Minimum Skill Level
    Students are expected to be familiar with using an operating system from the command line; knowledge of Python is helpful.
    Placement Test
    No
    Interview
    No
    More Start Dates
    January 14, 2020 - New York CityApply by January 10, 2020
    April 21, 2020 - New York CityApply by April 15, 2020
  • Data Science with Python: Data Analysis and Visualization (Weekend Course)

    Apply
    Start Date
    October 27, 2019
    Cost
    $1,590
    Class size
    20
    Location
    New 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
    Deposit
    N/A
    Refund / Guarantee
    NYC 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 Level
    Knowledge 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 Test
    No
    Interview
    No
    More Start Dates
    October 27, 2019 - New York CityApply by October 25, 2019
    January 19, 2020 - New York CityApply by January 15, 2020
    March 7, 2020 - New York CityApply by March 1, 2020
  • Data Science with Python: Machine Learning (Weekend Course)

    Apply
    Data Science, R, Machine Learning, Artificial Intelligence
    In PersonPart Time7 Hours/week5 Weeks
    Start Date
    October 27, 2019
    Cost
    $1,990
    Class size
    10
    Location
    New 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
    Deposit
    N/A
    Getting in
    Minimum Skill Level
    Completion of Data Science with Python: Data Analysis; Data Science with R: Machine Learning
    Placement Test
    No
    Interview
    No
    More Start Dates
    October 27, 2019 - New York CityApply by October 25, 2019
    January 19, 2020 - New York CityApply by January 15, 2020
    March 7, 2020 - New York CityApply by March 1, 2020
  • Data Science with R: Data Analysis and Visualization (Weekend Course)

    Apply
    Data Science, R, Data Visualization, Data Analytics , Data Structures
    In PersonPart Time7 Hours/week6 Weeks
    Start Date
    October 26, 2019
    Cost
    $2,190
    Class size
    15
    Location
    New 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
    Deposit
    N/A
    Getting in
    Minimum Skill Level
    Basic knowledge about computer components Basic knowledge about programming
    Prep Work
    None
    Placement Test
    No
    Interview
    No
    More Start Dates
    October 26, 2019 - New York CityApply by October 24, 2019
    January 18, 2020 - New York CityApply by January 15, 2020
    April 18, 2020 - New York CityApply by April 10, 2020
  • Data Science with R: Machine Learning (Weekend Course)

    Apply
    Data Science, R, Machine Learning
    In PersonPart Time7 Hours/week6 Weeks
    Start Date
    October 26, 2019
    Cost
    $2,990
    Class size
    40
    Location
    New 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
    Deposit
    N/A
    Getting in
    Minimum Skill Level
    Knowledge of Python programming Able to munge, analyze, and visualize data in Python
    Prep Work
    Knowledge of R programming Able to munge, analyze, and visualize data in R
    Placement Test
    No
    Interview
    No
    More Start Dates
    October 26, 2019 - New York CityApply by October 24, 2019
    January 18, 2020 - New York CityApply by January 15, 2020
    April 18, 2020 - New York CityApply by April 15, 2020
  • Data Science with Tableau (Online)

    Apply
    Data Science, Data Visualization, Business Intelligence
    In PersonPart Time5 Hours/week3 Weeks
    Start Date
    Rolling Start Date
    Cost
    $1,590
    Class size
    20
    Location
    Online
    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
    Deposit
    1590
    Refund / Guarantee
    NYC 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 Level
    Know 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 Work
    Before 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 Test
    No
    Interview
    No
  • Deep Learning with Tensorflow (Weekends and In-Person Only)

    Apply
    Start Date
    October 19, 2019
    Cost
    $2,990
    Class size
    15
    Location
    New 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
    Deposit
    N/A
    Getting in
    Minimum Skill Level
    Object-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 Test
    No
    Interview
    No
    More Start Dates
    October 19, 2019 - New York CityApply by October 15, 2019
  • Introduction to Python (Online)

    Apply
    Data Science, Python, Data Visualization, SQL, Data Structures
    OnlinePart Time5 Hours/week2 Weeks
    Start Date
    Rolling Start Date
    Cost
    $795
    Class size
    25
    Location
    Online
    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
    Deposit
    795
    Refund / Guarantee
    NYC 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 Level
    Comfort with Windows, Mac or Linux environment and ability to install third-party software.
    Prep Work
    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.
    Placement Test
    No
    Interview
    No
  • Introductory Python (Evenings)

    Apply
    Start Date
    October 21, 2019
    Cost
    $1,590
    Class size
    40
    Location
    New 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 / Guarantee
    NYC 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 Level
    This Introductory Python class is designed for computer-literate people with no programming background who wish to learn basic Python programming.
    Prep Work
    In 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 Test
    No
    Interview
    No
    More Start Dates
    October 21, 2019 - New York CityApply by October 18, 2019
    January 14, 2020 - New York CityApply by January 10, 2020
    March 9, 2020 - New York CityApply by March 5, 2020
  • Remote Immersive Data Science Bootcamp (Online)

    Apply
    Start Date
    Rolling Start Date
    Cost
    $17,600
    Class size
    25
    Location
    Online
    Our Remote Intensive 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
    Deposit
    5000
    Financing
    Climb Credit Loan $400* pm for 60 monthsFull Tuition Total $17,600Skills Fund Student Loan$397.88 pm for 60 months
    Tuition Plans
    We have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months.
    Refund / Guarantee
    NYC 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.
    Scholarship
    Limited number of scholarships available to qualified candidates.
    Getting in
    Minimum Skill Level
    Ideal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming.
    Prep Work
    http://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/
    Placement Test
    No
    Interview
    Yes
  • Remote Self-paced Data Science Bootcamp (Online)

    Apply
    Start Date
    Rolling Start Date
    Cost
    $17,600
    Class size
    25
    Location
    Online
    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
    Deposit
    17600
    Financing
    Climb Credit Loan $400* pm for 60 monthsFull Tuition Total $17,600Skills Fund Student Loan$397.88 pm for 60 months
    Tuition Plans
    We have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months.
    Refund / Guarantee
    NYC 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.
    Scholarship
    Limited number of scholarships available to qualified candidates.
    Getting in
    Minimum Skill Level
    Ideal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming.
    Prep Work
    http://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/
    Placement Test
    No
    Interview
    Yes

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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.

  • Shuheng Li • Data Science Analyst • Graduate
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    *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
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    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
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    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).  

  • Jingyu Zhang • Student
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    I had great experience with this bootcamp. Intense program, nice course contents.  Comprehensive training on coding,machine learning, presentation and writing. I had five projects done and blog/github posting. The package drove to  interview opportunities.  During and after the program, I still keep having help on polishing resume, mocking interview, and receiving job opportunites. Finally, I accepted data analyst postion near my home in Portland. 

  • Job Update
    - 10/27/2016
    Jurgen de Jager • Graduate
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    Quick addition to the review I wrote on 9/28/2016.

    I recieved an offer from Barclays today to work for them as a data scientist. Vivian introduced me to the lead data scientist and helped me through every part of the interview process. The encouragment and assistance from her and the whole team has been great. As I mentioned before, the staff at the academy go above and beyond in helping you land your dream job.

  • Brian Saindon • Data Scientist • Graduate
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    I completed the Data Science bootcamp during the Fall of 2015 and immediately was hired as a Data Scientist the following January.  During the NYCDSA bootcamp, I converted my skill set from a traditional statistician/analyst to a data scientist.  This bootcamp elevated my ability to apply a variety of advanced machine learning algorithms using codes like Python or R.  Today, I continue to use the skills that I had developed during this bootcamp.  In my opinion, this bootcamp was successful for me for three reasons:

    Course Content:  

    The course content covered coding in SQL, python and R during my time at the bootcamp.  As a data scientist, ability to code in this basic languages is critical to developing and testing statistical hypotheses and machine learning concepts.  All machine learning examples had supporting Python and R code to facilitate students' application of these algorithms.  This bootcamp covered application of Spark during the last few weeks of the course.  Knowing Spark capabilities was particularly helpful in my current position as a data scientist.

    The bootcamp covered traditional statistical concepts such as hypothesis testing, linear regression and logistic regression as well as advanced machine learning algorithms such as K-Means clustering and Neural Networks.  The bootcamp strategically provided theoretically background for these concepts in conjunction with worked out examples in R and Python.  Knowing how to apply all of these algorithms helps me to rapidly move through proof-of-concepts in my current day-to-day.

    Instructors:  

    During my cohort, the bootcamp instructors were incredibly dedicated to helping the students succeed.  Instructors were consistently available to answer coding questions on-site in person or off site via slack or email.  I was always satisfied that the instructors were able to answer my coding and ML questions rapidly and completely.

    Job Search:  

    The bootcamp helped me find several job interviews towards the end of the bootcamp.  It was  clear that the NYCDSA had access to an increasing network of employers looking to hire data scientists.  During the interview process, I had felt that the bootcamp prepared me to answer all of the data science interview questions during each interview.

    It has been over a year since I first enrolled in the NYCDSA bootcamp and I continue experience the benefits of the bootcamp in my day-to-day job as a data scientist.  I strongly recommend this bootcamp to anyone looking to make a career transition into the data science field.

  • Tyler Knutson • Graduate
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    The 12 week bootcamp at NYC Data Science Academy combines everything a budding data scientist needs while finding a balance between depth and bredth.  Coming from a background in strategy consulting I appreciated the intense nature of the schedule with tight turnarounds and explicit deadlines for coursework and project submission.  You'll be given the chance not only to learn from some of the best instructors with phenomenal backgrounds and real world experience, but also to showcase your own skills and ideas through 5 data science projects where you get to form hypotheses on data sets of interest to you and make meaningful conclusions.

    Though the pace is relentless, the program is very managable given the dedication of the instructors to see you succeed.  You'll form great relationships not only with the staff but with other gifted students as well as you all learn together about this exciting field.

  • Data Scientist
    - 10/14/2016
    Wanda Wang • Graduate
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    The NYC Data Science Academy provided an unparalleled experience - from the high quality of the instruction material to the dedicated teachers and staff, I gained both a strong personal and professional network and a greater exposure to the world of data science. The return on my investment was substantial, as I've successfully received five competitive job offers in a variety of industries (1 in finance, 2 in marketing, 2 in health) within just a few months of graduating. 

    Most importantly, learning in the immersive environment quickly accelerated my technical know-how. I became adept at R, Python in addition to structured thinking, open-ended problem solving, and communicating my ideas and work across to a wider audience. 

    Additionally, preparing for the five project presentations and homework assignments with like-minded peers in my cohort also positively influenced my experience. Sharing ideas, knowledge and experiences with my classmates, and TAs - encouraged me to creatively explore every approach when faced with a challenging problem or in-class lab. 

    I am grateful for my time at the NYC Data Science Academy. I highly recommend enrolling if you're undecided - it's an awesome place to prepare for a new career in data science and machine learning.

     

  • Trinity Yu • Graduate
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    I am writing to strongly recommend NYC Data Science Academy to anyone who is looking for opportunities as a data scientist. As a recent graduate student of the 6th data science bootcamp of NYC Data science Academy, I was immediately able to find an internship in an hedge fund as a quantitative trading analyst 2 weeks after I graduate from the bootcamp and currently actively seeking full time job under the guidance of Vivian, the founder of NYC Data Science Academy. Before attending the bootcamp, I graduated from Courant Institute of Mathematical Sciences, New York University with a master of science degree in Applied Math. I have always been in love with math and attracted by the beauty of proofs and theorems. However, I did not know how to make a use of my quantitative background into real life. By an occasional chance, NYC Data Science Academy came to my attention. I found out that they offer a highly immersive Data Science program involving data strategy and hands on expertise on machine learning, big data, advanced statistics and analytics. Students are able to solid R and Python development skills, various model ensembiling and stacking strategies and gain knowledge including but not limited to Unix, SQL, Hadoop, Spark etc. Soon after I contacted the academy, I got an chance to talk with Vivian and immediately feel that it is the right place for me. My intuition proved to be right after I attended the bootcamp because I not only strengthened my knowledge and learnt tons of new skills but also get to know many talented people from various background and developed strong network connection with them. The training contents are well-designed and students are required to complete 5 projects in the progress which comprehensively exhibits one's skills from visualization, web interactive app to machine learning and big data. To better assist the students with their job hunting process, the instructors and staffs in the NYC Data Science Academy worked very hard to organize a fantastic career fair and invited more than 30 companies and recruiters including JP Morgan, BAM, Google, FaceBook and Spotify. Students were able to show their accomplishment to the data scientists in the company directly and make connection with them. It was such a wonderful and unforgettable journey with my fellow data scientists. 

  • Jurgen de Jager • Graduate
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    The decision to enroll in this Bootcamp was one of the best decisions I’ve ever made. I had high expectations coming in to the program, mostly due to the reviews I’ve read, yet the 12 weeks I spent at the academy exceeded those expectations. The coursework is difficult enough to challenge those with a PhD, while the instructor’s and TA’s help out to the extent that even those with a Bachelor’s will find it manageable.

    The program covers a wide array of topics, combining theory and application to give you a well rounded understanding of the material. Students are encourage to learn by doing, and home-works are given out 2-3  times a week, with deadlines not always easy to meet. But given how much the instructors offer to help, students usually always find a way.

    The whole team goes above and beyond to help out not only with teaching you data science, but also with things like interview readiness, job-placement, and helping you build a great portfolio.

    You are surrounded with like-minded people for 12 weeks, forming great friendships learning from each other. You are tutored and lectured by industry professionals who go out of their way to make sure you understand the material. You are exposed to cutting edge softwares, advanced machine learning algorithms, and industry best practices. You are helped with building a portfolio, creating a great resume and how to pitch your work to employers.

    I’m truly happy I did this program, and so will you.

     

  • Arda Kosar • Senior Data Scientist • Graduate
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    I moved to United State in October 2015. I wanted to do a career transition and applied to NYC Data Science Academy 12-week Full-Time Data Science program after some searching over the web.

    I come from a Mechatronics Engineering background, with 2+ years as a Business and Sales Consultant and an MBA in general business management. At the beginning I was a little bit afraid about the programming side because the only programming experience I had is a course in my Bachelor's about C++ and two simple projects throughout that course. Also mathematically speaking during my bachelor's I only took linear algebra and differential equations, not that much statistics and programming before entering the bootcamp.

    The curriculum was mostly includes programming with SQL, R and Python and also learning to implement machine learning algorithms in R and Python. It is structured so well that eventhough you have a little experience with programming before, they start teaching it from basic level and build up nicely so that you do not get lost. 

    The instructors are incredibly helpful during your learning process, homeworks and projects. The lectures are fun with modern learning tools.

    They are known well in the industry. So when you apply to jobs the people will know the quality of NYC Data Science Academy and it will not be difficult for you to get interviews. They will also make it easier for you to meet with many hiring partners. 

    My overall experience with NYC Data Science Academy was wonderful and I can easily say that it was the best investment that I did for myself. 

    The most important thing to consider before applying is you should be ready to invest an intense 3-months. And also you should be ready to work hard as a student again.

    If you are thinking about enhancing your career to a new level and enter to the fantastic world of Data Science, I strongly recommend NYC Data Science Academy.

Thanks!