Learn to program statistical applications and Monte Carlo simulations with numerous "real-life" cases and R software.
Master key concepts and practical skills through structured learning modules. By completing this curriculum, you'll gain valuable expertise applicable to real-world scenarios.
Use R software to program probabilistic simulations, often called Monte Carlo simulations.
Use R software to program mathematical simulations and to create novel mathematical simulation functions.
Use existing R functions and understand how to write their own R functions to perform simulated inference estimates, including likelihoods and confidence intervals, and to model other cases of stochastic simulation.
Be able to generate different different families (and moments) of both discrete and continuous random variables.
Be able to simulate parameter estimation, Monte-Carlo Integration of both continuous and discrete functions, and variance reduction techniques.
This comprehensive R Programming for Simulation and Monte Carlo Methods curriculum is designed to take you from foundational concepts to advanced implementation. Each module builds upon the previous, ensuring a structured learning path that maximizes knowledge retention and practical application.
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What you need before starting this R Programming for Simulation and Monte Carlo Methods course:
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Everything you need to know about this online course, from duration to certification
Course Instructor
Geoffrey Hubona, Ph.D.
Expert instructor with industry experience
Course Language
English
All materials in English
This online course offers comprehensive training with expert instruction, practical exercises, and a certificate of completion. Join thousands of students advancing their careers through quality online education.
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