Data Science with R

Data Science with R

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.

Optional reading: R for Data Science by Garrett Grolemund and Hadley Wickham.

Course typically offered: Online during our 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 Number: CSE-41308
Credit: 3.00 unit(s)
Related Certificate Programs: Business Intelligence Analysis, Data Mining for Advanced Analytics, Database Management, Machine Learning Methods, Python Programming, R for Data Analytics, Selected Topics in Artificial Intelligence

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4/3/2023 - 6/2/2023

$745

Online

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• SECTION ID:

  170443

• 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:

  Li, Arthur, Biostatistician, City of Hope; Instructor, Department of Preventative Medicine, USC

  Arthur Li holds an M.S. in Biostatistics from the University of Southern California. Currently, he is a biostatistician at the City of Hope National Medical Center. Li developed and taught an introductory SAS course at USC for the past six years, and teaches a clinical biostatistics sourse at UC San Diego Extension. In addition to teaching and working on cancer-related research, Li wrote a book titled “Handbook of SAS® DATA Step Programming” which was released in April 2013.  

• TEXTBOOKS:

  No textbook required.

• POLICIES:

  No refunds after: 4/9/2023.
  

• NOTE:

• DATE & LOCATION:

  4/3/2023 - 6/2/2023
  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.