Full-Financing
Lifelong Career Support

Data Science with Machine Learning

IN-PERSON/REMOTE LIVE INSTRUCTION or ONLINE INSTRUCTION
Learn data science anytime, anywhere with R, Python, Machine Learning, Big Data and Deep Learning.
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Immerse yourself in accelerated learning and launch your data science career through In-Person/Remote-Live Instruction or Interactive Distance Learning!
This bootcamp is designed to equip you with the dominant skills and tools for data analytics and machine learning.

Options to Meet Your Need

NYC Data Science Academy offers different options of in-person immersive learning and fully online or interactive distance learning to meet individual student needs. Although the bootcamp curricular contents are the same, students can choose a mode of instruction that best suits their needs and their unique learning style.

In-Person* or Remote Live Learning

(Either In-Person or Remote Live Learning)
Daily in-person learning or live learning in Zoom
Set schedules for all learners
Real-time interactions in the same environment
Synchronous networking opportunities
Community for immersive experience

Interactive Distance Learning

Access instructions at your own convenience
Plan your own schedules to meet learning objectives
Asynchronous interactions with instructors and staff
One-on-one support by academic mentors
Longer time to master curricular competencies
IN-PERSON / Remote live
Data Science Bootcamp
12 Weeks (Full-time)
Commit 40+ hours/week
Interactive Distance Learning
Data Science Bootcamp
16 Weeks (Full-time)
Commit 30-40 hours/week
Interactive Distance Learning
Data Science Bootcamp
24 Weeks (Part-time)
Commit 20-30 hours/week

What You Will Learn

In the 400-hour Data Science with Machine Learning bootcamp, students will take seven modules as listed below and learn the major tools and methods for performing data analyses and apply them to various projects typically found in the data science field. At the foundation level of the program, students learn to employ R and Python for data analytics projects and for presenting research results effectively. Beyond the foundational level, students study machine learning with Python and carry out research projects that involve advanced data science methods and strategies. The program also exposes students to concepts and practices in deep learning and big data. We cover packages such as NumPy, SciPy, Pandas, Scikit-learn, Keras, TensorFlow, SpaCy, but not limited to these pacakges:

  • - Scikit-learn is a free software machine learning library for the Python programming language machines.
  • - Keras is an open-source software library that provides a Python interface for artificial neural networks
  • - TensorFlow is a free and open-source software library for machine learning and artificial intelligence.
  • - SpaCy is an open-source software library for advanced natural language processing.
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.
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.

Outlooks and Outcomes

25%↑
Fast-growing career field
$94,280
Median Annual salary

Networking opportunities with alumni and hiring managers

Networking Opportunities

Featured Alumni

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.

Choose The Path That's Right For You

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
Choose The Path That's Right For You

Learn From the Best

Vivian Zhang
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.

Connect with Academic Mentors From Industry

Stella Kim
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.

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

Fall Quarter
Full-time
September 25, 2023 - January 19, 2024
Fall Quarter
Part-time
September 25, 2023 - March 16, 2024
Winter Quarter
Full-time
November 6, 2023 - March 2, 2024
Winter Quarter
Part-time
November 6, 2023 - April 27, 2024
Fall Session
September 25, 2023 - January 19, 2024
Fall Session
September 25, 2023 - March 16, 2024
Winter Session
November 6, 2023 - March 2, 2024
Winter Session
November 6, 2023 - April 27, 2024

Tuition & Finance

Tuition Total
$17,600
full tuition payment
Payments can be made either by cash, credit card, check, or wire-transfer
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.
$397.88
per month for 60 months.
Borrow up to an additional
$7,500 for cost of living
$375 - $439*
per month for 60 months
Available to foreign citizens with a
U.S. citizen or resident co-signer
* range varies based on approval interest rate
Merit Scholarships:
Women in Data Science Scholarship
Post-Doctoral Student Scholarship

What Our Alumni Say About Us

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

Student Life on Campus

9 AM
Map Marker
10 AM
11 AM
12 PM
1 PM
2 PM
3 PM
4 PM
5 PM
6 PM
7 PM
8 PM

9:30 AM - 12:30 PM
Morning Lectures

The lectures are conducted in modern classrooms equipped with live web-streaming technology. Students have 24/7 building access, free high-speed internet, pantry with breakfast cereal, tea, coffee, granola bars, fresh fruits and more. The detailed daily schedule is shared with students during the orientation..

Frequently Asked Questions

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.

Start Your Data Science Career Today