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Data Analytics Bootcamp

12 WEEKS

An industry-embraced data analytics bootcamp
Recorded lessons, exciting projects, and more
Regular interactions with instructors and mentors

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Data Science with Machine
Learning Bootcamps

12 - 24 Weeks, Full time or part time

In-depth program including machine learning
Immersive or interactive learning environment
Regular interactions with instructors and mentors

Learn at any level, anywhere

Professional Development Courses

4 - 6 weeks

Python and R courses at different levels
Expert instructor support
Real-time instruction in Zoom rooms

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

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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.

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Big Data with Amazon Cloud, Hadoop/Spark and Docker

Aug 10th, 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.

Readability Counts: Best Practices in Python Coding

Aug 11th, 2021

6:00PM

Join us on Wednesday, August 11 at 6 PM EST, to discuss popular Python coding conventions, and learn how to incorporate them into your work to increase your code's readability. This session will cover styles that will help you write code that is more conducive to collaboration, which will make you more attractive as a candidate or colleague in the industry.As programmers, we try to write elegant code. This is for the benefit of those who may read and use our code in the future, including ourselves. As the PEP8 guide states, one of the key insights from Guido van Rossum, the creator of Python, is that "code is read much more often than it is written." Readability is one of the essential qualities of beautiful code. SIGN UP NOW TO RECEIVE THE WEBINAR LINK(Feel free to join 10 minutes prior to the beginning of the session) Check out our current promotions: https://nycdatascience.com/data-science-bootcamp/ Agenda6:00 pm - 6:05 pm: NYC Data Science Academy Overview6:05 pm - 6:50pm Hands-on workshop given by Alex6:50 pm - 7:00 pm Q&A and more minglingAbout the SpeakerAlex received his B.A. in Environmental Biology from Columbia University. He has experience with multiple computer languages, including Python, R, and SQL. He has worked on many projects including scraping movie critic reviews from RottenTomatoes to make a movie recommendation system. Alex is passionate about animal behavior and finding innovative ways to use data science in the field of biology. About NYC Data Science AcademyNYC Data Science Academy provides award-winning accelerated 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 2000 students at this point! Join our Interactive Distance Learning bootcamp, and get ready for the next step in your data science career! (https://nycdatascience.com/data-science-bootcamp/)Classes start on August 16th! Apply by August 9th to get a 10% off your tuition and secure your seat!

Data Science with R: Data Analysis and Visualization

Sep 18th, 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.

Data Science with Python: Machine Learning

Sep 19th, 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.

Data Science with Python: Data Analysis and Visualization

Sep 19th, 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.

Introductory Python

Sep 20th, 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.

Big Data with Amazon Cloud, Hadoop/Spark and Docker

Oct 19th, 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.

Data Science with R: Data Analysis and Visualization

Nov 13th, 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.

Data Science with Python: Machine Learning

Nov 14th, 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.

Data Science with Python: Data Analysis and Visualization

Nov 14th, 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.

Introductory Python

Nov 15th, 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.

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Big Data with Amazon Cloud, Hadoop/Spark and Docker

Aug 10th, 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.

Readability Counts: Best Practices in Python Coding

Aug 11th, 2021

6:00PM

Join us on Wednesday, August 11 at 6 PM EST, to discuss popular Python coding conventions, and learn how to incorporate them into your work to increase your code's readability. This session will cover styles that will help you write code that is more conducive to collaboration, which will make you more attractive as a candidate or colleague in the industry.As programmers, we try to write elegant code. This is for the benefit of those who may read and use our code in the future, including ourselves. As the PEP8 guide states, one of the key insights from Guido van Rossum, the creator of Python, is that "code is read much more often than it is written." Readability is one of the essential qualities of beautiful code. SIGN UP NOW TO RECEIVE THE WEBINAR LINK(Feel free to join 10 minutes prior to the beginning of the session) Check out our current promotions: https://nycdatascience.com/data-science-bootcamp/ Agenda6:00 pm - 6:05 pm: NYC Data Science Academy Overview6:05 pm - 6:50pm Hands-on workshop given by Alex6:50 pm - 7:00 pm Q&A and more minglingAbout the SpeakerAlex received his B.A. in Environmental Biology from Columbia University. He has experience with multiple computer languages, including Python, R, and SQL. He has worked on many projects including scraping movie critic reviews from RottenTomatoes to make a movie recommendation system. Alex is passionate about animal behavior and finding innovative ways to use data science in the field of biology. About NYC Data Science AcademyNYC Data Science Academy provides award-winning accelerated 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 2000 students at this point! Join our Interactive Distance Learning bootcamp, and get ready for the next step in your data science career! (https://nycdatascience.com/data-science-bootcamp/)Classes start on August 16th! Apply by August 9th to get a 10% off your tuition and secure your seat!

Data Science with R: Data Analysis and Visualization

Sep 18th, 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.

Data Science with Python: Machine Learning

Sep 19th, 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.

Data Science with Python: Data Analysis and Visualization

Sep 19th, 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.

Introductory Python

Sep 20th, 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.

Big Data with Amazon Cloud, Hadoop/Spark and Docker

Oct 19th, 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.

Data Science with R: Data Analysis and Visualization

Nov 13th, 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.

Data Science with Python: Machine Learning

Nov 14th, 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.

Data Science with Python: Data Analysis and Visualization

Nov 14th, 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.

Introductory Python

Nov 15th, 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.

August

2021

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NYC Data Science Academy

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.

NYC Data Science Academy is licensed by New York State Education Department.

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