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4 - 6 weeks
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October
2021
From Music PhD at Stanford to Data Scientist in Europe
Oct 27th, 2021
3:00PM EDT
NYC Data Science Academy Alumnus, Alex Sigman, will share his experience changing his career to data science after graduating with a PhD in Music CompositionAbout this eventAlthough becoming qualified as a data scientist requires a set of core technical competencies, the educational and professional backgrounds of individuals entering the field have become increasingly diverse in recent years. This talk will address ways in which someone with a less typical profile can harness their knowledge and experience and build a career in data science. On Wednesday, Oct 13th at 3PM EST, NYC Data Science Academy Alumnus, Alex Signman will cover Topics such as: 1. Navigating the transition between academia and industry2. Finding the best-fit working environment and role3. Relevant professional development resources4. The day-to-day challenges encountered at an AI music technology startup This talk is non-technical. Some basic math, data science, and programming concepts will be referenced, but it's not critical for following the discussion. REGISTER NOW to receive the webinar link Check out our Courses: https://nycdatascience.com/data-science-bootcamp/ Agenda 3:00 pm - 3:05 pm Overview of the Academy 3:05 pm - 3:50 pm Hands-on workshop given by Dean 3:50 pm - 4:00 pm Q&A and more mingling About Alex Sigman With a unique background in music composition + technology, cognitive science, and data science, Sigman has been active internationally as an interdisciplinary composer, performer, researcher, software engineer, and educator. He earned undergraduate degrees in Music and Cognitive Science at Rice University and his doctorate in Music Composition at Stanford. Sigman was a Data Science Fellow at the NYC Data Science Academy in 2019. Sigman has published and presented extensively on a broad range of research topics, including music information retrieval, innovative auditory warning design, technical and aesthetic aspects of robot opera, and approaches to creative audiovisual media integration. Throughout his career, he has held diverse leadership roles, including being a founding faculty member and Music program director of the International College of Liberal Arts (iCLA) of Yamanashi Gakuin University in Kofu, Japan. Sigman is currently a research and development engineer at AIVA Technologies, an AI music technology startup based in Luxembourg. 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 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 Data Science Bootcamp, and get ready for the next step in your data science career! (https://nycdatascience.com/data-science-bootcamp/) Classes start soon! Apply NOW and secure your seat!
Register Now
October
2021
How Strong is Your Machine Learning Model?
Nov 3rd, 2021
6:00PM EDT
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 November 3rd, 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. Here’s what to expect from the session: We run regular events to showcase our candidate's projects and welcome new project collaborations! NYC Data Science Academy collaborates with many industries, academies and offers open consulting opportunities. Welcome to connect with us for your project need! 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 flagship project, Data Science Bootcamp(https://nycdatascience.com/data-science-bootcamp/), has been recognized as the Best Data Science Bootcamp for 5 years in a row by Switchup.org. We offer it in remote live/distance learning in full-time and part-time fashion to best suit everyone's need. 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! Pin Our Upcoming Events On Your Calendar! Join our next Data Science Bootcamp and Data Analytics Bootcamp, and get ready for the next step in your data science career! (https://nycdatascience.com/data-science-bootcamp/)Classes start on January 3rd, 2022! Talk to our advisors now to secure your seat!
Register Now
Data Science with R: Data Analysis and Visualization
Nov 12th, 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
Nov 13th, 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
Nov 13th, 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
Nov 14th, 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
2021
Data Science with R: Data Analysis and Visualization
Jan 7th, 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
Data Science with Python: Machine Learning
Jan 8th, 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
Data Science with Python: Data Analysis and Visualization
Jan 8th, 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
Introductory Python
Jan 9th, 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
Big Data with Amazon Cloud, Hadoop/Spark and Docker
Jan 10th, 2022
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
2021
Data Science with R: Data Analysis and Visualization
Mar 4th, 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
Data Science with Python: Machine Learning
Mar 5th, 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
Data Science with Python: Data Analysis and Visualization
Mar 5th, 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
Introductory Python
Mar 6th, 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
Big Data with Amazon Cloud, Hadoop/Spark and Docker
Mar 21st, 2022
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
View All Events
Browse All Courses
Browse All Bundles
From Music PhD at Stanford to Data Scientist in Europe
Oct 27th, 2021
3:00PM EDT
NYC Data Science Academy Alumnus, Alex Sigman, will share his experience changing his career to data science after graduating with a PhD in Music CompositionAbout this eventAlthough becoming qualified as a data scientist requires a set of core technical competencies, the educational and professional backgrounds of individuals entering the field have become increasingly diverse in recent years. This talk will address ways in which someone with a less typical profile can harness their knowledge and experience and build a career in data science. On Wednesday, Oct 13th at 3PM EST, NYC Data Science Academy Alumnus, Alex Signman will cover Topics such as: 1. Navigating the transition between academia and industry2. Finding the best-fit working environment and role3. Relevant professional development resources4. The day-to-day challenges encountered at an AI music technology startup This talk is non-technical. Some basic math, data science, and programming concepts will be referenced, but it's not critical for following the discussion. REGISTER NOW to receive the webinar link Check out our Courses: https://nycdatascience.com/data-science-bootcamp/ Agenda 3:00 pm - 3:05 pm Overview of the Academy 3:05 pm - 3:50 pm Hands-on workshop given by Dean 3:50 pm - 4:00 pm Q&A and more mingling About Alex Sigman With a unique background in music composition + technology, cognitive science, and data science, Sigman has been active internationally as an interdisciplinary composer, performer, researcher, software engineer, and educator. He earned undergraduate degrees in Music and Cognitive Science at Rice University and his doctorate in Music Composition at Stanford. Sigman was a Data Science Fellow at the NYC Data Science Academy in 2019. Sigman has published and presented extensively on a broad range of research topics, including music information retrieval, innovative auditory warning design, technical and aesthetic aspects of robot opera, and approaches to creative audiovisual media integration. Throughout his career, he has held diverse leadership roles, including being a founding faculty member and Music program director of the International College of Liberal Arts (iCLA) of Yamanashi Gakuin University in Kofu, Japan. Sigman is currently a research and development engineer at AIVA Technologies, an AI music technology startup based in Luxembourg. 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 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 Data Science Bootcamp, and get ready for the next step in your data science career! (https://nycdatascience.com/data-science-bootcamp/) Classes start soon! Apply NOW and secure your seat!
Register Now
How Strong is Your Machine Learning Model?
Nov 3rd, 2021
6:00PM EDT
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 November 3rd, 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. Here’s what to expect from the session: We run regular events to showcase our candidate's projects and welcome new project collaborations! NYC Data Science Academy collaborates with many industries, academies and offers open consulting opportunities. Welcome to connect with us for your project need! 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 flagship project, Data Science Bootcamp(https://nycdatascience.com/data-science-bootcamp/), has been recognized as the Best Data Science Bootcamp for 5 years in a row by Switchup.org. We offer it in remote live/distance learning in full-time and part-time fashion to best suit everyone's need. 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! Pin Our Upcoming Events On Your Calendar! Join our next Data Science Bootcamp and Data Analytics Bootcamp, and get ready for the next step in your data science career! (https://nycdatascience.com/data-science-bootcamp/)Classes start on January 3rd, 2022! Talk to our advisors now to secure your seat!
Register Now
Data Science with R: Data Analysis and Visualization
Nov 12th, 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
Nov 13th, 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
Nov 13th, 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
Nov 14th, 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
Data Science with R: Data Analysis and Visualization
Jan 7th, 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
Data Science with Python: Machine Learning
Jan 8th, 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
Data Science with Python: Data Analysis and Visualization
Jan 8th, 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
Introductory Python
Jan 9th, 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
Big Data with Amazon Cloud, Hadoop/Spark and Docker
Jan 10th, 2022
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: Data Analysis and Visualization
Mar 4th, 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
Data Science with Python: Machine Learning
Mar 5th, 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
Data Science with Python: Data Analysis and Visualization
Mar 5th, 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
Introductory Python
Mar 6th, 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
Big Data with Amazon Cloud, Hadoop/Spark and Docker
Mar 21st, 2022
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
2021
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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.

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