• Classroom
  • Online, Instructor-Led

Introduction to R Programming for Data Science & Analytics is a hands-on course that presents common scenarios encountered in analysis and present practical solutions. This course provides indoctrination in the practical use of the umbrella of technologies that are on the leading edge of data science development focused on R and related tools. Working in a hands-on learning environment, led by our expert practitioner, you’ll learn R and its ecosystem, and where it’s a better a tool than Excel.

Learning Objectives

This course provides indoctrination in the practical use of the umbrella of technologies that are on the leading edge of data science development focused on R and related tools. Working in a hands-on learning environment, led by our expert practitioner, you’ll explore R and its ecosystem, and where it’s a better a tool than Excel. This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current “on-the-job” experience into every classroom. Working in a hands-on learning environment, guided by our expert team, attendees will learn about and explore: Data Science essentials R programming Essentials Variables and Types, Loops, R Scalars, Vectors, and Matrices String and Text Manipulation, List & Functions Data Frames and File I/O Reading data from files and data prep Visualization Exploration With Dplyr Statistical Modeling With R Data Exploration Regressions R and Big Data

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):