{"product_id":"hands-on-introduction-to-r","title":"Hands-On Introduction to R","description":"\u003cdiv\u003e\u003cp\u003eThis introductory R programming course provides hands-on experience using R, a programming language for statistical computing, machine learning, and graphics. R is widely used in diverse disciplines to estimate, predict, and display results. Students will learn how to use R to clean, analyze, and graph data in this course.\u003c\/p\u003e\u003c\/div\u003e\u003cdiv\u003e\n\u003ch3\u003eHands-On Introduction to R Benefits\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cp\u003ePerform computations in R\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eLoad data sets from various sources into R\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eTransform data sets in preparation for analysis\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eCreate tidy data using the Tidyverse packages\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eVisualize data with ggplot2\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eFit models to data\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eContinue learning and face new challenges with after-course one-on-one instructor coaching\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\u003cdiv\u003e\u003ch3\u003e\u003c\/h3\u003e\u003c\/div\u003e\u003cdiv\u003e\n\u003ch4\u003eImportant course information\u003c\/h4\u003e\n\u003cp\u003e\u003cb\u003ePrerequisites\u003c\/b\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eExperience with another procedural or object-oriented programming language, such as C, C++, Java, VB .NET, or SQL\u003c\/li\u003e\n\u003cli\u003eFamiliarity with concepts, such as variables, loops, and branches with some experience using a text editor to edit program code\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cb\u003eExam Information\u003c\/b\u003e\u003c\/p\u003e\n\u003cp\u003eOptional Learning Tree exam available at the end of class\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e\n\u003ch4\u003eChapter 1: Introduction to R\u003c\/h4\u003e\n\u003cul\u003e\n\u003cli\u003eIntroduction to S, S-PLUS, and R\u003c\/li\u003e\n\u003cli\u003eDesign of R\u003c\/li\u003e\n\u003cli\u003eAdvantages of R\u003c\/li\u003e\n\u003cli\u003eLimitations of R\u003c\/li\u003e\n\u003cli\u003eThe R GUI\u003c\/li\u003e\n\u003cli\u003eThe R GUI\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eHands-On Exercise 1.1\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eThe RStudio Interface\u003c\/li\u003e\n\u003cli\u003eThe RStudio Interface\u003c\/li\u003e\n\u003cli\u003eRStudio Demo\u003c\/li\u003e\n\u003cli\u003eSetting Up a Custom CRAN Mirror\u003c\/li\u003e\n\u003cli\u003eChanging RStudio Options\u003c\/li\u003e\n\u003cli\u003eNaming Conventions, R Commands and Variables\u003c\/li\u003e\n\u003cli\u003eBasic Data Types\u003c\/li\u003e\n\u003cli\u003eCreating and Removing Variables\u003c\/li\u003e\n\u003cli\u003eNumbers and Character Types\u003c\/li\u003e\n\u003cli\u003eFunctions and Packages\u003c\/li\u003e\n\u003cli\u003eCommon Mathematical Functions\u003c\/li\u003e\n\u003cli\u003eCommon Statistical Functions\u003c\/li\u003e\n\u003cli\u003eCommon Probability Functions\u003c\/li\u003e\n\u003cli\u003eThe tidyverse Family of Packages\u003c\/li\u003e\n\u003cli\u003eInstalling tidyverse\u003c\/li\u003e\n\u003cli\u003eCharacter Processing Functions in the stringr Package\u003c\/li\u003e\n\u003cli\u003eComplex Character Manipulation Functions\u003c\/li\u003e\n\u003cli\u003eComplex Character Manipulation Functions II\u003c\/li\u003e\n\u003cli\u003eComplex Character Manipulation Functions III\u003c\/li\u003e\n\u003cli\u003eMiscellaneous Functions\u003c\/li\u003e\n\u003cli\u003eThe Pipe Operator\u003c\/li\u003e\n\u003cli\u003ePipe Operator Example\u003c\/li\u003e\n\u003cli\u003ePerforming Calculations\u003c\/li\u003e\n\u003cli\u003eExecuting Code in R Script File\u003c\/li\u003e\n\u003cli\u003eExecuting Code in R Script File\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eHands-On Exercise 1.1\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eIntroducing the Tidyverse\u003c\/li\u003e\n\u003cli\u003eData Input\u003c\/li\u003e\n\u003cli\u003eReading From a File\u003c\/li\u003e\n\u003cli\u003eReading and Displaying a File\u003c\/li\u003e\n\u003cli\u003eStructure of the Data\u003c\/li\u003e\n\u003cli\u003eReading and Writing to Excel File\u003c\/li\u003e\n\u003cli\u003eReading From a Database Using the RODBC Package\u003c\/li\u003e\n\u003cli\u003eReading From a Database Using the dbplyr Package\u003c\/li\u003e\n\u003cli\u003eSaving Data From R to Disk\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eHands-On Exercise 1.2\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e\n\u003ch4\u003eChapter 2: Aggregate Data Types and Computation\u003c\/h4\u003e\n\u003cul\u003e\n\u003cli\u003eData Structures\u003c\/li\u003e\n\u003cli\u003eNumeric Vectors\u003c\/li\u003e\n\u003cli\u003eVector Arithmetic\u003c\/li\u003e\n\u003cli\u003eVector Arithmetic\u003c\/li\u003e\n\u003cli\u003eGenerating Sequences\u003c\/li\u003e\n\u003cli\u003eRepeating with the rep() function\u003c\/li\u003e\n\u003cli\u003eLogical Vectors\u003c\/li\u003e\n\u003cli\u003eBoolean Operations\u003c\/li\u003e\n\u003cli\u003eMissing Values\u003c\/li\u003e\n\u003cli\u003eCharacter Vectors\u003c\/li\u003e\n\u003cli\u003eThe paste() function\u003c\/li\u003e\n\u003cli\u003eSelecting and Modifying Elements of a Vector\u003c\/li\u003e\n\u003cli\u003eSelecting and Modifying Elements of a Vector\u003c\/li\u003e\n\u003cli\u003eSelecting and Modifying Elements of a Vector\u003c\/li\u003e\n\u003cli\u003eGetting Information about R Objects\u003c\/li\u003e\n\u003cli\u003eExamining a Vector\u003c\/li\u003e\n\u003cli\u003eMixing Types in a Vector\u003c\/li\u003e\n\u003cli\u003eFactor Types\u003c\/li\u003e\n\u003cli\u003eFactor Types\u003c\/li\u003e\n\u003cli\u003eConceptual Framework for Factors\u003c\/li\u003e\n\u003cli\u003eFactors for Numerical Data\u003c\/li\u003e\n\u003cli\u003eThe forcats Package\u003c\/li\u003e\n\u003cli\u003eUsing fct_infreq()\u003c\/li\u003e\n\u003cli\u003eUsing fct_lump()\u003c\/li\u003e\n\u003cli\u003eLists\u003c\/li\u003e\n\u003cli\u003eNaming List Elements\u003c\/li\u003e\n\u003cli\u003eApply Functions to Lists\u003c\/li\u003e\n\u003cli\u003eData Frames\u003c\/li\u003e\n\u003cli\u003eThe Tibble\u003c\/li\u003e\n\u003cli\u003eCreating a Tibble From Vectors\u003c\/li\u003e\n\u003cli\u003eColumn Names That Are Non-syntactic\u003c\/li\u003e\n\u003cli\u003eCreating a Tibble Using tribble()\u003c\/li\u003e\n\u003cli\u003eTibbles in Action\u003c\/li\u003e\n\u003cli\u003eMatrices\u003c\/li\u003e\n\u003cli\u003eCreating Matrices\u003c\/li\u003e\n\u003cli\u003eAccessing Elements of a Matrix\u003c\/li\u003e\n\u003cli\u003eMatrix Computations\u003c\/li\u003e\n\u003cli\u003eTranspose and Matrix Multiplication\u003c\/li\u003e\n\u003cli\u003eQuerying a Data Set\u003c\/li\u003e\n\u003cli\u003eVariable Exclusion I\u003c\/li\u003e\n\u003cli\u003eVariable Exclusion II\u003c\/li\u003e\n\u003cli\u003eVariable Exclusion III\u003c\/li\u003e\n\u003cli\u003eQuerying Columns From a Tibble\u003c\/li\u003e\n\u003cli\u003eQuerying Rows From a Tibble\u003c\/li\u003e\n\u003cli\u003eExploratory Data Analysis\u003c\/li\u003e\n\u003cli\u003eThe summarize() Function of dplyr\u003c\/li\u003e\n\u003cli\u003eWorking With summarize()\u003c\/li\u003e\n\u003cli\u003eUsing filter()\u003c\/li\u003e\n\u003cli\u003esummary() Function\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eHands-On Exercise 2.1\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eAdvanced Summary Options\u003c\/li\u003e\n\u003cli\u003eAggregate Examples I\u003c\/li\u003e\n\u003cli\u003eAggregate Examples II\u003c\/li\u003e\n\u003cli\u003eAggregate Examples III\u003c\/li\u003e\n\u003cli\u003eAggregate Examples IV\u003c\/li\u003e\n\u003cli\u003eData Preparation: Data Frame Manipulation—bind_rows()\u003c\/li\u003e\n\u003cli\u003eData Preparation: Data Frame Manipulation—bind_cols()\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eHands-On Exercise 2.2\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e\n\u003ch4\u003eChapter 3: Data Transformation\u003c\/h4\u003e\n\u003cul\u003e\n\u003cli\u003eCleaning and Transforming the Data\u003c\/li\u003e\n\u003cli\u003eCentering and Rescaling\u003c\/li\u003e\n\u003cli\u003eCentering and Rescaling II\u003c\/li\u003e\n\u003cli\u003eNormalizing\u003c\/li\u003e\n\u003cli\u003eMissing Values\u003c\/li\u003e\n\u003cli\u003eMissing Values\u003c\/li\u003e\n\u003cli\u003eDropping Rows with Missing Entries\u003c\/li\u003e\n\u003cli\u003eImputing Missing Values\u003c\/li\u003e\n\u003cli\u003eBinning\u003c\/li\u003e\n\u003cli\u003eAdditional Recoding Options\u003c\/li\u003e\n\u003cli\u003eMultilevel Recoding\u003c\/li\u003e\n\u003cli\u003eThe Function cut() in Action\u003c\/li\u003e\n\u003cli\u003eGeneral Approach for Multilevel Variable Recoding I\u003c\/li\u003e\n\u003cli\u003eGeneral Approach for Multilevel Variable Recoding II\u003c\/li\u003e\n\u003cli\u003eChecking for Duplicates and Formatting Dates\u003c\/li\u003e\n\u003cli\u003eReordering a Data Set\u003c\/li\u003e\n\u003cli\u003eReordering Examples I\u003c\/li\u003e\n\u003cli\u003eReordering Examples II\u003c\/li\u003e\n\u003cli\u003eReordering Examples III\u003c\/li\u003e\n\u003cli\u003eSorting, Ranking, and Ordering Data\u003c\/li\u003e\n\u003cli\u003eJoining Datasets\u003c\/li\u003e\n\u003cli\u003eInner Joins\u003c\/li\u003e\n\u003cli\u003eLeft Joins\u003c\/li\u003e\n\u003cli\u003eRight Joins\u003c\/li\u003e\n\u003cli\u003eGetting a Subset of Data\u003c\/li\u003e\n\u003cli\u003eAnother Example of Subset Function\u003c\/li\u003e\n\u003cli\u003eSampling\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eHands-On Exercise 3.1\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e\n\u003ch4\u003eChapter 4: Visualizing Data\u003c\/h4\u003e\n\u003cul\u003e\n\u003cli\u003eBase Graphics\u003c\/li\u003e\n\u003cli\u003eExploring Data Visualization\u003c\/li\u003e\n\u003cli\u003eExplore the options in qplot()\u003c\/li\u003e\n\u003cli\u003eWeather Data Set\u003c\/li\u003e\n\u003cli\u003eSimple Graph Plotting\u003c\/li\u003e\n\u003cli\u003eGraph Coloring With Attributes\u003c\/li\u003e\n\u003cli\u003eShape and Size to Graph\u003c\/li\u003e\n\u003cli\u003eBox Plots and Violin Plots\u003c\/li\u003e\n\u003cli\u003eHistogram\u003c\/li\u003e\n\u003cli\u003eDensity Plots\u003c\/li\u003e\n\u003cli\u003eGraph Labeling\u003c\/li\u003e\n\u003cli\u003ePie Charts\u003c\/li\u003e\n\u003cli\u003eCo-relationship in Data\u003c\/li\u003e\n\u003cli\u003ePlotting Correlation of Three Variables\u003c\/li\u003e\n\u003cli\u003eCorrelations for All the Numeric Variables\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eHands-On Exercise 4.1\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e\n\u003ch4\u003eChapter 5: Fitting Models to Data\u003c\/h4\u003e\n\u003cul\u003e\n\u003cli\u003etidymodel\u003c\/li\u003e\n\u003cli\u003eIntroduction to Regression\u003c\/li\u003e\n\u003cli\u003eWhen Is Regression Used?\u003c\/li\u003e\n\u003cli\u003eSample Use Cases\u003c\/li\u003e\n\u003cli\u003eDependent and Independent Variables\u003c\/li\u003e\n\u003cli\u003eCalculating Regression Equation\u003c\/li\u003e\n\u003cli\u003eMultiple Linear Regression\u003c\/li\u003e\n\u003cli\u003eEquation for Multiple Linear Regression\u003c\/li\u003e\n\u003cli\u003eR’s Built-In Function for Linear Regression\u003c\/li\u003e\n\u003cli\u003eAdditional Linear Modeling functions\u003c\/li\u003e\n\u003cli\u003eExample: Predicting Prestige\u003c\/li\u003e\n\u003cli\u003eThe Data Set\u003c\/li\u003e\n\u003cli\u003eExploring and Preparing the Data\u003c\/li\u003e\n\u003cli\u003eCreating a Training and a Testing Data Set\u003c\/li\u003e\n\u003cli\u003eThe Model\u003c\/li\u003e\n\u003cli\u003eFitting a Linear Model to the Data\u003c\/li\u003e\n\u003cli\u003eMaking Predictions From the Model\u003c\/li\u003e\n\u003cli\u003eFitting the Model With Parsnip\u003c\/li\u003e\n\u003cli\u003eInterpreting the Model\u003c\/li\u003e\n\u003cli\u003eInterpreting the Model\u003c\/li\u003e\n\u003cli\u003eEvaluating the Model\u003c\/li\u003e\n\u003cli\u003eEvaluating the Model\u003c\/li\u003e\n\u003cli\u003eEvaluating the Model\u003c\/li\u003e\n\u003cli\u003eTidying Up the Output\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eHands-On Exercise 5.1\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/div\u003e","brand":"Learning Tree","offers":[{"title":"268A52US \/ 2026-08-19T09:00:00 \/ Herndon, VA","offer_id":47534217330907,"sku":"US-1268-IL","price":2228.0,"currency_code":"USD","in_stock":true},{"title":"26BA93US \/ 2026-11-18T09:00:00 \/ Herndon, 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