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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Full-time 16 weeks
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Full-time 12 weeks
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4 - 6 weeks
  • Python and R courses at different levels
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Getting Started with Your First Data Science Project
Oct 14th, 2020
6:00PM
Find out the steps that to take when working on your first data science project: where to begin, where to aim, what conversations to have. By joining this workshop, you will find out the initial steps to take when working on your first data science project: where to begin, where to aim, and what conversations to have. You will learn from hands-on examples in Python which demonstrate that you may find different analytic and modeling paths with the same data depending on the objectives and the intended audience for the finished product. In particular, you will gain a better understanding of a project’s real value beyond a simple, standard metric of “performance.” Here are the key takeaways from this workshop. - The right place to start a data science project is to understand the project’s purpose.- How to understand what the value of a data science project is beyond the Kaggle mindset- Every step of a data science project should be in communication with every other step and the actual goal/scope/audience Save your spot today for this free online data science workshop here!https://info.nycdatascience.com/getting-started-with-your-first-data-science-project?utm_source=meetup&utm_medium=social&utm_campaign=Getting-Started-with-Your-First-Data-Science-Project
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
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: 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 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 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
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
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
Getting Started with Your First Data Science Project
Oct 14th, 2020
6:00PM
Find out the steps that to take when working on your first data science project: where to begin, where to aim, what conversations to have. By joining this workshop, you will find out the initial steps to take when working on your first data science project: where to begin, where to aim, and what conversations to have. You will learn from hands-on examples in Python which demonstrate that you may find different analytic and modeling paths with the same data depending on the objectives and the intended audience for the finished product. In particular, you will gain a better understanding of a project’s real value beyond a simple, standard metric of “performance.” Here are the key takeaways from this workshop. - The right place to start a data science project is to understand the project’s purpose.- How to understand what the value of a data science project is beyond the Kaggle mindset- Every step of a data science project should be in communication with every other step and the actual goal/scope/audience Save your spot today for this free online data science workshop here!https://info.nycdatascience.com/getting-started-with-your-first-data-science-project?utm_source=meetup&utm_medium=social&utm_campaign=Getting-Started-with-Your-First-Data-Science-Project
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
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: 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 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 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
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
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
October
2020
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