Capstone in Applied Data Science with R

Showcase your R expertise with a real-world, AI-powered analytics project This R Analytics Capstone Project course integrates skills from the three required courses in the "R for Data Analytics" program, enabling students to create a professional portfolio project (e.g.

Quarto book, R-Shiny interactive visualization, or similar) using AI assistance.

Focusing on data collection, cleaning, analysis, and visualization from provided sources, this course prepares professionals, researchers, and students for real-world analytics challenges.

Course Highlights: Introduction to Quarto Book Creation: Learning to structure and format a Quarto book for project documentation, including text, code, and output integration.

Data Collection from Multiple Sources: Selecting and importing data from provided datasets, preparing for analysis Data Cleaning and Preparation: Techniques to handle missing values, inconsistencies, and transformations in R Statistical Analysis Selection: Choosing and implementing a statistical method (e.g., regression, t-test) based on project needs Table and Figure Generation: Creating tables with "flextable" and visualizations to present results clearly Programming Skills: Writing custom functions and loops to automate and optimize data tasks Project Summary and Reporting: Crafting a comprehensive report in Quarto, integrating analysis, visuals, and conclusions AI-Assisted Project Development: Utilizing AI tools (e.g., for code suggestions, report polishing) to enhance project quality Course Learning Outcomes: Synthesize skills from prior R courses to design and execute a comprehensive data analytics project, documented in a professional R project Apply data collection, cleaning, and statistical analysis techniques to real-world datasets, selecting from provided sources Create publication-ready tables and figures to communicate findings effectively Develop reusable R functions and loops to streamline data processing, enhancing project efficiency Produce a detailed summary report, leveraging AI tools to refine analysis and presentation for professional use Course Typically Offered: Online in spring and fall quarters Prerequisites: Students must complete all three required courses in the R for Data Analytics certificate in order to enroll into this course which includes CSE-41097 Introduction to R Programming , CSE-41198 Introduction to Statistics using R , and CSE-41408 Advanced Data Wrangling and Visualization in R .

Next Step: After completing this course, consider taking CSE-41396 Practical R for the Pharmaceutical Industry to continue learning.

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