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Data Analytics Bootcamp

ONLINE INSTRUCTION
Learn data analytics anytime, anywhere with R, Python, SQL, and real-world business cases.
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Immerse yourself in accelerated learning and launch your data analytics career through Interactive Distance Learning! This short bootcamp is designed to equip you with the dominant skills and tools for data analytics.

DISCOVER ONLINE BOOTCAMP

Data Analytics Bootcamp - Online

Interactive Distance Learning: Online Learning, 1-on-1 Mentor, 3 Months, Part Time
Upcoming Cohorts
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Dates
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Upcoming Cohorts
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Dates
Price
Spring-mid Quarter (Online)
March 24
Mar 31, 2025 - Jun 20, 2025
$9,995.00
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Spring-mid Quarter (Online)
March, 24
Mar 31, 2025 -
Jun 20, 2025
$9,995.00
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Summer Quarter (Online)
May 5
May 12, 2025 - Aug 8, 2025
$9,995.00
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Summer Quarter (Online)
May, 5
May 12, 2025 -
Aug 8, 2025
$9,995.00
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Summer-mid Quarter (Online)
June 16
Jun 23, 2025 - Sep 12, 2025
$9,995.00
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Summer-mid Quarter (Online)
June, 16
Jun 23, 2025 -
Sep 12, 2025
$9,995.00
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For consideration on late enrollment, please email [email protected].
Program Highlights
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Become a Data Analyst in 12 Weeks

This immersive program provides training in major data analytics tools and methods and their applications in the business cases and prepare students to seek employment across all industries as data analysis professionals.
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Our Data Science Bootcamps have been rated as "Best Data Science Bootcamp" and "Best Online Bootcamp" by Switch-Up and CourseReport

A Complete Curriculum
Rich Curriculum Content

The only bootcamp that teaches both R and Python for data analytics and visualization.

Project-oriented
Project-oriented

Three application projects with real-world datasets and business considerations; the capstone project often sponsored by companies in New York City.

Cutting Edge
INDUSTRY-INFORMED

Curriculum designed and updated with input and advice from business leaders and experts in data science field.

Career services
ONLINE LEARNING PLATFORM

Responsive learning interface to access course materials anytime, anywhere

Engaging community
DEDICATED MENTORSHIP

Practicing data scientists to provide learning assistance and career advice

What You Will Learn

It is an accelerated training program in which students learn the major tools and methods for performing data analyses and apply them to various projects typically found in real-life business situations. Students learn to employ R and Python for data analytics projects and for presenting research results effectively.Students receive upon graduation a Certificate of Completion from NYC Data Science Academy, which is licensed to operate as a Private Career School by the New York State Education Department through its Bureau of Proprietary School Supervision.

Prework
DABC502 Data Science Toolkit
DABC506 Data Analytics with Python
DABC511 Data Analytics with R
DABC516 Business Cases in Data Science
DABC519 Data Analytics Capstone Project
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Download Curriculum
Prework
Prerequisite online coursework includes a total of forty hours of work and over two hundred exercises. The Prework will prepare students to work with both R and Python as well as revisit basic concepts in linear algebra, calculus, and statistics.
  • Mathematics/Statistics: Refresh your memory in linear algebra and statistics.
  • Calculus: Exercise basic calculus techniques for data.
  • Conda Installation: Kick off your Python journey with a beginner-friendly setting!
  • Python: Designed for people who are new to programming.
  • R: Learn R to process and analyze data.
DABC502 Data Science Toolkit

The Unix environment is widely used in the data science field. Being familiar with the common tools is important in order to carry out further data analysis. This course enables students to communicate with the computers via the command line environment. It also introduces the SQL database, a traditional database that has been widely used in the enterprise setting, as well as GitHub, a file sharing platform generally used by programmers for version control.

DABC506 Data Analytics with Python

This course introduces students to data analysis with the Python programming language. Students learn to work with different data structures in Python and the most popular data analytics and visualization packages such as numpy, scipy, pandas, matplotlib, and seaborn. Ultimately, students will use effective Python code and packages to solve problems; extract, transform, load, and analyze data to gain insights; and communicate the analyses, aided by appropriate visualizations. Students are required to complete a project incorporating these practices, culminating in a presentation of derived insights.

DABC511 Data Analytics with R

This course is designed to provide a comprehensive introduction to the R programming language for data analysis. Students will learn to load, save, and otherwise wrangle data with effective use of functions in R and relevant libraries, including those within the tidyverse collection. Students will practice deriving insights from data using common statistical techniques, including hypothesis testing and basic statistical modeling; effective visualization; and other frequently used techniques within data analysis. Further, students will learn to successfully communicate their insights, including creating reports with tools like knitr. Students are required to complete a project demonstrating the ability to analyze data in R.

DABC516 Business Cases in Data Science

This course was designed to help students place data analytics and data science work in the real-world context of business operations across industries. Students will be presented various business cases in which datasets were explored to gain insights to guide and/or enhance business operations. They will also be required to take given business cases and conceptualize viable project approaches with defined objectives, selected tools and methods, and expected deliverables

DABC519 Data Analytics Capstone Project

The capstone project is designed for students to employ the data analytics concepts, tools, and methods they have learned in the bootcamp to solve a business operational problem with real data sets from a real business entity. Students are presented data sets and potential problems to solve. Students are then required to form project teams, develop a project proposal for instructor review and approval, and execute the project. When the project is completed, each project team is required to present the project findings and share the business insights obtained from the research.

Prework
Prework
DABC502 Data Science Toolkit
DABC506 Data Analytics with Python
DABC511 Data Analytics with R
DABC516 Business Cases in Data Science
DABC519 Data Analytics Capstone Project
Prerequisite online coursework includes a total of forty hours of work and over two hundred exercises. The Prework will prepare students to work with both R and Python as well as revisit basic concepts in linear algebra, calculus, and statistics.
  • Mathematics/Statistics: Refresh your memory in linear algebra and statistics.
  • Calculus: Exercise basic calculus techniques for data.
  • Conda Installation: Kick off your Python journey with a beginner-friendly setting!
  • Python: Designed for people who are new to programming.
  • R: Learn R to process and analyze data.

The Unix environment is widely used in the data science field. Being familiar with the common tools is important in order to carry out further data analysis. This course enables students to communicate with the computers via the command line environment. It also introduces the SQL database, a traditional database that has been widely used in the enterprise setting, as well as GitHub, a file sharing platform generally used by programmers for version control.

This course introduces students to data analysis with the Python programming language. Students learn to work with different data structures in Python and the most popular data analytics and visualization packages such as numpy, scipy, pandas, matplotlib, and seaborn. Ultimately, students will use effective Python code and packages to solve problems; extract, transform, load, and analyze data to gain insights; and communicate the analyses, aided by appropriate visualizations. Students are required to complete a project incorporating these practices, culminating in a presentation of derived insights.

This course is designed to provide a comprehensive introduction to the R programming language for data analysis. Students will learn to load, save, and otherwise wrangle data with effective use of functions in R and relevant libraries, including those within the tidyverse collection. Students will practice deriving insights from data using common statistical techniques, including hypothesis testing and basic statistical modeling; effective visualization; and other frequently used techniques within data analysis. Further, students will learn to successfully communicate their insights, including creating reports with tools like knitr. Students are required to complete a project demonstrating the ability to analyze data in R.

This course was designed to help students place data analytics and data science work in the real-world context of business operations across industries. Students will be presented various business cases in which datasets were explored to gain insights to guide and/or enhance business operations. They will also be required to take given business cases and conceptualize viable project approaches with defined objectives, selected tools and methods, and expected deliverables

The capstone project is designed for students to employ the data analytics concepts, tools, and methods they have learned in the bootcamp to solve a business operational problem with real data sets from a real business entity. Students are presented data sets and potential problems to solve. Students are then required to form project teams, develop a project proposal for instructor review and approval, and execute the project. When the project is completed, each project team is required to present the project findings and share the business insights obtained from the research.

Apply Now
Download Curriculum

Online Classroom Features

Online Learning Platform

Students can access their coursework, get project feedback from instructors and mentors, and interact with fellow students for a truly interactive learning experience. The platform is designed to foster collaboration between students, instructors, and mentors. With our custom-built interface that works on any device, students are able to access their learning materials anytime, anywhere.

Dedicated Meeting Portal for 1-on-1 Support

The online meeting portal allows students to schedule meetings with our dedicated mentors to discuss coursework, projects, and career advice. These mentors are professional data scientists working at global companies including PriceWaterhouseCoopers, Unilever, Vanguard, and National Grid.

Community Interaction

Our online community ensures that students always receive timely support. The bootcamp involves group projects, peer programming, and online communication with their classmates and instructors. We aim to foster a community where every student can learn from each other’s codes and build the skills needed in a collaborative environment.

Outlooks and Outcomes

25%↑
Fast-growing career field
Operations Research Analysts : Occupational Outlook Handbook: : U.S. Bureau of Labor Statistics (bls.gov)
$84,810
Median Annual salary
Operations Research Analysts : Occupational Outlook Handbook: : U.S. Bureau of Labor Statistics (bls.gov)

Networking opportunities with alumni and hiring managers

Networking Opportunities
Apply Now
Schedule a Call
Apply Now
Schedule a Call

Featured Alumni

Tyler Kim
Tyler Kim
Data Scientist
Kiss Products, Inc.
Kiss Products, Inc.
Royce Ho
Royce Ho
Software Engineer
Amazon
Amazon
Domingos Lopes
Domingos Lopes
Software Engineer
Google
Google
Kweku Ulzen
Kweku Ulzen
Seinor Data Scientist
Neilsen
Neilsen
Elsa Vera Amores
Elsa Vera Amores
Data Scientist
JP Morgan Chase
JP Morgan Chase
Sheetal Darekar
Sheetal Darekar
Data Scientist
Verizon
Verizon
Katie Critelli
Katie Critelli
Data Scientist
Deutsche Bank
Deutsche Bank
Mikhail Stukalo
Mikhail Stukalo
Principal Data Scientist, AI Investment Management
Fidelity Investments
Fidelity Investments
Youngmin Paul Cho
Youngmin Paul Cho
Data Scientist
Mars
Mars
Sean Kickham
Sean Kickham
Data Science Manager
PwC
PwC
Tyler Kim
Tyler Kim
Data Scientist
Kiss Products, Inc.
Kiss Products, Inc.
Royce Ho
Royce Ho
Software Engineer
Amazon
Amazon
Domingos Lopes
Domingos Lopes
Software Engineer
Google
Google
Kweku Ulzen
Kweku Ulzen
Seinor Data Scientist
Neilsen
Neilsen
Elsa Vera Amores
Elsa Vera Amores
Data Scientist
JP Morgan Chase
JP Morgan Chase
Sheetal Darekar
Sheetal Darekar
Data Scientist
Verizon
Verizon
Katie Critelli
Katie Critelli
Data Scientist
Deutsche Bank
Deutsche Bank
Mikhail Stukalo
Mikhail Stukalo
Principal Data Scientist, AI Investment Management
Fidelity Investments
Fidelity Investments
Youngmin Paul Cho
Youngmin Paul Cho
Data Scientist
Mars
Mars
Sean Kickham
Sean Kickham
Data Science Manager
PwC
PwC
More alumni

Student Works Showcase

Learning Category-Wise Product Features from Amazon Reviews Learning Category-Wise Product Features from Amazon Reviews
Yan Qi
Capstone: Predicting Sephora Product Success Capstone: Predicting Sephora Product Success
Heather Kleypas
Deep Learning Meets Recommendation Systems Deep Learning Meets Recommendation Systems
Wann-Jiun Ma
Ranking #1 on Kaggle for Predicting Consumer Debt Default Ranking #1 on Kaggle for Predicting Consumer Debt Default
Bernard Ong, Jielei (Emma) Zhu, Nanda Rajarathinam and Miaozhi Yu
More blogs

Get Hired Along the Way

Students are provided extensive job placement assistance ranging from individualized resume support and interview guidance to access to our network of hiring partners and events.
Customized resume support, LinkedIn profile review, elevator pitch workshops and career guidance
Three rounds of personalized resume review, LinkedIn profile review, and career guidance sessions
Mock coding challenges, technical and behavioral interview assistance
1-on-1 post-interview review and feedback sessions with Career Advisors
Life-long access to hiring and networking events with industry professionals
Access to NYC Data Science Academy's alumni network and industry connections
Complimentary access to meetups, workshops and alumni presentations to foster industry relationships
Three rounds of personalized resume review, LinkedIn profile review, and career guidance sessions
Mock coding challenges, technical and behavioral interview assistance
1-on-1 post-interview review and feedback sessions with Career Advisors
Life-long access to hiring and networking events with industry professionals
Access to NYC Data Science Academy's alumni network and industry connections
Complimentary access to meetups, workshops and alumni presentations to foster industry relationships

Choose The Path That's Right For You

Choose The Path That's Right For You
Data Science with Machine Learning Data Science with Machine Learning - Online Data Analytics Bootcamp - Online Bundled Professional Development Courses Professional Development Courses
Commitment Full-time
Remote Live/In-person
Full-time / Part-time
Online
Online Part-time Remote Live/In-person
Duration 12 Weeks
Only on Weekdays
16 Weeks (Full-time)
24 Weeks (Part-time)
12 Weeks
Self-paced
Combination of professional development courses 4 - 6 weeks
Weekdays or Weekends
Career Support / /
Cost $17600 $17600 $9995 Starts at $4500 Starts at $1500
Financing Options /
Choose The Path That's Right For You
Choose The Path That's Right For You

Learn From the Best

Cole Ingraham
Cole Ingraham
Lead AI instructor
Dr. Cole Ingraham has been teaching and working with music, game design, and machine learning for decades. He started learning software engineering and data science by studying music composition and computer animation. As an educator, he taught various instruments, writing music, and programming to students from elementary school through university and beyond. His career as the chief scientist and musician has led him to design Amper Music, the world's leading AI music composition platform from 2015-2020. Later, Cole joined Shutterstock as Director of AI and BlueCore as Director of Data Science. Cole has worked in the industry building generative AI models for Fortune 500 companies and giving consulting services to investment firms and top leaderships in a big array of industries on how to build and invest in a future of Generative AI. He is our Lead AI instructor and in charge of Generative AI and Large Language Model bootcamps and courses.
Vivian Zhang
Chief Technology Officer and School Director
Vivian is the CTO and School Director of NYC Data Science Academy and CTO of SupStat. She is an adjunct professor at Stony Brook University and founded the NYC Open Data Meetup, which is 4000 strong. She has many years of practical experience in data technologies and the analytics, and has expertise in multiple programming languages including R, Python, Hadoop, and Spark. Vivian was ranked in "9 Women Leading The Pack In Data Analytics" by Forbes in August 2016. She enjoys meeting people and enjoys sharing her experiences with young professionals and students.
Zeyu Zhang
Data Scientist
Zeyu obtained his master degree of Electrical Engineering from New York University. With a strong background in object oriented programming and a solid understanding of machine learning algorithms, he helps virtual and physical machines to evolve. Known for doing many difficult things well at the same time, or one simple thing very slowly, Zeyu thrives on problems that require multiple skills. Throw him into a pool of Python, C++, R, SQL, C#, HTML/CSS, JavaScript or find him actually swimming since retiring from his short-lived very-amateur basketball career.
Hasan Aljabbouli
Instructor
Hasan Aljabbouli is an Assistant Professor in Computer Science. He obtained his Master's and Doctorate in Artificial Intelligence from Cardiff University in the United Kingdom and his Bachelor's in Engineering in Information Technology from Homs University. He worked for different universities and has published many scholastic materials in Data Mining and Machine Learning and its applications. In addition to his academic experience, Hasan received two patents and earned relevant experiences participating in various technical projects.
Cole Ingraham Vivian Zhang Zeyu Zhang Hasan Aljabbouli

Connect with Academic Mentors From Industry

Sumanth Reddy
Sumanth Reddy
Sumanth has been a Senior Data Engineer at Draft King for six years and graduated after our boot camp. Sumanth genuinely enjoys complex analysis of dynamic systems. As a former professional poker player, he has made countless analytical decisions under pressure and is intimidated by challenging questions. With undergraduate backgrounds in physics and economics, Sumanth is self-driven to find the answers to stimulating questions about our universe. He is a true team player, always concerned about the people around him, and it is gratifying to make sure everyone is working well together. He recently quit his job to focus on new interests, including mentoring our students and working on a new course at NYC Data Science Academy called “A Manager’s Guide for Data Science Professionals” and graduate school application. He has tons of real-world work experience.
Sining Chen
Principal Data Scientist
Sining is Principal Data Scientist at NYC Data Science Academy. She is also an adjunct professor at Columbia University. She was the director of Data Science at Warner Music Group. She Led and oversaw the development of core algorithms with methodological soundness and business impact: e.g. demand forecasting of cultural products, optimization, marketing research, knowledge graph, NLP tools, deep learning tools; and engineering efforts in bringing machine learning algorithms to production as enterprise-level tools.
Her academic credentials include a Ph.D. from Duke University in Statistics and Decision Sciences and an extensive career in data science, marked by Director of Data Science at Warner Music Group, Technical Staff at Bell Laboratories, Associate Professor at Rutgers University, and Assistant Professor at Johns Hopkins University.
Stella Kim
NYC Data Science Mentor
Stella Kim is a highly analytical and motivated individual interested in using AI to reshape business strategies to make data-driven, customer-centric decisions. She is currently working as a data scientist in the telecommunications industry under their Corporate Finance division. She holds a Master's in Biotechnology, has Ph.D. experience in Cancer Biology and Genomics and has worked as a data scientist in the biopharmaceutical industry. She is proficient in Python, R, and SQL, and is skilled in data analytics, visualization, machine learning, and statistical methodology.
Tristan Dresbach
Instructor
Tristan Dresbach is a data scientist with a BA in economics and a proven track record of using data to drive significant and tangible business results. She has hands-on experience in web-scraping, data visualization, supervised and unsupervised predictive modeling, as well as optimization.
Kyle Gallatin
NYC Data Science Mentor
Kyle Gallatin is currently a software engineer on the machine learning platform team at Etsy. In this role, Kyle is redesigning existing ML systems with a focus on ML model training, real-time model serving, MLOps processes, and model governance. Kyle spends his free time teaching and volunteering within the ML space. He also writes articles for technical publications on ML engineering, MLOps, and infrastructure.
David Corrigan
Instructor
David is assistant director at Sema4, a precision medicine company! Previously Researcher and data scientist with a doctorate degree in Microbiology and Immunology from Columbia University (2018). Enrolled in an immersive, 12-week Data Science Bootcamp (NYC Data Science Academy) after graduation to refine and develop skills in data science.
Denis Nguyen
NYC Data Science Mentor
Denis is a Bootcamp graduate and has been working in the analytics space for over 2 years. With a growing interest in business and management, he obtained his MBS in Analytics from Rutgers University and works on performance improvement through workflow automation. He enjoys sparking creativity in students and helping them think about how to view data to garner insights. In his free time, Denis enjoys exploring nature and learning about various topics on YouTube. The success of students is Denisu2019 priority and he looks forward to working with you.
Jonathan Presley
Instructor
Jonathan is an award-winning public health professional with a certification in data science dedicated to data-based decision-making and efficiency. With nine years of combined experience in scientific research, biotechnology, education, and healthcare, he has developed a variety of skills in research, policy, program development and implementation, monitoring and evaluation, capacity building, and analytics. Jonathan's curiosity and learn-by-doing approach - instilled by his alma mater, Cal Poly, San Luis Obispo - has pushed him to exercise his leadership and innovative spirit domestically and abroad, whether it be studying international health systems in Denmark, volunteering with clinical lab scientists in Bolivia, or developing new health programs in San Luis Obispo.
Sumanth Reddy Sining Chen Stella Kim Tristan Dresbach Kyle Gallatin David Corrigan Denis Nguyen Jonathan Presley

Start your Application

1

Apply for the Program

We suggest applicants to have a master’s degrees or Ph.D.s in Science, Technology, Engineering or Mathematics, or equivalent experience. Bachelor's or non-STEM degrees will also be considered.

2

Talk to an Admission Officer

After reviewing your application, our team will invite you to schedule a video interview. The interview serves as a chance to connect and better understand your background and career goals.

3

Technical Assessment

You will be asked to complete a series of technical questions that will assess your thought process and technical knowledge. You may use any programming language to complete the assessment.

4

Welcome on Board!

Our admissions process is highly competitive, rigorous and may take up to 7-10 business days. We encourage students to apply early as limited seats are offered and filled on first-come-first-serve basis.

Upcoming Cohorts

Spring-mid Quarter
Online
March 31, 2025 - June 20, 2025
Summer Quarter
Online
May 12, 2025 - August 8, 2025
Summer-mid Quarter
Online
June 23, 2025 - September 12, 2025
Spring-mid Session
March 31, 2025 - June 20, 2025
Summer Session
May 12, 2025 - August 8, 2025
Summer-mid Session
June 23, 2025 - September 12, 2025
Apply Now
Schedule a Call

Tuition & Finance

Tuition Total
$9,995
full tuition payment
Payments can be made either by cash, credit card, check, or wire-transfer
Reserve Seat
Third-Party Financing Options
We partner with Ascent Fund and Climb Credit to offer third-party financing options to interested students.
Ascent Fund offers fixed interest rates on 3- and 5-year loans, regardless of current income, employment, or educational background. Climb Credit offers fixed interest rate loans for various types of credit, including students with no credit. International students are eligible to apply with a qualified co-borrower.
Range varies based on approval interest rate.
Range varies based on approval interest rate.
* Available to foreign citizens with a U.S. citizen or resident co-signer
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Upcoming Events

															

Campus Location

Campus Location
500 8th Ave Suite 905, New York, NY 10018
Nearby Subways
1 2 3 34th, Penn Station
A C E 34th, Penn Station
N Q R B D F M 34th, Herald Square
Detailed Directions

Frequently Asked Questions

What do you offer in your 12-week Data Analytics Bootcamp - Online?

The 12-week Data Analytics Bootcamp - Online is an interactive distance learning program. It is an accelerated training program in which students learn the major tools and methods for performing data analyses and apply them to various projects typically found in real-life business situations. Students learn to employ R and Python for data analytics projects and for presenting research results effectively.

What is the application process?

Interested applicants are encouraged to submit their bootcamp application as early as possible as the Academy has a competitive process due to the number of applications that are received and limited seats that are offered.

The application process consists of three steps:

  1. Applicants are required to submit an online application designed to help the Admissions team get a sense of each applicant’s educational and work background. Applicants are also asked to complete self-assessment questions about their familiarity and technical experience with various data science topics and tools. It should not take more than 10 to 15 minutes to complete the online application.
  2. After the application is reviewed, the applicant will be contacted by a member of the Admissions team to schedule a video interview. This interview serves as a chance for both parties to understand better if the bootcamp program is the best fit for the background and goals of the applicant.
  3. If advanced to the final step, the applicant is invited to complete a technical assessment. It contains technical challenges that determine the thought process and programming experience of the applicant. Each applicant has 48 hours to complete and submit the assessment. The team will then review and evaluate the responses and determine if the applicant is ready to join the bootcamp.

Who is eligible to apply?

To enroll in the bootcamp, applicants must possess a minimum of a Bachelor’s Degree. Degrees in Math, Science or Technology are highly desirable. However, applicants with strong domain knowledge in an area that employs data scientists, and some background in either coding or statistics, will also be considered.

Under exceptional circumstances, an applicant without a baccalaureate degree may be considered for admittance into the bootcamp, in which case the applicant must meet the following requirements:

  • Proof of high school graduation
  • Proof of exceptional talent in computer programming
  • Evidence of domain knowledge in math and science
  • Pass the Academy’s Technical Assessment with a B or higher grade
  • Two letters of recommendation by relevant professionals

Does NYC Data Science Academy help bootcamp students with job placement?

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

Do online bootcamp students get job placement support?

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

How much statistics and programming are required for the program?

We work with every student individually to get their skills up to a level where they can start the bootcamp. We offer customized 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.

Do you provide financial assistance?

Funding opportunities are available through two different financing institutions: Ascent and Climb.

Ascent 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.

What is the cost for bootcamp?

The tuition for Data Science with Machine Learning or Data Science with Machine Learning - Online is $17,600. The tuition for Data Analytics Bootcamp - Online is $9,995. A deposit of $5,000 is required after acceptance to secure your spot.

Are scholarships available?

Yes, you can find the details here.

Can international students attend?

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.

Does NYC Data Science Academy provide visas?

Unfortunately we do not provide visas.

Have More Questions?

For more questions, visit our frequently asked questions page or schedule a call with us. with our admissions team.

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The online meeting portal allows students to schedule meetings with our dedicated mentors to discuss coursework, projects, and career advice. These mentors are professional data scientists working at global companies including PriceWaterhouseCoopers, Unilever, Vanguard, and National Grid.

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NYC Data Science Academy’s mission is to provide accelerated data science training programs that prepare people for employment as data science professionals and to offer continuing education courses for professional development.

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