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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 important in the pharmaceutical industry. Finally, tables, lists and graphs will be created from SDTMs and ADaMs.
 

Course Learning Highlights:

  • Install R Packages and Load Libraries Exercises
  • Access CSV, Excel, and SAS Data sets Exercises
  • Create Variables as Vectors and Assign Values or read CSV, Excel, SAS file into Data Frames
  • Create Data Frames from Vectors
  • Data Management Operations and Functions
  • Summarize, Transpose, Format, Join, View and Display Data Frames
  • Tidyverse Package for Data Management
  • DPLYR for SQL
  • R Piping %>%
  • Create SDTMs and ADaMs
  • Summary Tables and Lists
  • Statistical Analysis
  • Create Graphs  


Course Outcomes:

  • Learn setup process and import data types into R data frames
  • Master basic R programming concepts: Vectors, Data Frames, Data Management, Joins, Summarize and View
  • Understand and apply advanced R programming concepts: Piping command (%>%), DPLYR components and Tidyverse
  • Create regulartory compliance deliberables for pharmaceutical industry: SDTMs, ADaMs, Tables, Lists and Graphs 
 

Software: Base R, R Studio are required which are free to download

Hardware:

  • An Intel-compatible platform running Windows 11, 10 /8.1/8 /7 /Vista /XP /2000 Windows Server 2022, 2019 /2016 /2012 /2008 /2003
  • At least 256 MB of RAM, a mouse, and enough disk space for recovered files, image files, etc.
  • A Mac computer with Apple Silicon, Intel, PowerPC G5 or PowerPC G4 processors.
  • At least 256 MB of RAM, a mouse

Course Typically Offered: Online in Summer and Winter quarters

Textbook required: None

Contact: For more information about this course, please contact unex-techdata@ucsd.edu

Course Number: CSE-41396
Credit: 2.00 unit(s)
Related Certificate Programs: BiostatisticsData Mining for Advanced AnalyticsR for Data Analytics

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