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NYC Data Science Academy

New York City, Online

NYC Data Science Academy

Avg Rating:4.83 ( 271 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-Week Immersive Data Science Bootcamp (In-person)

    Apply
    Start Date Rolling Start Date
    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
    • Climb Credit Loan $400* pm for 60 months

    • Full Tuition Total $17,600

    • Skills Fund 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
  • Big Data with Amazon Cloud, Hadoop/Spark and Docker

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    Data Science, Python, Hadoop, Spark, Data Structures
    In PersonPart Time5 Hours/week2 Weeks
    Start Date January 14, 2020
    Cost$2,990
    Class size10
    LocationNew York City
    This is a 6-week evening program providing a hands-on introduction to the Hadoop and Spark ecosystem of Big Data technologies. The course will cover these key components of Apache Hadoop: HDFS, MapReduce with streaming, Hive, and Spark. Programming will be done in Python. The course will begin with a review of Python concepts needed for our examples. The course format is interactive. Students will need to bring laptops to class. We will do our work on AWS (Amazon Web Services); instructions will be provided ahead of time on how to connect to AWS and obtain an account.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelStudents are expected to be familiar with using an operating system from the command line; knowledge of Python is helpful.
    Placement TestNo
    InterviewNo
    More Start Dates
    January 14, 2020 - New York City Apply by January 10, 2020
    April 21, 2020 - New York City Apply by April 15, 2020
  • Data Science with Python: Data Analysis and Visualization (Weekend Course)

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    Start Date January 19, 2020
    Cost$1,590
    Class size20
    LocationNew York City, Online
    This five week course is an introduction to data analysis with the Python programming language, and is aimed at beginners. We introduce how to work with different data structure in Python. We covered the most popular modules, including Numpy, Scipy, Pandas, matplotlib, and Seaborn, to do data analytics and visualization. We use ipython notebook to demonstrate the results of codes and change codes interactively during the class. Our past students include people with no programming experience or those who have minimal exposure to Python. Students told us our classes are very informative, engaging, and hands-on.
    Financing
    DepositN/A
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    Getting in
    Minimum Skill LevelKnowledge of basic data types (e.g. string, numeric), data structures (e.g. list, tuple, dictionary) Familiarity with concepts of list comprehension and for/while loop
    Placement TestNo
    InterviewNo
    More Start Dates
    January 19, 2020 - New York City Apply by January 15, 2020
    March 7, 2020 - New York City Apply by March 1, 2020
  • Data Science with Python: Machine Learning (Weekend Course)

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    Data Science, R, Machine Learning, Artificial Intelligence
    In PersonPart Time7 Hours/week5 Weeks
    Start Date January 19, 2020
    Cost$1,990
    Class size10
    LocationNew York City, Online
    This 20-hour Machine Learning with Python course covers all the basic machine learning methods and Python modules (especially Scikit-Learn) for implementing them. This includes linear regression, Naïve Bayes classifiers, logistic regression, linear discriminant analysis, cross-validation, bootstrapping, feature selection, regularization, model selection, SVM, decision trees, random forest, PCA, K-Means, and Hierarchical clustering. In addition, this course teaches the basics of natural language processing. After successfully completing this course, you will be able to explain the principles of machine learning algorithms and implement these methods to analyze complex datasets and make predictions in Python.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelCompletion of Data Science with Python: Data Analysis; Data Science with R: Machine Learning
    Placement TestNo
    InterviewNo
    More Start Dates
    January 19, 2020 - New York City Apply by January 15, 2020
    March 7, 2020 - New York City Apply by March 1, 2020
  • Data Science with R: Data Analysis and Visualization (Weekend Course)

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    Data Science, R, Data Visualization, Data Analytics , Data Structures
    In PersonPart Time7 Hours/week6 Weeks
    Start Date January 18, 2020
    Cost$2,190
    Class size15
    LocationNew York City, Online
    This course is designed to provide a comprehensive introduction to R. Students will practice programming and analyzing data with R. Students will learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models to data. In addition to a theoretical framework in which to understand the process of data analysis, this course focuses on the practical tools needed in data analysis. This course also covers the creation of dynamic reports with the knitr package in R as well as the creation of dynamic dashboards with R Shiny. By the end of the course, students will have mastered the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting the code.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelBasic knowledge about computer components Basic knowledge about programming
    Prep WorkNone
    Placement TestNo
    InterviewNo
    More Start Dates
    January 18, 2020 - New York City Apply by January 15, 2020
    April 18, 2020 - New York City Apply 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 January 18, 2020
    Cost$2,990
    Class size40
    LocationNew York City, Online
    This 35-hour Machine Learning with R course introduces both the theoretical foundation of machine learning algorithms as well as their practical applications in R. It will introduce you to data mining, performance measures and dimension reduction, regression models, both linear and generalized, KNN and Naïve Bayes models, tree models, and SVMs as well as the Association Rule for analysis. After successfully completing this course, you will be able to break down the mathematics behind major machine learning algorithms, explain the principles of machine learning algorithms, and implement these methods to solve real-world problems. Unit 1: Foundations of Statistics and Simple Linear Regression Unit 2: Multiple Linear Regression and Generalized Linear Model Unit 3: kNN and Naive Bayes, the Curse of Dimensionality Unit 4: Tree Models and SVMs Unit 5: Cluster Analysis and Neural Networks Final Project After 35 hours of structured lectures, students are encouraged to work on an exploratory data analysis project based on their own interests. A project presentation demo will be arranged.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelKnowledge of Python programming Able to munge, analyze, and visualize data in Python
    Prep WorkKnowledge of R programming Able to munge, analyze, and visualize data in R
    Placement TestNo
    InterviewNo
    More Start Dates
    January 18, 2020 - New York City Apply by January 15, 2020
    April 18, 2020 - New York City Apply by April 15, 2020
  • Data Science with Tableau (Online)

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

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

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

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    Start Date January 14, 2020
    Cost$1,590
    Class size40
    LocationNew York City
    This is a class for computer-literate people with no programming background who wish to learn basic Python programming. The course is aimed at those who want to learn “data wrangling” – manipulating downloaded files to make them amenable to analysis. We concentrate on language basics such as list and string manipulation, control structures, simple data analysis packages, and introduce modules for downloading data from the web. This Introductory Python class runs over four weeks, with five hours of class per week (split into 2 ½ hour evening classes). Classes will be given in a lab setting, with student exercises mixed with lectures. Students should bring a laptop to class. There will be a modest amount of homework after each class.
    Financing
    Deposit$1590
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    Getting in
    Minimum Skill LevelThis Introductory Python class is designed for computer-literate people with no programming background who wish to learn basic Python programming.
    Prep WorkIn the class, we will use Python 3. If you are following this video to set up Python environment, please make sure you download the Python 3.X version starting from 1 min 23 s in the video. Link: https://vimeo.com/160172414
    Placement TestNo
    InterviewNo
    More Start Dates
    January 14, 2020 - New York City Apply by January 10, 2020
    March 9, 2020 - New York City Apply by March 5, 2020
  • Remote Immersive Data Science Bootcamp (Online)

    Apply
    Start Date Rolling Start Date
    Cost$17,600
    Class size25
    LocationOnline
    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
    Deposit5000
    Financing
    • Climb Credit Loan $400* pm for 60 months

    • Full Tuition Total $17,600

    • Skills Fund 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
  • Remote Self-paced Data Science Bootcamp (Online)

    Apply
    Start Date Rolling Start Date
    Cost$17,600
    Class size25
    LocationOnline
    This is an online part-time self-paced program. Students have 4 - 10 months to complete this program. The curriculum is the same as our on-campus program, with full-financing options, career support and with a one on one support from our mentors. This program is designed for students that work full-time and are not able to quit their jobs. Our curriculum is drawn from data science engagement with corporate consulting and training, hiring partners and active industry participation. Our remote bootcamp ensures that students achieve a very high level of proficiency. Students are expected to dedicate themselves fully to this program and fulfill all the requirements, which include completing lecture videos, daily homework, and four projects. The Remote Bootcamp is built as a collaborative environment utilizing online chat and meeting systems. Students also have the opportunity to collaborate on homework, projects, job applications, interview preparation, paired programming, and even further through our extended alumni community. We work closely with hiring partners and recruiting firms to create a pipeline of interests for students. Each student receives one-on-one support with job searching and access to all kinds of job assistance resources, including coding reviews, interview prep, resume workshop, and access to our exclusive hiring partner network.
    Financing
    Deposit17600
    Financing
    • Climb Credit Loan $400* pm for 60 months

    • Full Tuition Total $17,600

    • Skills Fund Student Loan
    $397.88 pm for 60 months
    Tuition PlansWe have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months.
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    ScholarshipLimited number of scholarships available to qualified candidates.
    Getting in
    Minimum Skill LevelIdeal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming.
    Prep Workhttp://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/
    Placement TestNo
    InterviewYes

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  • Brian Saindon • Data Scientist • Graduate
    Overall Experience:
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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.

  • Tingyan Zheng • Graduate
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    This course convers major R machine learning topics; course is intense and you will learn a lot if you keep up with the pace. Instructor Shu Yan is great at explaining complicated statistical concepts/formulas and translate them into R coding techniques. Couse materials, in-class practices and home work assignment are really helpful in terms of learning and future references.

    I would recommend this course to anyone who is interested in data science/maching learning but doesn't know much about this field. It will be a good start for you if you plan to work in this field. It certainly helped me understand a lot about data scicence and improved my R coding skills.

    What I learned from this course is worth the money I paid and the effort I put in.

  • Bin Lin • Data Science Engineer • Graduate
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    I was coming from a Computer Sicience background. And I decided to make a career switch to Data Science. One of my data scientist friends recommended me to take the NYC Data Science Academy's 12 weeks Data Science Bootcamp. It turns out to be money worthy. 

    The bootcamp covers all the skills that I need to know to be a successful Data Scientist. It provides training on: programming skills (in both R and Python), basic Linux/Unix commands, basic database SQL programming, exploratory data analysis & data visualizationn (in both R and Python), Machine Learning in both R and Python, and basic Hadoop and Spark skills. Some people might wonder why both R and Python were taught. From my experience, R is really helpful and handy when doing the EDA and visualiztion at the beginning. Python is more useful when building production pipeline models. Also Jupyter Notebook (orignially called iPython Notebook) makes sharing the code and charts easier. So I feel it was right that they taught both R and Python.

    The program was very intensive. There was so much information thrown into my brain every day so thus I had to study and reivew the course material every night late in order to digest them. We were assigned homework every other day and projects every 2 weeks. There were about 5-6 projects through the course of the bootcamp. Each project had a different focus. While the earlier projects focused on Exploratory Data  Analysis, the later ones were more Machine Learning focused. I found myself was always rushing to wrap up the projects because I always had diffcult time to come up with an idea or started it late. Lesson learned!

    During the bootcamp, because I was from computer science backgroud, I was quite relaxed on the programming parts. But I definitely struggled a little bit on the Machine Learning part since it invovled advanced Math and statistics. So I had to go back and review some of the Math material and took some online training on statistics. Therefor it would be great advantage for people with statistics backgroud. If one without statistics background is trying to take the bootcamp, I would suggest that you study some statistics material from online before the bootcamp so that you can really understand the theory behind. 

    I also want to give credits to the awesome instructors. Special thanks to Sam, Chris, and Luke who did a great job on teaching the class and answered all my questions. There were also two TAs who has provided big help on homeworks and projects.

    Quick notes on job assitance, NYC Data Science Academy has connections with hiring partners. Therefore we got many job opportunities directly from the hring partners, such as Goldman Sachs, Chase, NBL, Booz Allen Hamilton. There was a time that the former job placement manager was slacked. But it was quickly fixed and the job placement manager was replaced and things were back on track again. We were also provided training on preparing interviews and sharping up my resume. Even though I got a job from an opportunity I found from LinkedIn, but the job assistance from the Academy was definitely helpful.  

    To sum it up, I have learned a lot from the bootcamp and I also spent a lot time to digest them after I finished the bootcamp.

    The only two things I suggest are: 
    1. Because EDA and Data Visualization are so import, it would be great to have a example on those that we could have walked through or done together. Or for at least one of the EDA and Data Visualization projects, we work on the same topic and review it together. 
    2. More hands-on Spark excise. I would suggest using of Databrick community version or student excise.
  • Engaging
    - 9/1/2016
    Melita
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    This class touched upon the basic to more sophisticated application of R programming through use of available and popular packages.  Amy has been a very caring and responsive instructor.  She is always willing to help and offer insights in selecting appropriate approach to gain efficiency.    The materials covered  were vast and familiarity requires a lot of practice.  The classroom work and homework gave the students the push to get more involved and provide the hands-on experience. This class was engaging. 

  • Tatiana Sorokina • Sr. Director, Data Science @ Medivo
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    Hiring a Data Scientist in NYC is a full-time job on its own. Your inbox may be exploding with hundreds of applications, yet it is extremely challenging to find the right candidates. While I was in the middle of sorting through resumes I was invited to a Data Science Academy happy hour by Vivian. I heard of Data Science Academy but never thought to look for hires there.

    As soon as I arrived I met Vivian and her team who already knew what type of Data Scientist I was looking for and introduced me to a few students. I was so impressed by them that I decided to invite them for an interview and within one week hired one of the graduates. He has been working with us for a few months and has already made a difference. His amazing technical skills combined with a very strong business acumen helped him take a lead on critical corporate projects and execute them with excellence.

    I strongly recommend all employers looking for Data Scientists to contact Data Science Academy as it truly helps prepare the next generation of data scientists for real world jobs.

  • Robert Castellano • Data Scientist • Graduate
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    The NYC Data Science Academy bootcamp is everything I hoped it would be. I entered as a recent Mathematics PhD unsure of my job prospects and left well prepared for the data science job market. I was offered a job within weeks of graduating and now have a great job as a data scientist.

    The bootcamp is an intense experience that will reward you if you put in the appropriate effort. The lectures are fantastic and the instructors are incredibly helpful with your projects. They will offer you as much help and guidance as you want (they were, more often than not, there before me and were still there when I left). 

    Job placement assistance was also crucial to my success. I met my current employer through a bootcamp and felt more then prepared during my interviews. You really feel that you are given individual attention and they will do everything in their power to help you find a job.

    Some tips to prospective students:

    • Become familiar with the basics of R and Python (especially Python as this is introduced later in the bootcamp when you are becoming busy).  I didn't enter the bootcamp as a programming expert but I found having some knowledge was a large advantage. A few months of learning the basic syntax and doing exercises in your spare time should be sufficient (that is approximately what I did).
    • Enter if you are willing to commit 3+ months to your career (you will be studying and preparing for interviews after you finish the bootcamp).

    NYC Data Science Academy was a fantastic introduction to the world of data science. I still stop by the offices to say hi to instructors and students and discuss life. I would make the decision to join the bootcamp again 10/10 times. 

  • Jiaqi L • Graduate
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    I really enjoyed the R course with instructor Amy Ma. The content is very practical. It can be directly applied to solve real-world data analysis problem.  We had many in-class coding exercises, which helped us understand the R syntax. 

    Also, Amy tried her best to provide a lot of useful resources. We could tell that she is very passionate about what she is doing, and she is patient with students. We could reach her after class through email, even the course was finished. I highly recommend this course to anyone who is interested in data analysis and wants to learn R from the beginning. 

     

  • Iris Huang • Student
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    I really enjoy taking the R course with Amy Ma. She's patient and thorough. Her analogies made it easier  for me to understand the R syntax. I really like the in-class coding exercise and it was good to practice what I have learned. Amy's class is very interactive. She doesn't just talk off the slides. She always codes with us and shows us different ways of doing the same thing or breaking down the code part by part. She would compare and contrast the nuances between different commands, which was quite helpful. 

  • Ho Fai Wong • Graduate
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    The NYC Data Science Academy's 12-week bootcamp is an intense, well-thought out and comprehensive program that accelerates one's immersion into the world of data science. Having worked in IT infrastructure consulting for 8 years at one of the Big Four, I wanted to shift career orientation and focus more on data science, elements of which had begun to interest me over the course of several client projects.

     

    Comments on the program:

    • Strong teaching staff who is clearly passionate about teaching data science as evidenced by the late evenings and weekend support
    • Focus on concepts and skills that are actually relevant to the marketplace
    • Broad and dense curriculum (R, Python, machine learning, Hadoop, Spark, MongoDB, etc) to maximize learning in a limited timeframe
    • Flexibility and nimbleness of the program to adapt to feedback from alumni, employers and the market to maintain the relevancy of every topic taught
    • Good mix of lectures, homework and projects
    • Helpful job prep activities such as interview coding simulations (and others that I won't spoil)
    • Eclectic mix of students (though this may vary by cohort) that allowed us to learn from each other's diverse backgrounds and areas of expertise, and develop deep personal friendships and professional relationships
    • Opportunity, if selected, to present projects at Data Science Meetups which offers networking opportunities as well as practice of presentation skills

     

    Suggestions for improvement:

    • As data science is a dynamic and evolving field, keep up with the latest advances such as improvements in R packages and update the curriculum accordingly
    • Give harsher constructive feedback to students when required
    • More transparency on student evaluations overall and for Meetup project selections as well

     

    Recommendations for aspiring students:

    • Be committed: the bootcamp is demanding but that is by design. It's an investment; you get out what you put in. Don't show up late, don't ignore the homework. If you do, it's your loss
    • Don't fall behind: there's a lot of work and learning a very rapid pace, not to mention homework almost daily
    • Be proactive: reach out to the TAs or the instructors for feedback (not just help), read up on machine learning outside of the bootcamp, talk to your classmates on how to collaborate
    • Manage your time: you will have to juggle many responsibilities and will most likely feel overwhelmed in general. That is also a skill you will need in the professional world
    • Learn to be autonomous: don't run to the TAs or the teachers for help as your first recourse. Google, StackOverflow and other resources most likely already ahve the answer you are looking for. Only when you have made a decent attempt at figuring out the problem should you ask for help. After the bootcamp, that safety net will no longer be there so it's best to practice early

     

    Overall, very positive experience. I can't speak to the job placement assistance as I returned to my original firm, but regardless, I'll maintain the great relationships built with the Academy.

  • Great Investment!
    - 8/19/2016
    Kelly • Associate Director, Marketing Science • Graduate
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    NYC Data Science Academy (NYCDSA) provided the platform to pursue my dream career.  The curriculum is well thought out, with detailed notes, hands-on projects, and great hiring partners. NYCDSA gave me the tools to be come a data scientist, and the exposure to land the job.  Truly one of the best investments I have ever made!

  • Denis Nguyen • Graduate
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    NYC Data Science Academy's 12-week bootcamp was a life-changing experience. It was an intensive 3 months but definitely helped me transition from healthcare to data science.

    Comparing against other bootcamps, I decided to go with NYCDSA for its thoughtfully planned schedule. From the large volume of content to the scheduling of each day, it had what I needed to succeed. Each day consisted of lectures with really useful slides and concluded with time for homework and projects in the afternoons. The allocated time in the afternoons gave us time to digest what we learned and the homework assignments reinforced the new knowledge.

    Coming from a background in biomedical engineering and biological sciences, I was used to being told everything I had to know. The bootcamp gives a lot of information with its detailed lectures but also challenges students to find their own answers. For example, a homework assignment had a problem mentioning a function that was not mentioned in lecture. We had to research it and learn how to use the function before we could do the problem. This taught me how to be resourceful and find answers on my own instead of relying on someone to tell me everything. Because data science is a growing field, you cannot expect to learn everything in a short period of time but should know how to find solutions on your own.

    Being challenged to learn may sound intimidating but it really isn't when you're surrounded by supportive peers and staff. The staff are extremely hardworking and friendly. They stay late, sometimes even until 11pm and they love what they do so they won't be grumpy or annoyed at you. They also come in on the weekends and will help with homework assignments and projects if you require it. The TAs are excellent resources who are passionate about data science and motivate you to always do better.

    Advice: Try to familiarize yourself with the suggested R and Python readings before you begin the bootcamp so that you can spend less time trying to understand concepts and more time on the data science parts.

    Even after graduating from the bootcamp, I still feel like family around them. The instructors and staff do not forget you and continue to help with your job search. Vivian actively connects you with resources and posts jobs you may be a fit for. She also holds coding review sessions so that we are better prepared for interviews.

    Job Prospects: Besides the countless data scientist and analyst job posts found online, NYCDSA hosts a hiring party at the end of the bootcamp that connects recruiters from multiple companies with students. It gives you a big opportunity to speak with recruiters and build connections. I interviewed with one of the hiring managers from the event and got an excellent data scientist job approximately 1 month after graduation. You have other opportunities to stand out from crowd when Vivian reaches out to her contacts and sends in your resume so you're not just another applicant in the pool. There are tons of jobs and the support from NYCDSA is outstanding.

    I have no negative memories of the bootcamp besides the late nights spent on projects but you get as much as you put into the program. Overall, the bootcamp does a good job preparing you for a career in data science as long as you work hard for it. Your peers will be your friends and consultants for your data science problems. I would join another cohort at NYCDSA if I could!

  • Yuka • Data Analyst • Graduate
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    I took the data analysis and visualization with R class in June. The lecture and presentation was very thoughtful. The instructor was very helpful. After taking the course, I can actually pick up some skillsets like doing some descriptive analysis and creating some plots. But more practice is needed outside the classroom if you really want to get something from the course.

    Overall, I would recommend the course to people who have some coding experience and would like to learn more on the topic.

     

  • Adam Cone • Graduate
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    I finished the bootcamp yesterday. I have a BA with honors in Math, an MA in Applied Math, and an MS in Civil Engineering. I have 8 years of work experience in both the private and public sectors. I committed to this program to help me transition to becoming a data scientist. I had minimal professional programming or statistics experience when I applied.

    • I bought a new computer and studied statistics, R, and Python for over a month before my first day in the bootcamp.
    • I worked more intensely and consistently at the bootcamp than I've worked on anything over a 3-month period, either in school or in a job.
    • The staff are maybe the bootcamp's finest feature. The instructors are technically proficient, patient, and articulate. Somehow, I didn't feel intimidated, more inspired. In three months, every time I requested support, I was supported.
    • The office has a simple aesthetic and is well-equipped and well-maintained. It is often crowded, but overall a space where I felt focused and could work.
    • I gave the curriculum 4/5 stars. I found the material fascinating. There were many times when I simply didn't keep up. There is a lot of material. Read that sentence again. The curriculum moves so quickly that it often felt like a day-tour of Europe.
    • I found my classmates highly-educated, focused, and committed. I forged some excellent working and social relationships.

    Overall, I recommend this bootcamp under the following conditions:

    1. You will commit yourself to this program for 3 months. For these 3 months, this is what you will do during the day and in the evening, weekdays and weekends.
    2. With whatever time you have before the bootcamp, you will study statistics, R, and Python.
    3. You accept early on that sometimes it will be acutely stressful and overwhelming.

    Having completed the bootcamp, I see the value in Vivian's approach: by working at capacity among such skilled staff and focused students, my skills and knowledge developed quickly. Overall, this bootcamp worked well for me and I'm glad I did it.

  • Wendy
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    This is an awesome program you will not regret attending! 

    I was in the Jan-April 2016 cohort. The course covers everything you need to know to apply for data scientist jobs. We started from the fundamental of stats in R, and moved into machine learning in both R and Python. In the last two weeks we also got a fair exposure to big data tools like Hadoop and Spark. The instructors we have are AMAZING!!! They are super knowledgeable and also very passionate about data science. TAs are the most hard working group of people I know! They really try their best to help you. Students at the bootcamp are impressive as well. Most of them either have a phd degree or have significant/successful work experiences prior to joining the bootcamp. We did five projects during the bootcamp which you can totally show off during your job interviewsss! And you will have a least a few job interviews guaranteed during/after the bootcamp. They really tried their hardest to help you preparing and securing job interviews. I personally had at least 5 interviews while I was still in the bootcamp, and was hired only two weeks after the bootcamp ended.

    The program wasn’t easy, you will have a ton of homework and projects to do, but they are always there to support and help you. I would recommend this 12 weeks bootcamp to anyone who wants to be a data scientist or simply interested in data science. 

  • David Steinmetz
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    This course is ideal if you already have programming experience. I had experience with Matlab and R, so this provided the answer to the "how do I do that in Python" question. If you have never programmed before, go through Learn Python the Hard Way very thoroughly before enrolling. You will get the most out of this course if you have already learned basic programming concepts and can therefore focus on the intent of the course: data analysis and visualization.

    The class teaches very practical aspects of Python and data manipulation and visualization. Often we know what question we want to ask and maybe even already have the data, but need to get it into a form to analyze and present visually. This course was good at preparing you for that. Little time was spent on cleaning data, most was spent on learning Python and manipulating data and how to visualize it. 

    The instructor, Liz, was easygoing and personable, which made it very easy to ask questions. She was also knowledgeable about the topic and could give insights into what it was like to actually use these tools on a daily basis. I enjoyed having her as an instructor.

    I'm only giving it four stars, which to me means very good, because five stars to me means truly exceptional. In order for this course to be truly exceptional, it would need to ensure all students were up to a certain standard in Python, allowing the class to go into the data analysis and visualization much faster. Given that the students in the class had extremely different backgrounds and levels of programming experience, I was very impressed.

    In conclusion, if you are using other tools like Excel and have some programming experience, I recommend this course as a good way to move your work into Python to take advantage of its speed, flexibility and packages. I was able to create visualizations of crime and weather data I got from the NYC Open Data site in only a couple hours after taking this course. Well worth it!

  • Anonymous
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    I took both the intro to data analytics and the machine learning course, both using R. Both the instructors Luke and Shu went out of there to answer emails and help me get a better understanding of the field. I'm new to data science and computer science and after the course, I felt very comfortable using R and discussing machine learning and data science with other individuals. 

  • Anonymous • Student
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    Well, i could have learned much more things by finding a good book and reading it or taking online course which would've been much more chaper as well. First of all if you re beginner at python , this course deffinetly is not for you . You get very brief information in the lectures and you have to figure out  rest by yourself. I took this course just because i didnt have time to learn by myself and i thought they will actually teach me , not pushing me figure out by myself but obviously i was wrong, so disapointed.

    It was very bad idea to pay more than $1500 and take this course.It doesnt worth at all !

  • Christopher Redino • Graduate
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    I chose NYCDSA over similiar bootcamps because they seemed to have largest breadth of content and also seemed to be the most challenging, and I believe they delievered in both those aspects. You will learn a lot, and you will be challenged, even if you come into the bootcamp with some experience in data science.

    The lectures themselves are very enganging, and the intstructors are very knowledgable. The course content (slides, lecture code, homework, etc) are not only excellent for learning the matieral, but I think they will also be valuable references going forward.

    I feel the bootcamp has prepared me well for my job search. I had several interviews set up before the bootcamp had ended, and my first offer a few weeks after that. I'm confident that if I want to interview with more companies that NYCDSA can help to make this happen.  Employers are interested in the projects I've done with the bootcamp, so I can get their attention, and the course material has trained me in the areas they are likely to test me on during interviews.

  • Life-Changing
    - 4/3/2016
    Sricharan Maddineni • Fellow • Graduate
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    My time at the Nyc Data Science Academy was some of the best three months I've ever spent. This is an intense bootcamp but it the instructors are absolutely amazing and push you to excel. Christopher (the main statistics and R instructor) is one of the best people I've ever met and you are guaranteed to be inspired by him. The TA's are some of the most hard-working people you will ever meet and are always available to help (most days until 11pm - not sure if they even go home!). 

    All my peers in the cohort were positively affected by their experience and you should attend without hesitation if you're accepted! Vivian, the academy founder, is personally vested in helping her students find jobs and she is extremely well connected and caring. We are fortunate to be on the cusp of this new and exciting field and have the opportunity to attend such a bootcamp. 

  • Joseph Lee • Data Scientist • Graduate
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    The program offers a very good course for building foundational data science skills.  It is very evident how motivated the faculty and instructors are in helping their students achieve their initial career goals in data science. The curriculum covers topics and subject matter that is considered mandatory for any entry-mid level data scientist and the program does a good job preparing students for data science oriented interviews.  Data Science is a large field that cannot fully be appreciated in 12 weeks.  In spite of this the NYCDSA does a great job designing both the breadth and depth of their curriculum, which they are always improving and expanding.  
    Overall, I had a very successful experience and had multiple interviews both during and after the program, which eventually led me to my present dream data scientist job.  

    Overall Pros
    - Talented and very bright staff and instructors.
    - Very good network with NYC companies
    - Growing company
    - Available staff at all (or most) times
    - NYC Location 
    - Homework is reasonable, challenging, and yet fun
    - Curriculum covers many basics that are important for data science interviews. 

    Overall Cons
    - Growing pains, which should be expected for any growing startup in a hectic and driven environment such as NYC.  
    - Hiring network is fairly limited to the east coast (from when I attended), however last time I checked they are making successful efforts in branching out to other regions.

    My Advice:
    The program is a goldmine of learning potential for any student who is willing to put in the hours both inside and outside of the classroom.  In order to yield the most benefits from the program, students should be flexible and nimble.  Data science is a constantly growing and changing field, thus the curriculum must also constantly change.  Furthermore, students should constantly engage with the instructors and TA's.  The curriculum goes at a face pace and it is their (the faculty) mission to ensure that all students maximize their learning.  From my personal experience, 30% of what I learned came from the lectures while the other 70% of what I learned came through working on projects and problems after class with my peers and TA's.  

    Conclusion:
    I would highly recommend this program to any person who are willing to work hard and put in the hours to learn and reinforce the material.  

Thanks!