R Mentoring Program ( Join Us - Start on Your Schedule)
My unique R-Guru mentoring program assumes no prior R knowledge. This comprehensive program includes: installing R and RStudio, familiarizing the basics of R, understanding R's data structures, learning the basics of data import and manipulation, and finally practicing data reporting and visualization. At the end of completing all weekly hands-on exercises, you will earn the R Clinical Trials Certificate! See Table of Tasks and Papers and Videos. E-mail me your R questions!
R-Guru Empowers all R Programmers with Three Learning Methods
A. R-Guru Weekly Videos & Exercises (Password required to access videos)
Week 1 Video: Install RStudio, Install and Load Packages, What is R, Learning R, Create Objects, Process Flow & Scope, Common Packages, Common Operations, Importing Data into R |
Week 2 Video: View, Create Vars, Data Frames, Manage Data Frames |
Week 3 Video: Join, Summarize and Transpose Data Frames |
Week 4 Video: Tidyverse Data Management Operations |
Week 5 Video: DPLYR for SQL, DPLYR Functions, %>% Piping |
Week 6 Video: Create SDTMs |
Week 7 Video: Create ADaMs |
Week 8 Video: Tables, Stats, Graphs |
Optional: Compare with SAS, SAS Tasks, SAS Procedures, SAS Syntax, SASSY, Debugging, Metadata, Custom R Functions, Custom R Packages, R in AI, R Markdown, Pharmaverse, R Shiny |
B. R-Guru Class Weekly Structure
Mathura Ramanathan, Statistical Programming & CDISC Standards Consultant
R-Guru.com is a wealth of treasures and information for anyone who is motivated to get ready for R.
Amole Palande, Director, Statistical Programming at Chinook Therapeutics, Inc. A Novartis Company
I enjoyed learning R and believe I will be able to leverage/advance this knowledge as needed in my career.
Ekaterina Rudenko, Statistician
I liked that there was a lot of information packed in a precise manner. I feel like I learned a lot in just those 6 weeks.
Master Concepts: Getting Started with R, Data Structures, R Packages and Scripts, Descriptive Statistics, Statistical Graphs, Working with Messy Data, Conditionals, Controls and Functions, SQL and R