12-Week Immersive
Data Science Bootcamp

Learn R, Python, Hadoop and Spark in just 12 weeks with job placement support

NYC Campus
Special Summer Bootcamp
Jun 3, 2019 – Aug 23, 2019
NYC Campus
Summer Bootcamp
Jul 1, 2019 – Sep 20, 2019
NYC Campus
Fall Bootcamp
Sep 23, 2019 – Dec 13, 2019

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Data Science Bootcamp Overview


In this program students will learn beginner and intermediate levels of Data Science with R, Python, Spark and Hadoop as well as widely used industry tools such as Selenium, Caret, Tensorflow, MongoDB, AWS, and more. Students are expected to complete four projects that demonstrate industry experience as well as pass coding challenge exams and a final consisting of machine learning theory. 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 awards certification of graduation certified by the New York State Board of Education.


500 8th Avenue, Suite 905, New York, NY 10018 Google Map


Ideal applicants should have a Masters or PhD degree in Science, Technology, Engineering or Math or equivalent experience in quantitative science or programming. Applicants with a bachelor's degree will also be considered.
Read on how to get prepared for the bootcamp


Monday through Friday, from 9:30am to 6:00pm



Program Highlights

Best Reviewed Bootcamp

NYC Data Science Academy is the top-rated bootcamp based on SwitchUp

A Complete Curriculum

The only Data Science bootcamp that teaches both Python and R

Cutting Edge

Curriculum drawn from engagement with corporate training and industry participation


Create a personal portfolio with 4 projects to showcase your skills and knowledge

Career services

Enjoy 1-on-1 career support and access to all amazing job assistance resources

Engaging community

Become part of our data-passionate community with 5000+ members and 1000+ alumni

Student Reviews

Course Report
Best Bootcamp Award
by SwitchUp


In order to sufficiently prepare for the rigors of the bootcamp itself, students should have practice in both R and Python as well as basic concepts in linear algebra, calculus, and statistics.

Prerequisite online coursework includes a total of forty hours of lecture videos and over two hundred coding challenge questions. External readings in statistics, linear algebra and calculus are suggested with staff recommendations. The expected total time for the prework should take around one hundred hours on average. A diagnostic exam is given the week before the orientation day. Students are also encouraged to take our in-person short courses based in NYC.

Want to start the prep course now?

Intro to Python
Designed for people who are new to programming
Python for Data Analysis
Level up your Python skills
R for Data Analysis
Learn R to process, analyze and visualize data

* The cost of short courses are fully deductible from the tuition of the bootcamp as we encourage students to take short courses both as a preview of our courses but also to be well prepared for the bootcamp itself.


Our bootcamp is proud to be the only bootcamp to offer both R and Python. Our curriculum is focused on practical real data science experience with heavy emphasis on machine learning algorithms, coding expertise and database query. Topics are taught by specialists in the field rather than a general instructor for an entire semester. The bootcamp will encompass over four hundred hours of curriculum content including three hours of daily lectures in the morning as well as afternoon jump start sessions of widely used industry tools such as Selenium, Caret, Tensorflow, MongoDB, AWS, etc.

Download Curriculum
An expected one hundred hours of coursework prior to entering the bootcamp as well as passing an entrance exam
Unit 1
Data Science Toolkit
Learn to work from the command line - a must have skill for all data scientists. Work with basic Linux commands, text editing, and Git for version control. MySQL is taught with extensive practice on data manipulation.
Unit 2
Data Analytics & Visualization with R
Dive deep into R programming language from basic syntax to advanced packages and data visualization (e.g. tidyr, dplyr, string manipulation, ggplot2, R Shiny). Create a data-centric application with interactive visualizations.
Unit 3
Data Analytics & Visualization with Python
Basic Python programming, followed by versatile packages such as Numpy, Pandas, Matplotlib, Beautifulsoup, Scrapy and Selenium. Exposure to NoSQL and MongoDB. Complete a Python web scraping project.
Unit 4
Machine Learning with R
Descriptive statistics, hypothesis testing, missingness, imputation & KNN, simple linear regression, multiple linear regression, generalized linear models, principal components analysis, ridge/Lasso regression, trees, random forests, bagging, boosting, support vector machines, unsupervised learning. Complete a Kaggle competition.
Unit 5
Machine Learning with Python
Deepen machine learning skills with scikit learn. Focus on data cleaning, feature extraction, modeling and model selection using regression, SVM, PCA, tree models, clustering and more. Acquire skills in Natural Language processing, Time Series Analysis, and Deep Learning.
Unit 6
Data Engineering/Big Data Track
Learn database management tools such as AWS, NoSQL, MongoDB. Introduction to MapReduce, Hadoop, Hive, Spark, and Spark MLlib.
Deep Learning Track
Build Deep Learning models in TensorFlow. Acquire knowledge and skills in Machine Visions, Natural Language processing, Time Series Analysis, and Reinforcement Learning.
Unit 7
Capstone Project & Job Placement Support
Complete a capstone project. Resume review, tips of interview skills, and opportunities to interview with potential employers.
View Daily Schedule


Aiko Liu
Aiko Liu
Data Scientist
David Romoff
David Romoff
Data Scientist
Luke Lin
Luke Lin
Data Scientist
Shu Yan
Shu Yan
Data Scientist
Zeyu Zhang
Zeyu Zhang
Data Scientist

Guest Lecture

Henri Dwyer
Data Scientist at Dataiku
Automated Machine Learning
Andy Eschbacher
Map Scientist at CARTO
Data Science and Maps
Dan Shiebler
Data Scientist at TrueMotion
Smartphone Sensor Data
Susan Sun
Freelance Data Scientist
The Data Scientist at Work
Bernard Ong
AVP at Lincoln Financial Group
Data Science Career Trajectory

Career Services

1. Resume and LinkedIn profile review, interview skills & elevator pitch workshops

2. Mock technical interview and coding tasks

3. One-on-One post-interview review and feedback outreach

4. In-class Industry Experts speaker series

5. Hiring partner event series, including student presentations and a hiring partner networking gala party

6. Present projects and networking with data science peers through our meetup events

Companies that hired our students

Students Get Hired

Domingos Lopes
Ph.D., Mathematics, New York University
Software Engineer
Hired at
Claire Keser
MBA Entrepreneurship, University of Victoria, Canada
Senior Analyst
Hired at
Chao Shi
Ph.D., Computational Geodynamics, Cornell University
Senior Data Scientist
Hired at
David Steinmetz
Ph.D., Materials Science, RWTH Aachen University
Machine Learning Engineer
Hired at
Lydia Kan
M.S. Marketing Analytics, New York University
Data Scientist
Hired at
Fangzhou Cheng
Master of Science, Management and Sys., NYU
Data Scientist
Hired at

Tuition & Finance

Tuition Total
full tuition payment
Make full payment using cash, check or wire-transfer
Climb Credit Loan
$375 - $439*
per month for 60 months
More options to finance our bundle class
Learn More
* range varies based on approval interest rate
Tuition Total
full tuition payment
Make full payment using cash, check or wire-transfer
Skills Fund Student Loan
per month for 60 months
Borrow up to an additional $7,500 for cost of living
Learn More

Frequently Asked Questions

Read our Full FAQ here

The 12-week bootcamp teaches the full set of tools necessary for a data scientist to hit the ground running in his/her first job. Unlike other programs, that focus on one language, or one set of tools, NYC Data Science Academy teaches all the technical skills that employers are looking for, including R, Python, Hadoop and Spark.

We accept candidates on a rolling basis. You can apply at any time for any cohort.

The application process consists of two steps: an online written application and a virtual or in-person interview.

The written application takes about one and half hours. The application is designed to help us get a sense of your educational and working experience. The application ends with short coding challenges. You can use any programming languages you feel comfortable to solve the challenges.

After reading your application, we will send you an invitation via email to schedule a virtual interview. The interview helps us understand why you want to pursue a career in data science and how NYCDSA is the best fit for your goals. At times we'll have a second in-person interview to help us to get to know you better and see if you're a good technical and cultural fit for the program.

We deliver an admission decision to you within one week and talk about next steps.

We accept some talented individuals who don't have any coding experience. We can teach you, too! We encourage people with zero coding background to apply at least six weeks ahead of the bootcamp start date, to allow enough time to finish a solid pre-work plan.

NYC Data Science Academy will accept applications from individuals with master’s degrees or Ph.D.s in Science, Technology, Engineering or Mathematics, or equivalent experience. Some Bachelor's or non-STEM degrees will also be considered, though we strongly urge you to take statistics and/or programming pre-work before the bootcamp starts. We encourage people with zero coding background to apply at least six weeks ahead of the bootcamp start date, to allow enough time to finish a solid pre-work plan.

Yes. NYC Data Science Academy has partnered with diverse companies from small startups to large corporations to help place our students in positions just right for them. But a job is not guaranteed. Our job placement assistance includes:

  • Resume review, LinkedIn profile improvement, interview skills workshops
  • In-class Industry Experts speaker series
  • Hiring partner event series, including student presentations and a hiring partner networking gala party
  • Mock technical interview and coding tasks
  • Presentation of projects and networking with data science peers through our meetup events
  • Real-world consulting project opportunities offered by hiring companies
  • Company site visits
  • Access to post-graduation resources

Our 12-week bootcamp is a full-time program. Students must be able to commit to 9:30-6:30 during the week and should expect to spend some time in the evenings and over weekends to complete project work. As with any instruction, students will get as much out of the program as they put into it.

Yes, we provide the bootcamp remotely through a combination of video recordings of the actual bootcamp class lectures, 1-on-1 TA support, and career support. We give our remote students usually 4 to 6 months of support to complete the program. Feel free to reach out to [email protected] to learn more about this option.

We work with every student individually to get their skills up to a level where they can start the bootcamp. We offer a variety of free part-time data science courses and customize pre-work packages for accepted students. If students have limited statistical and programming background, there are some books and online courses that we recommend. Also for students who are already in the New York City area, they can take part-time courses for free.

The tuition for Data Science Bootcamp is $17,600. A deposit of $5,000 is required after acceptance to secure your spot.

We partner with two different financing institutions: Skills Fund and Climb.

Skills Fund offers fixed interest rates on 3- and 5-year loans, regardless of current income, employment, or educational background.  In addition to the cost of the program, they offer a living stipend up to $7,500 with tuition financing.

Climb Credit offers fixed interest rate loans for both immersive and bundled part-time courses. Financing is available for various types of credit, including students with no credit. 95% of applicants will receive an instant decision after completing Climb's quick 5-minute application. International students are welcome to apply with a qualified co-borrower who is either a US citizen or permanent resident. Living expense stipends are also offered to those who qualify.

Information for either can be found on their respective sites.

We do not generally provide scholarships; in rare cases we provide some limited scholarships, often to those with PhDs and show financial need.

Yes! We have had a few international students in our bootcamp. There are a few things you should keep in mind: We do not provide visas, our international students have all come here on traveler visas or valid student visas; We do not guarantee a job for international students, as getting a job and working visa in the U.S. purely depends on potential employer's preference as well as the U.S. immigration policy; You should also be aware that the opportunities to get job and working visa in the U.S. with a non-U.S. degree are very few; As for hiring partnerships, we have a limited number of relationships outside of the U.S. but we are committed to helping you find a job where ever that may be.

Unfortunately we do not provide visas.

NYC Data Science Academy does not provide housing accommodations. There are a lot of affordable short-term housing options that you can search online, like Craigslist.org and AirBNB. We also partner with Literati Group Housing, which provides furnished housing and private rooms in apartments (ranging from $800-1450, average is $1000 without utilities in Astoria, Long Island City, Woodside, Jackson Heights, Harlem, Elmhurst). For more information, visit http://literati.nyc/

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