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R training lets you learn R programming language that is deployed for varied purposes like graphic representation, statistical analysis, and reporting. With this online R Programming for Data Science training, you will be able to get a clear understanding of the core concepts like importing data in various formats for statistical computing, data manipulation, Business Analytics, Machine Learning algorithms, and data visualization.
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Course Customization Options To request a customized training for this course, please contact us to arrange.
ARTIFICIAL INTELLIGENCE / MACHINE LEARNING / DEEP LEARNING
Machine learning is revolutionizing industries by enabling predictive analytics and automation. Our Machine Learning using Python with R course provides hands-on experience in building machine learning models, applying statistical techniques, and analyzing data. Participants will learn to implement regression algorithms, neural networks, and decision trees using Python and R. By the end of this course, you will be proficient in Machine Learning using Python with R, allowing you to extract valuable insights from data and drive business success.
DATA SCIENCE
Course Customization Options To request a customized training for this course, please contact us to arrange.
CLOUD COMPUTING
The webMethods Integration Cloud Workshop enables you to develop integration applications using the webMethods Integration Cloud as Platform-as-a-Service (IPaaS). You will learn how to integrate and orchestrate SaaS (Software as a Service) applications and on-premise enterprise integrations served by a webMethods Integration Server.
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Power BI is quickly gaining popularity among professionals in data science as a cloud-based service that helps them easily visualize and share insights from their organizations' data.
This course provides an application-oriented introduction to advanced statistical methods available in IBM SPSS Statistics. Students will review a variety of advanced statistical techniques and discuss situations in which each technique would be used, the assumptions made by each method, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for predicting variables, as well as methods to cluster variables and cases.
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Course Customization Options To request a customized training for this course, please contact us to arrange.