Introduction to Programming for Data Science (201-0-20)

Meeting Info

Fisk Hall 217: Mon, Wed, Fri 3:00PM - 3:50PM

Overview of class

This introductory course provides a foundation in programming with Python and R, focusing on essential skills for data science. Students will learn to write, execute, debug, and test code while developing an understanding of both languages' unique features. Key topics include using conditional statements and loops, creating user-defined and recursive functions, and selecting appropriate data structures to manage data effectively. Students will translate real-world problems into coding solutions, incorporating best practices for efficiency, style, and reproducibility, including version control, style guides, and effective commenting. This course emphasizes building a solid programming base tailored for data science applications.

Registration Requirements

High School Algebra

Learning Objectives

Write, execute, debug and test code in Python and R
Use conditional statements and loops to implement various tasks
Create user-defined and recursive functions to create specialized code blocks
Incorporate the appropriate data structures of a programming language to handle data
Translate a problem from layman terms to a coding problem in Python and R
Incorporate best programming practices for writing efficient code in Python and R
Incorporate best practices for code reproducibility (version control, style guides, and commenting)

Teaching Method

There will be three 50-minute lectures per week. The lectures will mostly include in-class coding with explanatory notes as comments on the script; along with some diagrams to visualize some coding concepts better.

Evaluation Method

Students will have roughly one homework assignment each week to practice and demonstrate the coding techniques taught during class hours,  2-3  in-class exams, and other miscellaneous assessment methods (for example: short discussions, surveys, and mini quizzes).

Class Materials (Required)

A Practical Introduction to Python Programming by Brian Heinold

An Introduction to R by Alex Douglas

Class Attributes

Empirical and Deductive Reasoning Foundational Dis
Formal Studies Distro Area