Join us for our FREE webinar on Data Visualization with R on October 16. RSVP today: Click here

Become a Data Scientist

Launch your career as a data scientist through our cutting edge curriculum, real–world projects, and personalized career support
Apply to Bootcamp
Not sure what you're looking for?
Take a quiz to find out!
Choose Your Learning Path
On Campus
Immersive Bootcamp

Learn R, Python, machine learning and big data in just 12 weeks with our full job support

Short Courses

Upgrade your data science skills with these in-person targeted courses and earn a certificate

Online
Remote Bootcamp

Learn data science online at your own pace or through our live daily lectures.

Online Training

Master in-demand skills through industry-proven curriculum and premium learning system

Corporate Offerings

We are experts in customizing training, consulting, and project help. Let us help you boost your team’s data science skills.

Customized Training

Corporate training offerings in R, Python and Big Data, customized for your needs: from high level executive offerings to technical hands-on training in programming and implementation.

Consulting

Expert professional consulting services from data scientists and engineers, building big data solutions and solving data science problems.

Project Help

Free service offered by our advanced Bootcamp trainees to solve immediate project needs, from visualization, to drawing insights from data, to predictive modeling.

Become Our Hiring Partner

Your search to hire a data scientist starts here.
Join Our Next Career Day
Wed, Sep 25, 2019
Data Scientist & Employer Networking Event
6:00 PM – 8:00 PM EDT
RSVP

Student Success

Our Alumni work at these firms

Upcoming Courses and Events

Check your schedule for some in-person data science actions
Sep 25th, 2019
Data Scientist & Employer Networking Event
Event

Join Our Data Scientist & Employer Networking Event

6:00 PM – 8:00 PM EDT
RSVP
Oct 2nd, 2019
Deep Learning Illustrated: Book Signing & Course Demo
Event

The talk will serve as an overview of Jon Krohn's upcoming Deep Learning course (http://nycdatascience.com/courses/deep-learning/) at NYC Data Science Academy, running from October 19th to December 7th. It will conclude with a book-signing featuring Jon's newly-published book, Deep Learning Illustrated - 5 copies will be given away to attendees. Deep Learning algorithms have become unprecedentedly transformative across industry verticals and are now the state of the art across applications as diverse as image classification, natural language processing, generation of content, and game-playing. Almost unknown a few years ago, Deep Learning today powers countless everyday services from Tesla's Autopilot to Amazon Alexa’s voice recognition, and from Google Translate to superhuman ability at elaborate boardgames. Via analogy to biological neurons and the human brain, this talk is a highly visual introduction to Deep Learning. It features interactive demos and example code from all three of the leading open-source Deep Learning libraries: TensorFlow, Keras, and PyTorch. Agenda:6:00 - 6:30 pm - Food, Drinks and Mingling6:30 - 6:40 pm - Hank, a student on the previous Deep Learning class cohort, will present on his capstone project and his experience taking the course6:40 - 7:30 pm - Course Demo by Jon Krohn7:30 - 8:00 pm - Q&A and Mingling Speaker:Jon Krohn (https://www.jonkrohn.com/) is Chief Data Scientist at the machine learning company untapt. He is the presenter of a popular series of tutorials on artificial neural networks, including (https://learning.oreilly.com/videos/deep-learning-with/9780134770826), and is the author of Deep Learning Illustrated (https://deeplearningillustrated.com), the acclaimed book released by Pearson in 2019. Jon holds a doctorate in neuroscience from Oxford University and has been publishing on machine learning in leading academic journals since 2010. He guest lectures at Columbia University and, along with researchers from the university's Irving Medical Center, holds a National Institutes of Health grant to automate medical image processing with deep learning.

6:00PM
RSVP
Oct 16th, 2019
Data Visualization with R (Free Course Demo)
Event

Join us for an online introductory lesson on Data Visualization with R from NYC Data Science Academy Instructor Michael Charles. The course demo will feature basic coding techniques that will help you to write functions, generate graphs and fit basic statistical models. You’ll also learn how to load, save, and transform data as well as understand the process of data analysis in R alongside some data visualization best practices. Both, programmers who are looking to expand their data toolkit and non-programmers who do not have any coding experience, are invited to join. Participants are encouraged to download the latest versions R and R Studio prior to the session. This session will also include a brief overview of the NYC Data Science Academy, including its data science bootcamp and other course offerings. What to expect:In the first part of the info session, we will give you an overview of what makes NYC Data Science Academy different. You will learn how to prepare for the Bootcamp, what to learn, and application process. The information session will be as follows:7:00 - 7:10 pm Introduction to NYC Data Science Academy and What We Do7:10 - 7:45 pm Data Visualization with R by Michael Charles7:45 - 8:00 pm Q&A Save your spot → https://info.nycdatascience.com/online-data-visualization-oct2019

7:00PM
RSVP
Oct 19th, 2019
Deep Learning (with TensorFlow 2, Keras and PyTorch)
Course

This course is an introduction to artificial neural networks that brings high-level theory to life with interactive labs featuring TensorFlow, Keras, and PyTorch -- the leading Deep Learning libraries. Essential theory will be covered in a manner that provides students with a complete intuitive understanding of Deep Learning’s underlying foundations. Paired with hands-on code run-throughs in Jupyter notebooks as well as strategic advice 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 all of the contemporary families, including: Convolutional Networks for machine vision Long Short-Term Memory Recurrent Nets for natural language processing and time series analysis Generative Adversarial Networks for producing jaw-dropping synthetic data Reinforcement Learning for complex sequential decision-making

11:00am-5:00pm
Enroll Now
Oct 21st, 2019
Introductory Python
Course

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.

7:00-9:30pm
Enroll Now
Oct 22nd, 2019
Kafka on Kubernetes: Just because you can, doesn't mean you should!
Event

In this technical deep dive, Viktor Gamov will go through challenges and pitfalls of managing Kafka on Kubernetes as well as the goals and lessons learned from the development of the Confluent Operator for Kubernetes. Abstract:When it comes to choosing a distributed streaming platform for real-time data pipelines, everyone knows the answer: Apache Kafka! And when it comes to deploying applications at scale without needing to integrate different pieces of infrastructure yourself, the answer nowadays is increasingly Kubernetes. However, with all great things, the devil is truly in the details. While Kubernetes does provide all the building blocks that are needed, a lot of thought is required to truly create an enterprise-grade Kafka platform that can be used in production. Agenda6:45 - 7:00 pm - Food, Drinks, and Mingling7:00 - 8:00 pm - Talk by Viktor Gamov8:00 pm - 8:15 pm - Q&A and Networking. Speaker Bio:Viktor Gamov is a Developer Advocate at Confluent, the company that makes a streaming platform based on Apache Kafka. Working in the field, Viktor Gamov developed comprehensive expertise in building enterprise application architectures using open source technologies. He enjoys helping different organizations design and develop low latency, scalable and highly available distributed systems. He is a professional conference speaker on distributed systems, streaming data, JVM and DevOps topics, and is regular on events including JavaOne, Devoxx, OSCON, QCon, and others. He co-authored O’Reilly’s 'Enterprise Web Development'.

6:45PM
RSVP
Oct 26th, 2019
Data Science with R: Data Analysis and Visualization
Course

This course is a 35-hour program designed to provide a comprehensive introduction to R. You’ll learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models with data. In addition to a theoretical framework in which you will learn the process of data analysis, this course focuses on the practical tools needed in data analysis and visualization. By the end of the course, you will have mastered the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting your codes.

10:00am-5:00pm
Enroll Now
Oct 26th, 2019
Data Science with R: Machine Learning
Course

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 of 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.

10:00am-5:00pm
Enroll Now
Oct 27th, 2019
Data Science with Python: Data Analysis and Visualization
Course

This class is a comprehensive introduction to data science with Python programming language. This class targets people who have some basic knowledge of programming and want to take it to the next level. It introduces how to work with different data structures in Python and covers the most popular data analytics and visualization modules, including numpy, scipy, pandas, matplotlib, and seaborn. We use Ipython notebook to demonstrate the results of codes and change codes interactively throughout the class.

1:00-5:00pm
Enroll Now
Oct 27th, 2019
Data Science with Python: Machine Learning
Course

This 20-hour Machine Learning with Python course covers all the basic machine learning methods and Python modules (especially Scikit-Learn) for implementing them. The five sessions cover: simple and multiple Linear regressions; classification methods including logistic regression, discriminant analysis and naive bayes, support vector machines (SVMs) and tree based methods; cross-validation and feature selection; regularization; principal component analysis (PCA) and clustering algorithms. After successfully completing of 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.

1:00-5:00pm
Enroll Now
Jan 6th, 2020
Data Science Bootcamp: Intensive 12-Week
Course

NYC Data Science Academy. a full-time 12-week immersive program, offers the highest quality in data science training. It’s designed specifically around the skills employers are seeking, including R, Python, Machine Learning, Hadoop, Spark, github, SQL, and much more.

Monday through Friday, from 9:00am to 6:00pm
Enroll Now
Jan 14th, 2020
Introductory Python
Course

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.

7:00-9:30pm
Enroll Now
Jan 14th, 2020
Big Data with Amazon Cloud, Hadoop/Spark and Docker
Course

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.

7:00-9:30pm
Enroll Now
Jan 18th, 2020
Data Science with R: Machine Learning
Course

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 of 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.

10:00am-5:00pm
Enroll Now
Jan 18th, 2020
Data Science with R: Data Analysis and Visualization
Course

This course is a 35-hour program designed to provide a comprehensive introduction to R. You’ll learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models with data. In addition to a theoretical framework in which you will learn the process of data analysis, this course focuses on the practical tools needed in data analysis and visualization. By the end of the course, you will have mastered the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting your codes.

10:00am-5:00pm
Enroll Now
Jan 19th, 2020
Data Science with Python: Machine Learning
Course

This 20-hour Machine Learning with Python course covers all the basic machine learning methods and Python modules (especially Scikit-Learn) for implementing them. The five sessions cover: simple and multiple Linear regressions; classification methods including logistic regression, discriminant analysis and naive bayes, support vector machines (SVMs) and tree based methods; cross-validation and feature selection; regularization; principal component analysis (PCA) and clustering algorithms. After successfully completing of 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.

1:00-5:00pm
Enroll Now
Jan 19th, 2020
Data Science with Python: Data Analysis and Visualization
Course

This class is a comprehensive introduction to data science with Python programming language. This class targets people who have some basic knowledge of programming and want to take it to the next level. It introduces how to work with different data structures in Python and covers the most popular data analytics and visualization modules, including numpy, scipy, pandas, matplotlib, and seaborn. We use Ipython notebook to demonstrate the results of codes and change codes interactively throughout the class.

1:00-5:00pm
Enroll Now