CS50's Introduction to Programming with R

Introduction

David Malan

• Introduction to the course and its focus on R.
• Context: R used for statistical computing, graphics, data science.
• Relationship to CS50x: while CS50x focuses on CS and programming broadly, CS50R is all about R.
• Flexibility: can be taken before, during, or after CS50x.

Carter Zenke

• Course progression and content overview.

Course Outline

Data Representation in R

• Vectors and Data Frames: initial focus on representing data.

Data Transformation

• Logical Expressions: used for filtering and analyzing data subsets.
• Functions and Loops for data transformation.
• Functional Programming paradigms.

Data Tidying

• Learning from existing R code and methodologies for tidying data.
• Making data easier to analyze.

Data Visualization

• Techniques for visualizing tidy data.

Testing and Packaging Programs

• Testing: Ensuring programs behave as intended.
• Packaging: Preparing programs for sharing.

Goals and Outcomes

• Taking students from no knowledge of R to the ability to share their R knowledge with the world.
• Encouragement and excitement for the creation and application of R.

Ending Note

• Enthusiasm expressed for student creativity and results.