This hands-on training course teaches technology professionals and data analysts the fundamentals of R programming. Lecture and lab sessions collaborate to cover importing and manipulating various formats of data, data mining techniques, performing predictive analysis and data visualization using R Commander and Deducer.
Upon completion of the course, attendees will be capable of employing data importing techniques, understanding decision trees, random forests, association rule mining, sentiment analysis, and machine learning techniques. Students will learn to manipulate data with functions like grepl(), sub(), and apply(); to apply data visualization for complex plots, implement linear and logistic regression and understanding Anova; to apply predictive analytics and implement R analytics to create business insights.
Available for Instructor-Led (ILT) in-person/onsite training or Virtual Instructor-Led training (VILT) delivery; Open Enrollment options may be available.
Who Should Attend
Application Developers, Analysts and Data Scientists
What Attendees will learn
This course is designed to provide attendees with a practical introduction to data analysis with R. Learning modules include:
- Linear and nonlinear modeling
- Classical statistical testing, time-series analyzing, classifying, and clustering of data
- Graphical techniques for working with data
- Working with R commands for statistics and visualization
Each attendee will require the ability to run a 64 bit virtual machine (provided with the course). Basic Linux command line skills are valuable but not required.