Launch Your Dream Career in Data Science at an Accredited Bootcamp!

Explore our accredited bootcamps and professional development courses to have rigorous and robust training for high-demand careers in the data science field.

Choose Your Learning Path

Learn on your own schedule!
7 - 12 weeks, Full Time or part time

Analyze real business cases by utilizing data analytics tools and methods.

Learn in-person or online!
12 - 24 weeks, Full Time or part time

Learn in-depth machine learning knowledge and skills with real-world applications.

Learn at any level, anywhere!
4 - 6 weeks, part time

Upskill yourself with Python, R, and other machine learning tools at different levels.

Nationally Accredited Data Science Academy

Options to Meet Your Needs

You have different options of in-person immersive learning, remote live, or interactive distance learning to master the content while meeting your unique learning style.

Project-Oriented Curriculum

You will gain business experience from capstone projects with real-world datasets and business considerations; the capstone projects are often sponsored by companies in New York City.

Get Hired Upon Graduation

You’ll benefit from extensive job placement assistance ranging from individualized resume support and interview guidance to access to our network of hiring partners and events.

Life Time Career Support

Career Guidance and Networking Events

You have life-long access to our career-related services to get connected with industry professionals and to keep up to date with industry hiring trends.

Personalized Resume Reviews

You will have at least 3 rounds of 1-on-1 personalized resume reviews, LinkedIn profile reviews, and career guidance sessions.

Ace the Interviews

Practice with mock interviews including coding challenges and behavioral questions. You will also get 1-on-1 post-interview reviews and feedback from your career mentor.

Sofia Wang
“Upon graduation, there are helpful resources on landing the next job - mock interviews, career advising, and networking.”
Currently at
David Corrigan
“You will learn far more efficiently here than you would on your own. There is simply too much material to learn in such a short time – without knowledgeable...”
Currently at
Dean Goldman
“Within a few weeks after graduating, I was offered my first full-time job as a data engineer. (I do not come from a CS, math or stats background). NYC Data Science...”
Currently at
Mike Chuang
“The course covered broad topics in data science with enough depth to be applied in the real world, so I now feel empowered to further my learning and tackle even...”
Currently at
David Steinmetz
“The opportunity to network was incredible. You are beginning your data science career having forged strong bonds with 35 other incredibly intelligent and inspiring...”
Currently at

Discover Our Student Success

Corporate Training

Harness the full potential of your company's existing talent and data to deliver business insights that can maximize your bottom line. Build a training program tailored to your unique specifications and needs.

Rigorous corporate bootcamps

Onsite training with our reliable team of instructors

Live online training ideal for remote teams

Customized training paths for varying skill levels

Licensed content and product solutions

Become A Hiring Partner

Our graduates have undergone a rigorous, collaborative training experience as they prepare to join leading companies as data science professionals. Join our hiring partner network and let us help you grow your team with the right talent.

Join Our Upcoming Courses and Events

Jul 5th, 2022
5:00PM EDT
<[Register here](https://nycdatascience.zoom.us/webinar/register/WN_Rt8TB3rYSseoL_mdf5aOWw)> Join us on \| **Tuesday,** **July 5th at 5 PM** \| to learn how to visualize information like a data scientist\. No coding\, statistical\, machine learning\, or visualization experience is required to attend\. **About this event****One of the most important skills of a data scientist is properly communicating concepts. Perhaps, the best way is through visualizations. In this webinar, we will look at multiple types of visualizations and analyze why some work and others do not. This will include an explanation of when to use specific types of visualizations, what are important features to consider when creating them, and best practices in designing them.** **Agenda:****5:00 - 5:15 PM - NYC Data Science Academy Overview****5:15 - 5:50 PM** * **What is a good visualization?*** **How to decide which visualization to use*** **Best practices when creating visualizations*** **Creating a great visualization** **5:50 - 6:00 PM - Q&A** **Vivian is the CTO and School Director of NYC Data Science and CTO of SupStat. With her extensive experience working in the data science field, she developed expertise in multiple programming languages, including R, Python, Hadoop, and Spark. In August 2016, Forbes ranked her amongst one of the nine women leading the pack in the data analytics field, In 2013, she founded the NYC Open Data Meetup group, which stands as one of the largest data science communities offering meetups, conferences, and a weekly newsletter. In her spare time, Vivian enjoys meeting people and sharing her motivational stories with our students and other professionals.**  **About NYC Data Science Academy** **[NYC Data Science Academy](https://bit.ly/3zZPdyq) provides data science training programs and courses that prepare people for employment opportunities for data science professionals across all industries.** **NYC Data Science Academy teaches data science, trains companies and their employees to better profit from data, excels at big data project consulting, and connects trained Data Scientists to our industry. We have graduated over 5000 students at this point!** **Join our [Interactive Distance / In-Person Learning Bootcamp](https://bit.ly/3NgAMZM), and get ready for the next step in your data science career!**
Register Now
Aug 5th, 2022
10:00am-5:00pm
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.
Enroll Now
Aug 6th, 2022
1:00-5:00pm
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.
Enroll Now
Aug 6th, 2022
1:00-5:00pm
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.
Enroll Now
Aug 7th, 2022
7:00-9:00pm
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.
Enroll Now
Aug 9th, 2022
5:00PM EDT
**Unleashing the full potential of data and AI requires a paradigm shift in the algorithms and tools used to analyze data and build models towards more interactive systems with highly collaborative and visual interfaces. Ideally, data scientists and domain experts should be able to closely work together and make discoveries together by directly manipulating, analyzing and visualizing data on the spot as a team, instead of having week-long forth-and-back interactions between them.** **Current visualization and workflow tools are ill-suited for this purpose. They were not designed to be interactive nor to support teams to actually work together rather than just share final results. Similarly, most machine learning algorithms are not able to provide initial answers at "human speed" (i.e., seconds), nor are existing methods sufficient to convey the impact of the various risk factors, such as multi-hypothesis problems. Finally, most visual data exploration tools still fail when used over large datasets or require horrendous loading times before any real-work can begin.** **Join us on August 9th from 5-6 PM EST, to learn how Northstar, a novel system developed for Interactive Data Exploration, required us to completely rethink the entire analytics stack.** **Agenda:****5:00 - 5:15 PM: NYC Data Science Academy Introduction****5:15 - 5:50 PM: Northstar (A Novel System) Presentation****5:50 - 6:00 PM: Q&A** **Bio:****Tim Kraska is an Associate Professor of Electrical Engineering and Computer Science in MIT's Computer Science and Artificial Intelligence Laboratory, co-director of the Data System and AI Lab at MIT ([email protected]), and co-founder of Einblick Analytics. Currently, his research focuses on building systems for machine learning, and using machine learning for systems to build instance-optimized systems. Tim is most known for developing techniques to make Data Science more interactive and collaborative, and creating the first Learned Index structure and Learned Query Optimizer.** **About NYC Data Science Academy** **NYC Data Science Academy provides data science training programs and courses that prepare students to use data science tools and apply them to real-world situations.** **NYC Data Science Academy teaches data science, trains companies and their employees to better profit from data, excels at big data project consulting, and connects trained Data Scientists to our industry. We have graduated over 5000 students at this point!** **Join our Interactive Distance / In-Person Learning Bootcamp, and get ready for the next step in your data science career! ([https://nycdatascience.edu/data-science-bootcamp/](https://nycdatascience.edu/data-science-bootcamp/))**
Register Now
Sep 23rd, 2022
10:00am-5:00pm
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.
Enroll Now
Sep 24th, 2022
1:00-5:00pm
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.
Enroll Now
Sep 24th, 2022
1:00-5:00pm
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.
Enroll Now
Sep 25th, 2022
7:00-9:00pm
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.
Enroll Now
Jul 5th, 2022
5:00PM EDT
<[Register here](https://nycdatascience.zoom.us/webinar/register/WN_Rt8TB3rYSseoL_mdf5aOWw)> Join us on \| **Tuesday,** **July 5th at 5 PM** \| to learn how to visualize information like a data scientist\. No coding\, statistical\, machine learning\, or visualization experience is required to attend\. **About this event****One of the most important skills of a data scientist is properly communicating concepts. Perhaps, the best way is through visualizations. In this webinar, we will look at multiple types of visualizations and analyze why some work and others do not. This will include an explanation of when to use specific types of visualizations, what are important features to consider when creating them, and best practices in designing them.** **Agenda:****5:00 - 5:15 PM - NYC Data Science Academy Overview****5:15 - 5:50 PM** * **What is a good visualization?*** **How to decide which visualization to use*** **Best practices when creating visualizations*** **Creating a great visualization** **5:50 - 6:00 PM - Q&A** **Vivian is the CTO and School Director of NYC Data Science and CTO of SupStat. With her extensive experience working in the data science field, she developed expertise in multiple programming languages, including R, Python, Hadoop, and Spark. In August 2016, Forbes ranked her amongst one of the nine women leading the pack in the data analytics field, In 2013, she founded the NYC Open Data Meetup group, which stands as one of the largest data science communities offering meetups, conferences, and a weekly newsletter. In her spare time, Vivian enjoys meeting people and sharing her motivational stories with our students and other professionals.**  **About NYC Data Science Academy** **[NYC Data Science Academy](https://bit.ly/3zZPdyq) provides data science training programs and courses that prepare people for employment opportunities for data science professionals across all industries.** **NYC Data Science Academy teaches data science, trains companies and their employees to better profit from data, excels at big data project consulting, and connects trained Data Scientists to our industry. We have graduated over 5000 students at this point!** **Join our [Interactive Distance / In-Person Learning Bootcamp](https://bit.ly/3NgAMZM), and get ready for the next step in your data science career!**
Register Now
Aug 5th, 2022
10:00am-5:00pm
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.
Enroll Now
Aug 6th, 2022
1:00-5:00pm
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.
Enroll Now
Aug 6th, 2022
1:00-5:00pm
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.
Enroll Now
Aug 7th, 2022
7:00-9:00pm
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.
Enroll Now
Aug 9th, 2022
5:00PM EDT
**Unleashing the full potential of data and AI requires a paradigm shift in the algorithms and tools used to analyze data and build models towards more interactive systems with highly collaborative and visual interfaces. Ideally, data scientists and domain experts should be able to closely work together and make discoveries together by directly manipulating, analyzing and visualizing data on the spot as a team, instead of having week-long forth-and-back interactions between them.** **Current visualization and workflow tools are ill-suited for this purpose. They were not designed to be interactive nor to support teams to actually work together rather than just share final results. Similarly, most machine learning algorithms are not able to provide initial answers at "human speed" (i.e., seconds), nor are existing methods sufficient to convey the impact of the various risk factors, such as multi-hypothesis problems. Finally, most visual data exploration tools still fail when used over large datasets or require horrendous loading times before any real-work can begin.** **Join us on August 9th from 5-6 PM EST, to learn how Northstar, a novel system developed for Interactive Data Exploration, required us to completely rethink the entire analytics stack.** **Agenda:****5:00 - 5:15 PM: NYC Data Science Academy Introduction****5:15 - 5:50 PM: Northstar (A Novel System) Presentation****5:50 - 6:00 PM: Q&A** **Bio:****Tim Kraska is an Associate Professor of Electrical Engineering and Computer Science in MIT's Computer Science and Artificial Intelligence Laboratory, co-director of the Data System and AI Lab at MIT ([email protected]), and co-founder of Einblick Analytics. Currently, his research focuses on building systems for machine learning, and using machine learning for systems to build instance-optimized systems. Tim is most known for developing techniques to make Data Science more interactive and collaborative, and creating the first Learned Index structure and Learned Query Optimizer.** **About NYC Data Science Academy** **NYC Data Science Academy provides data science training programs and courses that prepare students to use data science tools and apply them to real-world situations.** **NYC Data Science Academy teaches data science, trains companies and their employees to better profit from data, excels at big data project consulting, and connects trained Data Scientists to our industry. We have graduated over 5000 students at this point!** **Join our Interactive Distance / In-Person Learning Bootcamp, and get ready for the next step in your data science career! ([https://nycdatascience.edu/data-science-bootcamp/](https://nycdatascience.edu/data-science-bootcamp/))**
Register Now
Sep 23rd, 2022
10:00am-5:00pm
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.
Enroll Now
Sep 24th, 2022
1:00-5:00pm
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.
Enroll Now
Sep 24th, 2022
1:00-5:00pm
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.
Enroll Now
Sep 25th, 2022
7:00-9:00pm
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.
Enroll Now
June
2022