Data Science with R
CSE-41308
Data management and manipulation is an essential task for data scientists who deal with data on a day-to-day basis. In recent years, many R packages were developed to tackle a wide variety of data science challenges. The focus of this course is the tidyverse suite of packages, which contain a large variety of tools to efficiently manage complex and big data. The materials in this course are essential for developing robust and efficient R programs in the data science field.
At the end of this course, students will be able to work independently to solve common data management tasks by developing their own customized and reusable programs in the data science field.
Course Highlights:
- Review R Objects and RStudio
- The tibble object
- Pipes
- Data Input and Output and Data Transforamation
- Tidy and Relational Data
- Data and Time Manipulation
- String Manipulations
- Functions
- Functional Programming
Course Learning Outcomes:
- Solve common data management tasks
- Develop customized and reusable programs
- Grasp and implement the techniques of efficient programming in R language
- Efficient importing, tidying, manipulating and presenting data from different sources
Software: R, a free software environment for statistical computing and graphics, or RStudio
Course typically offered: Online in Spring and Fall quarters
Prerequisites: Basic understanding of R language or complete Introduction to R Programming.
Next steps: Upon completion of this class, consider enrolling in other required coursework in the R for Data Analytics specialized certificate program
Contact: For more information about this course, please contact unex-techdata@ucsd.edu
Course Information
Course sessions
Section ID:
Class type:
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.
Textbooks:
No textbook required.
Policies:
- No refunds after: 4/7/2025
Schedule:
Instructor: Arthur Li, Master of Science
Biostatistician, City of Hope; Instructor, Department of Preventative Medicine, USC
Arthur Li holds an M.S. in Biostatistics from the University of Southern California and serves as a biostatistician at City of Hope National Medical Center, where he supports cancer research by analyzing clinical and genomic data. At USC, he developed and taught SAS and R programming courses and occasionally taught a linear regression course, helping students build data analysis skills. At UC San Diego Division of Extended Studies, Li developed and teaches the Biostatistical Methods series courses, transitioned from SAS to R, assisting learners in exploring biostatistics, alongside other R programming courses. He authored the Handbook of SAS® DATA Step Programming (CRC Press, 2013), a resource for data management in SAS. In his spare time, Li enjoys traveling, cooking, and exploring new cultures.
