Become a Data Scientist

NYC Data Science Academy is the premier training ground providing premium, accelerated training in data science through immersive bootcamps and courses.
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In-person Bootcamp
Full-time 12 weeks

Build your career in data science by learning today's most in-demand skills through extensive in-person instruction

Online Bootcamp
Full-time 16 weeks
Part-time 24 weeks

Become a data scientist by undergoing a rigorous, online program tailored to accelerate your career on a busy schedule

Professional Development Courses
4 - 6 weeks

Accelerate your career by learning data science through individual courses perfect for professionals at different levels

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.

Discover Our Student Success

Network with our alumni and hiring partners from these companies
meet more Alumni

Join Our Upcoming Courses and Events

How to Excel as a Data Scientist in Any Company
Oct 22nd, 2020
6:00PM
Hear from bootcamp alumna Katie Critelli as she shares practical advice on how to hit the ground running and excel in any company. About this Event: Join us on Thursday, October 22, and hear from bootcamp alumna Katie Critelli, Product Manager/Data Scientist at Total Brain. She will share advice and valuable lessons on how to hit the ground running and excel as a data scientist in any company. In her presentation, she will help you: Better define your job search and identify the best role for youUnderstand how the role of a data scientist differs in various company environments, using the examples of a large bank and a small startupUnderstand some typical challenges and questions you'll encounter day-to-day in each roleHit the ground running and be prepared for whatever work environment you end up choosing. About Katie: Katie graduated from the University of Pennsylvania with a Bachelor's degree in Neuroscience, and an Honor's thesis focused on protein-modeling in neurodegenerative diseases. In her previous roles, she worked as a Healthcare Analyst at Booz Allen Hamilton and as an Associate at Deutsche Bank. Katie has joined NYC Data Science Academy to strengthen her technical skills to pursue further work in neuroscience and healthcare. Currently, she works as a Product Manager/Data Scientist at the self-monitoring and self-care platform, Total Brain. About NYC Data Science Academy: NYC Data Science Academy provides award-winning accelerated data science training programs and courses that prepare people for employment opportunities across all industries as data science professionals. Our data science bootcamps, full-time and part-time, have been recognized the Best Data Science Bootcamp for 5 years in a row by Switchup.org. Save your spot today →https://info.nycdatascience.com/how-to-excel-as-a-data-scientist-in-any-company?utm_source=meetup&utm_medium=referral&utm_campaign=how-to-excel-as-a-data-scientist-in-any-company
Enroll Now
Big Data with Amazon Cloud, Hadoop/Spark and Docker
Oct 27th, 2020
7:00-9:30pm
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.
Enroll Now
How Strong is Your Machine Learning Model?
Oct 28th, 2020
6:00PM
Learn about the concept of the likelihood function as it supervises models from logistic regression to deep learning. About this Event Machine learning enables a system to learn from data instead of explicit programming. It is a form of AI that can produce predictions as a predictive algorithm trains input data. As data science professionals, we must ensure that our models will provide accurate predictions at best, so we develop ways to monitor our predictive model's performance at every stage. Join us on October 28, Wednesday, and learn about the concept of the likelihood function in logistic regression. A likelihood function is a widely accepted concept for such measurement, from a simple linear model such as logistic regression to a sophisticated neural network. Moreover, you will understand that a model can be taken for a family of parameterized distributions. This idea will also be generalized to a simple linear regression to introduce the likelihood approach to train a model. This workshop is best for professionals interested in learning more about the practical applications of AI and machine learning. Save your spot herehttps://info.nycdatascience.com/how-strong-is-your-machine-learning-model?utm_source=meetup&utm_medium=referral&utm_campaign=how-strong-is-your-machine-learning-model
Enroll Now
Data Science with R: Machine Learning
Oct 31st, 2020
10:00am-5:00pm
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.
Enroll Now
Data Science with R: Data Analysis and Visualization
Oct 31st, 2020
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
Data Science with Python: Machine Learning
Nov 1st, 2020
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
Data Science with Python: Data Analysis and Visualization
Nov 1st, 2020
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
Introductory Python
Nov 3rd, 2020
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
Data Science with R: Data Analysis and Visualization
Jan 9th, 2021
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
Data Science with R: Machine Learning
Jan 9th, 2021
10:00am-5:00pm
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.
Enroll Now
Data Science with Python: Data Analysis and Visualization
Jan 10th, 2021
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
Data Science with Python: Machine Learning
Jan 10th, 2021
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
Introductory Python
Jan 12th, 2021
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
Big Data with Amazon Cloud, Hadoop/Spark and Docker
Jan 12th, 2021
7:00-9:30pm
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.
Enroll Now
Data Science with R: Machine Learning
Feb 27th, 2021
10:00am-5:00pm
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.
Enroll Now
Data Science with R: Data Analysis and Visualization
Feb 27th, 2021
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
Data Science with Python: Data Analysis and Visualization
Feb 28th, 2021
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
Data Science with Python: Machine Learning
Feb 28th, 2021
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
Introductory Python
Mar 2nd, 2021
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
How to Excel as a Data Scientist in Any Company
Oct 22nd, 2020
6:00PM
Hear from bootcamp alumna Katie Critelli as she shares practical advice on how to hit the ground running and excel in any company. About this Event: Join us on Thursday, October 22, and hear from bootcamp alumna Katie Critelli, Product Manager/Data Scientist at Total Brain. She will share advice and valuable lessons on how to hit the ground running and excel as a data scientist in any company. In her presentation, she will help you: Better define your job search and identify the best role for youUnderstand how the role of a data scientist differs in various company environments, using the examples of a large bank and a small startupUnderstand some typical challenges and questions you'll encounter day-to-day in each roleHit the ground running and be prepared for whatever work environment you end up choosing. About Katie: Katie graduated from the University of Pennsylvania with a Bachelor's degree in Neuroscience, and an Honor's thesis focused on protein-modeling in neurodegenerative diseases. In her previous roles, she worked as a Healthcare Analyst at Booz Allen Hamilton and as an Associate at Deutsche Bank. Katie has joined NYC Data Science Academy to strengthen her technical skills to pursue further work in neuroscience and healthcare. Currently, she works as a Product Manager/Data Scientist at the self-monitoring and self-care platform, Total Brain. About NYC Data Science Academy: NYC Data Science Academy provides award-winning accelerated data science training programs and courses that prepare people for employment opportunities across all industries as data science professionals. Our data science bootcamps, full-time and part-time, have been recognized the Best Data Science Bootcamp for 5 years in a row by Switchup.org. Save your spot today →https://info.nycdatascience.com/how-to-excel-as-a-data-scientist-in-any-company?utm_source=meetup&utm_medium=referral&utm_campaign=how-to-excel-as-a-data-scientist-in-any-company
Enroll Now
Big Data with Amazon Cloud, Hadoop/Spark and Docker
Oct 27th, 2020
7:00-9:30pm
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.
Enroll Now
How Strong is Your Machine Learning Model?
Oct 28th, 2020
6:00PM
Learn about the concept of the likelihood function as it supervises models from logistic regression to deep learning. About this Event Machine learning enables a system to learn from data instead of explicit programming. It is a form of AI that can produce predictions as a predictive algorithm trains input data. As data science professionals, we must ensure that our models will provide accurate predictions at best, so we develop ways to monitor our predictive model's performance at every stage. Join us on October 28, Wednesday, and learn about the concept of the likelihood function in logistic regression. A likelihood function is a widely accepted concept for such measurement, from a simple linear model such as logistic regression to a sophisticated neural network. Moreover, you will understand that a model can be taken for a family of parameterized distributions. This idea will also be generalized to a simple linear regression to introduce the likelihood approach to train a model. This workshop is best for professionals interested in learning more about the practical applications of AI and machine learning. Save your spot herehttps://info.nycdatascience.com/how-strong-is-your-machine-learning-model?utm_source=meetup&utm_medium=referral&utm_campaign=how-strong-is-your-machine-learning-model
Enroll Now
Data Science with R: Machine Learning
Oct 31st, 2020
10:00am-5:00pm
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.
Enroll Now
Data Science with R: Data Analysis and Visualization
Oct 31st, 2020
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
Data Science with Python: Machine Learning
Nov 1st, 2020
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
Data Science with Python: Data Analysis and Visualization
Nov 1st, 2020
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
Introductory Python
Nov 3rd, 2020
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
Data Science with R: Data Analysis and Visualization
Jan 9th, 2021
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
Data Science with R: Machine Learning
Jan 9th, 2021
10:00am-5:00pm
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.
Enroll Now
Data Science with Python: Data Analysis and Visualization
Jan 10th, 2021
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
Data Science with Python: Machine Learning
Jan 10th, 2021
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
Introductory Python
Jan 12th, 2021
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
Big Data with Amazon Cloud, Hadoop/Spark and Docker
Jan 12th, 2021
7:00-9:30pm
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.
Enroll Now
Data Science with R: Machine Learning
Feb 27th, 2021
10:00am-5:00pm
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.
Enroll Now
Data Science with R: Data Analysis and Visualization
Feb 27th, 2021
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
Data Science with Python: Data Analysis and Visualization
Feb 28th, 2021
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
Data Science with Python: Machine Learning
Feb 28th, 2021
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
Introductory Python
Mar 2nd, 2021
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
October
2020
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