Practical R for the Pharmaceutical Industry

Practical R for the Pharmaceutical Industry - Learn to Create Regulartory Compliance Deliberables for Pharmaceutical Industry: SDTMs, ADaMs, Tables, Lists and Graphs

This 20-hours online class teaches essential concepts about common R packages (Tidyverse, DPLYR and Piping) and the R programming language. Attendees learn how to access, create and process R data frames in data management, reporting and analysis. In addition, this class 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 Highlights:

• 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 

 
Course Learning Outcomes:

• 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  

   
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, and

Course Typically Offered: Online in Summer and Winter
 
Textbook required: None
 
Prerequisite: 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: Biostatistics, Data Mining for Advanced Analytics, R for Data Analytics

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7/12/2023 - 8/19/2023

$495

Online

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• SECTION ID:

  174087

• CLASS TYPE:

  Online Asynchronous.
  
  This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
  You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.

• INSTRUCTOR:
  

  Gupta, Sunil K, Principal SAS CDISC Consultant, Gupta Programming

  Sunil K. Gupta is a best-selling SAS author and global corporate trainer.  Sunil is the Principal SAS CDISC Consultant at Gupta Programming since 1994.  His experience with large pharmaceutical companies includes working on six FDA submissions.  In 2011, Sunil launched his unique SAS resource blog, SASSavvy.com, for smarter SAS searches and has released five new SAS e-Guides.  Most recently, Sunil was recognized by SAS Institute’s Circle of Excellence for 20 years of service.  Last year, Sunil was an invited presenter at WUSS, NESUG and SESUG for his ‘highly acclaimed’ Proc SQL Hands-on workshop. 

• TEXTBOOKS:

  No information available at this time.

• POLICIES:

  No refunds after: 7/11/2023.
  

• NOTE:

• DATE & LOCATION:

  7/12/2023 - 8/19/2023
  extensioncanvas.ucsd.edu
  You will have access to your course materials on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.