Description

R is a functional programming environment for business analysts and data scientists, serving as the perfect tool for solving statistical, numerical, or probability-based problems based on real data, when they’ve pushed Excel past its limits. Introduction to R Programming for Data Science and Analytics is a three-day, hands-on course designed to provide you with the practical skills and experience needed use R to handle large datasets, perform intricate analyses and data management, and create vivid and insightful data visualizations - all essential competencies for today's data professional. Working in a hands-on learning environment guided by our expert instructor, you’ll gain an comprehensive understanding of R programming. Starting with the basics, you'll learn about R and RStudio, the installation of packages, and diverse variable types and data structures. Data visualization forms a critical part of the learning journey as you learn to create base plots, use ggplot2, and explore interactive data visualization tools like Shiny and Plotly. The course emphasizes data management skills, teaching you data summarization, how to create factor variables, merge and join data, and use the table() function effectively. By the end of the course, you'll be proficient in data import and export, including handling Excel spreadsheets, creating and plotting linear model objects, creating data summarization tables, and combining matrices of objects into data frames. You'll have the skills to manage data efficiently and produce engaging, insightful visualizations, ready to apply this knowledge in real-world projects. With these competencies, you'll be well-positioned to make a tangible impact on your team's data analytics processes, making you an invaluable asset in your professional ecosystem.