R for Data Analytics

Introduction to R Programming Statistical computing is employed within a diverse range of industries. In recent years, an open source project, R, has emerged as the preeminent statistical computing platform. With its unsurpassed library of freely available packages, R is capable of addressing almost every statistical inference problem. In this course, you will learn the most commonly-used (roughly 100) functions and operators from the R Base Package, which serves as the fundamental tools for accessing data from multiple sources, manipulating different types of R objects, performing...

Introduction to Statistics using R Statistics allows us to collect, analyze, and interpret data. The R programming language is one of the most widely-used tools for data analysis and statistical programming. Its easy to learn syntax, built-in statistical functions, and powerful graphing capabilities make it an ideal tool to learn and apply statistical concepts. In this class, you will master the most widely used statistical methods, while also learning to design efficient and informative studies, to perform statistical analyses using R, and to critique the statistical methods used in...

Communicate Complex Data Clearly with Advanced R Visualization and AI Tools In today’s data-driven economy, the ability to manage, transform, and visualize data is a mission-critical skill for data analysts, data scientists, and researchers. This advanced course in R programming equips learners with cutting-edge techniques for data wrangling — including data cleaning, reshaping, merging, and feature engineering — as well as advanced data visualization strategies to communicate complex information with clarity and impact. By integrating artificial intelligence–enhanced exercises, the course...

Introduction to R Programming Statistical computing is employed within a diverse range of industries. In recent years, an open source project, R, has emerged as the preeminent statistical computing platform. With its unsurpassed library of freely available packages, R is capable of addressing almost every statistical inference problem. In this course, you will learn the most commonly-used (roughly 100) functions and operators from the R Base Package, which serves as the fundamental tools for accessing data from multiple sources, manipulating different types of R objects, performing...

Introduction to Statistics using R Statistics allows us to collect, analyze, and interpret data. The R programming language is one of the most widely-used tools for data analysis and statistical programming. Its easy to learn syntax, built-in statistical functions, and powerful graphing capabilities make it an ideal tool to learn and apply statistical concepts. In this class, you will master the most widely used statistical methods, while also learning to design efficient and informative studies, to perform statistical analyses using R, and to critique the statistical methods used in...

Learn to Create Regulatory Compliance Deliverables for Pharmaceutical Industry: SDTMs, ADaMs, Tables, Lists and Graphs Participants will gain comprehensive knowledge on common R packages (Tidyverse, DPLYR and Piping) and the R programming language. Attendees will learn how to access, create and process R data frames in data management, reporting and analysis. In addition, this course shows best practices in how to select, filter, derive, append and join data frames using SQL type code. Ideal for the pharma industry, examples of both SDTM and ADaM datasets will be created, which are...

Showcase your R expertise with a real-world, AI-powered analytics project This R Analytics Capstone Project course integrates skills from the three required courses in the "R for Data Analytics" program, enabling students to create a professional portfolio project (e.g. Quarto book, R-Shiny interactive visualization, or similar) using AI assistance. Focusing on data collection, cleaning, analysis, and visualization from provided sources, this course prepares professionals, researchers, and students for real-world analytics challenges. Course Highlights: Introduction to Quarto Book Creation:...

Learn to Create Regulatory Compliance Deliverables for Pharmaceutical Industry: SDTMs, ADaMs, Tables, Lists and Graphs Participants will gain comprehensive knowledge on common R packages (Tidyverse, DPLYR and Piping) and the R programming language. Attendees will learn how to access, create and process R data frames in data management, reporting and analysis. In addition, this course shows best practices in how to select, filter, derive, append and join data frames using SQL type code. Ideal for the pharma industry, examples of both SDTM and ADaM datasets will be created, which are...