Geoffrey Hubona coupons

95% off The Comprehensive Programming in R Course (Coupon)

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The Comprehensive Programming in R Course - Udemy Coupon

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Coupon & course info

Course Name: The Comprehensive Programming in R Course

Subtitle: How to design and develop efficient general-purpose R applications for diverse tasks and domains.

Instructor: Taught by Geoffrey Hubona, Professor of Information Systems

Category: Business

Subcategory: Data & Analytics

Provided by: Udemy

Price: $149 (before discount)

Free coupon code: See above (no charge for coupon)

Review info & popularity

As of March 9, 2016…

Students: 1215 students enrolled

Ratings: 110 reviews

Rank: ranked #126 in Udemy Business Courses

Brief course description

The Comprehensive Programming in R Course is actually a combination of two R programming courses that together comprise a gentle, yet thorough introduction to the practice of general-purpose application development in the R environment. The original first course (Sections 1-8) consists of approximately 12 hours of video content and provides extensive example-based instruction on details for programming R data structures. The original second course (Sections 9-14), an additional 12 hours of video content, provides a comprehensive overview on the most important conceptual topics for writing efficient programs to execute in the unique R environment. Participants in this comprehensive course may already be skilled programmers (in other languages) or they may be complete novices to R programming or to programming in general, but their common objective is to write R applications for diverse domains and purposes. No statistical knowledge is necessary. These two courses, combined into one course here on Udemy, together comprise a thorough introduction to using the R environment and language for general-purpose application development.

The Comprehensive Programming in R Course (Sections 1-8) presents an detailed, in-depth overview of the R programming environment and of the nature and programming implications of basic R objects in the form of vectors, matrices, dataframes and lists. The Comprehensive Programming in R Course (Sections 9-14) then applies this understanding of these basic R object structures to instruct with respect to programming the structures; performing mathematical modeling and simulations; the specifics of object-oriented programming in R; input and output; string manipulation; and performance enhancement for computation speed and to optimize computer memory resources.

…

(Read more about this course on the official course page.)

Geoffrey Hubona bio

Dr. Geoffrey Hubona has been a full-time faculty member at 3 major state universities in the Eastern United States for 20 years, teaching dozens of different statistics, business information systems, and computer science courses to undergraduate, master’s and PhD students. He earned a PhD in Information Systems and Computer Science (1993) from the University of South Florida in Tampa, FL (1993); an MA in Economics (1990) from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He held full-time faculty positions at the University of Maryland Baltimore County (1993-1996), Virginia Commonwealth University (1996-2001), and Georgia State University (2001-2010). He is the founder of the Georgia R School (2010), a non-profit online educational institution that teaches research methods and quantitative analysis techniques such as linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is recognized as an expert of the analytical, open-source R software suite and of various path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

(Learn more about this instructor on the official course page.)

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Final details for this Udemy course

Languages: English

Skill level: All Levels

Lectures: 120 lessons

Duration: 25 Hours of video

What you get: Acquire the skills needed to successfully develop general-purpose programming applications in the R environment

Target audience: Anyone interested in writing computer applications that execute in the R environment.

Requirements: Students will need to install the no-cost R console and the no-cost RStudio application (instructions are provided).

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons

95% off Data Mining with R: Go from Beginner to Advanced! (Coupon)

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Data Mining with R: Go from Beginner to Advanced! - Udemy Coupon

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Coupon & course info

Course Name: Data Mining with R: Go from Beginner to Advanced!

Subtitle: Learn to use R software for data analysis, visualization, and to perform dozens of popular data mining techniques.

Instructor: Taught by Geoffrey Hubona, Professor of Information Systems

Category: Business

Subcategory: Data & Analytics

Provided by: Udemy

Price: $99 (before discount)

Free coupon code: See above (no charge for coupon)

Review info & popularity

As of March 9, 2016…

Students: 1693 students enrolled

Ratings: 18 reviews

Rank: ranked #154 in Udemy Business Courses

Brief course description

This is a “hands-on” business analytics, or data analytics course teaching how to use the popular, no-cost R software to perform dozens of data mining tasks using real data and data mining cases. It teaches critical data analysis, data mining, and predictive analytics skills, including data exploration, data visualization, and data mining skills using one of the most popular business analytics software suites used in industry and government today. The course is structured as a series of dozens of demonstrations of how to perform classification and predictive data mining tasks, including building classification trees, building and training decision trees, using random forests, linear modeling, regression, generalized linear modeling, logistic regression, and many different cluster analysis techniques. The course also trains and instructs on “best practices” for using R software, teaching and demonstrating how to install R software and RStudio, the characteristics of the basic data types and structures in R, as well as how to input data into an R session from the keyboard, from user prompts, or by importing files stored on a computer’s hard drive. All software, slides, data, and R scripts that are performed in the dozens of case-based demonstration video lessons are included in the course materials so students can “take them home” and apply them to their own unique data analysis and mining cases. There are also “hands-on” exercises to perform in each course section to reinforce the learning process. The target audience for the course includes undergraduate and graduate students seeking to acquire employable data analytics skills, as well as practicing predictive analytics professionals seeking to expand their repertoire of data analysis and data mining knowledge and capabilities.

…

…

(Read more about this course on the official course page.)

Geoffrey Hubona bio

Dr. Geoffrey Hubona has been a full-time faculty member at 3 major state universities in the Eastern United States for 20 years, teaching dozens of different statistics, business information systems, and computer science courses to undergraduate, master’s and PhD students. He earned a PhD in Information Systems and Computer Science (1993) from the University of South Florida in Tampa, FL (1993); an MA in Economics (1990) from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He held full-time faculty positions at the University of Maryland Baltimore County (1993-1996), Virginia Commonwealth University (1996-2001), and Georgia State University (2001-2010). He is the founder of the Georgia R School (2010), a non-profit online educational institution that teaches research methods and quantitative analysis techniques such as linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is recognized as an expert of the analytical, open-source R software suite and of various path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

(Learn more about this instructor on the official course page.)

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Final details for this Udemy course

Languages: English

Skill level: All Levels

Lectures: 80 lessons

Duration: 12 Hours of video

What you get: Use R software for data import and export, data exploration and visualization, and for data analysis tasks, including performing a comprehensive set of data mining operations.

Target audience: Anyone who wants to learn more about performing data analysis using a variety of popular, contemporary data mining techniques.

Requirements: Download and install no-cost R software (complete, easy-to-follow instructions are provided).

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons

95% off Applied Multivariate Analysis with R (Coupon)

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Applied Multivariate Analysis with R - Udemy Coupon

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Coupon & course info

Course Name: Applied Multivariate Analysis with R

Subtitle: Learn to use R software to conduct PCAs, MDSs, cluster analyses, EFAs and to estimate SEM models.

Instructor: Taught by Geoffrey Hubona, Professor of Information Systems

Category: Business

Subcategory: Data & Analytics

Provided by: Udemy

Price: $99 (before discount)

Free coupon code: See above (no charge for coupon)

Review info & popularity

As of March 9, 2016…

Students: 1259 students enrolled

Ratings: 6 reviews

Rank: ranked #252 in Udemy Business Courses

Brief course description

Applied Multivariate Analysis (MVA) with R is a practical, conceptual and applied “hands-on” course that teaches students how to perform various specific MVA tasks using real data sets and R software. It is an excellent and practical background course for anyone engaged with educational or professional tasks and responsibilities in the fields of data mining or predictive analytics, statistical or quantitative modeling (including linear, GLM and/or non-linear modeling, covariance-based Structural Equation Modeling (SEM) specification and estimation, and/or variance-based PLS Path Model specification and estimation. Students learn all about the nature of multivariate data and multivariate analysis. Students specifically learn how to create and estimate: covariance and correlation matrices; Principal Components Analyses (PCA); Multidimensional Scaling (MDS); Cluster Analysis; Exploratory Factor Analyses (EFA); and SEM model estimation. The course also teaches how to create dozens of different dazzling 2D and 3D multivariate data visualizations using R software. All software, R scripts, datasets and slides used in all lectures are provided in the course materials. The course is structured as a series of seven sections, each addressing a specific MVA topic and each section culminating with one or more “hands-on” exercises for the students to complete before proceeding to reinforce learning the presented MVA concepts and skills. The course is an excellent vehicle to acquire “real-world” predictive analytics skills that are in high demand today in the workplace. The course is also a fertile source of relevant skills and knowledge for graduate students and faculty who are required to analyze and interpret research data.

…

…

(Read more about this course on the official course page.)

Geoffrey Hubona bio

Dr. Geoffrey Hubona has been a full-time faculty member at 3 major state universities in the Eastern United States for 20 years, teaching dozens of different statistics, business information systems, and computer science courses to undergraduate, master’s and PhD students. He earned a PhD in Information Systems and Computer Science (1993) from the University of South Florida in Tampa, FL (1993); an MA in Economics (1990) from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He held full-time faculty positions at the University of Maryland Baltimore County (1993-1996), Virginia Commonwealth University (1996-2001), and Georgia State University (2001-2010). He is the founder of the Georgia R School (2010), a non-profit online educational institution that teaches research methods and quantitative analysis techniques such as linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is recognized as an expert of the analytical, open-source R software suite and of various path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

(Learn more about this instructor on the official course page.)

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Final details for this Udemy course

Languages: English

Skill level: All Levels

Lectures: 75 lessons

Duration: 12 Hours of video

What you get: Conceptualize and apply multivariate skills and “hands-on” techniques using R software in analyzing real data.

Target audience: Anyone interested in using multivariate analysis technques as a basis for data mining, statistical modeling, and structural equation modeling (SEM) estimation.

Requirements: No specific knowledge or skills are required.

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons

95% off Comprehensive Linear Modeling with R (Coupon)

Online Courses Pro
Attention: This post may contain affiliate links, meaning when you click the links and make a purchase, we receive a commission at no extra cost to you. Thanks!

Comprehensive Linear Modeling with R - Udemy Coupon

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Bonus: download a free guide that reveals 11 tricks for getting the biggest discounts on Udemy courses, including this course.

Coupon & course info

Course Name: Comprehensive Linear Modeling with R

Subtitle: Learn to model with R: ANOVA, regression, GLMs, survival analysis, GAMs, mixed-effects, split-plot and nested designs

Instructor: Taught by Geoffrey Hubona, Professor of Information Systems

Category: Business

Subcategory: Data & Analytics

Provided by: Udemy

Price: $99 (before discount)

Free coupon code: See above (no charge for coupon)

Review info & popularity

As of March 9, 2016…

Students: 39390 students enrolled

Ratings: 2 reviews

Rank: ranked #439 in Udemy Business Courses

Brief course description

Comprehensive Linear Modeling with R provides a wide overview of numerous contemporary linear and non-linear modeling approaches for the analysis of research data. These include basic, conditional and simultaneous inference techniques; analysis of variance (ANOVA); linear regression; survival analysis; generalized linear models (GLMs); parametric and non-parametric smoothers and generalized additive models (GAMs); longitudinal and mixed-effects, split-plot and other nested model designs. The course showcases the use of R Commander in performing these tasks. R Commander is a popular GUI-based “front-end” to the broad range of embedded statistical functionality in R software. R Commander is an ‘SPSS-like’ GUI that enables the implementation of a large variety of statistical and graphical techniques using both menus and scripts. Please note that the R Commander GUI is written in the RGtk2 R-specific visual language (based on GTK+) which is known to have problems running on a Mac computer.

The course progresses through dozens of statistical techniques by first explaining the concepts and then demonstrating the use of each with concrete examples based on actual studies and research data. Beginning with a quick overview of different graphical plotting techniques, the course then reviews basic approaches to establish inference and conditional inference, followed by a review of analysis of variance (ANOVA). The course then progresses through linear regression and a section on validating linear models. Then generalized linear modeling (GLM) is explained and demonstrated with numerous examples. Also included are sections explaining and demonstrating linear and non-linear models for survival analysis, smoothers and generalized additive models (GAMs), longitudinal models with and without generalized estimating equations (GEE), mixed-effects, split-plot, and nested designs. Also included are detailed examples and explanations of validating linear models using various graphical displays, as well as comparing alternative models to choose the ‘best’ model. The course concludes with a section on the special considerations and techniques for establishing simultaneous inference in the linear modeling domain.

The rather long course aims for complete coverage of linear (and some non-linear) modeling approaches using R and is suitable for beginning, intermediate and advanced R users who seek to refine these skills. These candidates would include graduate students and/or quantitative and/or data-analytic professionals who perform linear (and non-linear) modeling as part of their professional duties.

(Read more about this course on the official course page.)

Geoffrey Hubona bio

Dr. Geoffrey Hubona has been a full-time faculty member at 3 major state universities in the Eastern United States for 20 years, teaching dozens of different statistics, business information systems, and computer science courses to undergraduate, master’s and PhD students. He earned a PhD in Information Systems and Computer Science (1993) from the University of South Florida in Tampa, FL (1993); an MA in Economics (1990) from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He held full-time faculty positions at the University of Maryland Baltimore County (1993-1996), Virginia Commonwealth University (1996-2001), and Georgia State University (2001-2010). He is the founder of the Georgia R School (2010), a non-profit online educational institution that teaches research methods and quantitative analysis techniques such as linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is recognized as an expert of the analytical, open-source R software suite and of various path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

(Learn more about this instructor on the official course page.)

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Final details for this Udemy course

Languages: English

Skill level: All Levels

Lectures: 104 lessons

Duration: 14.5 Hours of video

What you get: Understand, use and apply, estimate, interpret and validate: ANOVA; regression; survival analysis; GLMs; smoothers and GAMs; longitudinal, mixed-effects, split-plot and nested model designs using their own data and R software.

Target audience: This course is aimed at graduate students and working quantitative and data-analytic professionals who seek to acquire a wide range of linear (and non-linear) modeling skills using R.

Requirements: Students will need to install R and R Commander using the ample video and written instructions that are provided for doing so.

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons

95% off Multivariate Data Visualization with R (Coupon)

Online Courses Pro
Attention: This post may contain affiliate links, meaning when you click the links and make a purchase, we receive a commission at no extra cost to you. Thanks!

Multivariate Data Visualization with R - Udemy Coupon

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Bonus: download a free guide that reveals 11 tricks for getting the biggest discounts on Udemy courses, including this course.

Coupon & course info

Course Name: Multivariate Data Visualization with R

Subtitle: Course describes and demonstrates a creative approach for constructing and drawing grid-based multivariate graphs in R

Instructor: Taught by Geoffrey Hubona, Professor of Information Systems

Category: Business

Subcategory: Data & Analytics

Provided by: Udemy

Price: $49 (before discount)

Free coupon code: See above (no charge for coupon)

Review info & popularity

As of March 9, 2016…

Students: 1515011 students enrolled

Ratings: 4 reviews

Rank: ranked #522 in Udemy Business Courses

Brief course description

It is often both useful and revealing to create visualizations, plots and graphs of the multivariate data that is the subject of one’s research project. Often, both pre-analysis and post-analysis visualizations can help one understand “what is going on in the data” in a way that looking at numerical summaries of fitted model estimates cannot. The lattice package in R is uniquely designed to graphically depict relationships in multivariate data sets.

This course describes and demonstrates this creative approach for constructing and drawing grid-based multivariate graphic plots and figures using R. Lattice graphics are characterized as multi-variable (3, 4, 5 or more variables) plots that use conditioning and paneling. Consequently, it is a popular approach for, and a good fit to visually present the results of multi-variable statistical model fitting. The appearance of most of the plots, graphs and figures are determined by panel functions, rather than by the high-level graphics function calls themselves. Further, the user of lattice graphics has extensive and comprehensive control over many more of the details and features of the visual plots, far greater control that is afforded by the base graphics approach in R. The method is based on trellis graphics which were popularized in the S language developed by Bell Labs.

…

(Read more about this course on the official course page.)

Geoffrey Hubona bio

Dr. Geoffrey Hubona has been a full-time faculty member at 3 major state universities in the Eastern United States for 20 years, teaching dozens of different statistics, business information systems, and computer science courses to undergraduate, master’s and PhD students. He earned a PhD in Information Systems and Computer Science (1993) from the University of South Florida in Tampa, FL (1993); an MA in Economics (1990) from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He held full-time faculty positions at the University of Maryland Baltimore County (1993-1996), Virginia Commonwealth University (1996-2001), and Georgia State University (2001-2010). He is the founder of the Georgia R School (2010), a non-profit online educational institution that teaches research methods and quantitative analysis techniques such as linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is recognized as an expert of the analytical, open-source R software suite and of various path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

(Learn more about this instructor on the official course page.)

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Final details for this Udemy course

Languages: English

Skill level: All Levels

Lectures: 32 lessons

Duration: 7 Hours of video

What you get: Graphically depict visual 2D, 3D, 4D (and so on) relationships that exist in multivariate data sets.

Target audience: Anyone who uses R, or who wants to use R, for any sort of multivariate data analysis would benefit from taking this course.

Requirements: Students will need to install R and RStudio (instructions are provided in the course materials).

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons

95% off R Programming for Simulation and Monte Carlo Methods (Coupon)

Online Courses Pro
Attention: This post may contain affiliate links, meaning when you click the links and make a purchase, we receive a commission at no extra cost to you. Thanks!

R Programming for Simulation and Monte Carlo Methods - Udemy Coupon

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Bonus: download a free guide that reveals 11 tricks for getting the biggest discounts on Udemy courses, including this course.

Coupon & course info

Course Name: R Programming for Simulation and Monte Carlo Methods

Subtitle: Learn to program statistical applications and Monte Carlo simulations with numerous “real-life” cases and R software.

Instructor: Taught by Geoffrey Hubona, Professor of Information Systems

Category: Business

Subcategory: Data & Analytics

Provided by: Udemy

Price: $49 (before discount)

Free coupon code: See above (no charge for coupon)

Review info & popularity

As of March 9, 2016…

Students: 741 students enrolled

Ratings: 3 reviews

Rank: ranked #592 in Udemy Business Courses

Brief course description

R Programming for Simulation and Monte Carlo Methods focuses on using R software to program probabilistic simulations, often called Monte Carlo Simulations. Typical simplified “real-world” examples include simulating the probabilities of a baseball player having a ‘streak’ of twenty sequential season games with ‘hits-at-bat’ or estimating the likely total number of taxicabs in a strange city when one observes a certain sequence of numbered cabs pass a particular street corner over a 60 minute period. In addition to detailing half a dozen (sometimes amusing) ‘real-world’ extended example applications, the course also explains in detail how to use existing R functions, and how to write your own R functions, to perform simulated inference estimates, including likelihoods and confidence intervals, and other cases of stochastic simulation. Techniques to use R to generate different characteristics of various families of random variables are explained in detail. The course teaches skills to implement various approaches to simulate continuous and discrete random variable probability distribution functions, parameter estimation, Monte-Carlo Integration, and variance reduction techniques. The course partially utilizes the Comprehensive R Archive Network (CRAN) spuRs package to demonstrate how to structure and write programs to accomplish mathematical and probabilistic simulations using R statistical software.

…

…

(Read more about this course on the official course page.)

Geoffrey Hubona bio

Dr. Geoffrey Hubona has been a full-time faculty member at 3 major state universities in the Eastern United States for 20 years, teaching dozens of different statistics, business information systems, and computer science courses to undergraduate, master’s and PhD students. He earned a PhD in Information Systems and Computer Science (1993) from the University of South Florida in Tampa, FL (1993); an MA in Economics (1990) from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He held full-time faculty positions at the University of Maryland Baltimore County (1993-1996), Virginia Commonwealth University (1996-2001), and Georgia State University (2001-2010). He is the founder of the Georgia R School (2010), a non-profit online educational institution that teaches research methods and quantitative analysis techniques such as linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is recognized as an expert of the analytical, open-source R software suite and of various path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

(Learn more about this instructor on the official course page.)

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Final details for this Udemy course

Languages: English

Skill level: All Levels

Lectures: 107 lessons

Duration: 11.5 Hours of video

What you get: Use R software to program probabilistic simulations, often called Monte Carlo simulations.

Target audience: You do NOT need to be experienced with R software and you do NOT need to be an experienced programmer.

Requirements: Students will need to install the popular no-cost R Console and RStudio software (instructions provided).

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons