EDUC 260B

EDUC 260B
Fundamentals of Programming

Promo Video

Winter 2024

This is the second course in a programming/data science sequence designed for students who do not have a programming background and perhaps never thought they would write code. (The first course in the sequence is EDUC 260A: Introduction to Programming and Data Management)

Although EDUC 260B primarily uses the R programming language, the course is organized around practical programming skills/concepts that are fundamental across modern object-oriented programming languages (e.g., Python, Javascript). Course topics include the following: organizing files, folders, and scripts; reading (importing) and writing (exporting) data; using Git and GitHub for version control and collaboration; writing functions; iteration (e.g., "loops"); conditional execution; strings and regular expressions. These general programming skills are prerequisite for flashier data science applications (e.g., web-scraping, streaming social media data, interactive maps, machine learning).

Syllabus & Resources

Class materials including the syllabus, class Zoom link, GitHub issues, GitHub teams, and course textbook are linked below.

Lecture Materials

Lecture materials are organized by topic. All lectures will have associated materials for that lecture topic linked below. This includes lecture notes (html), the R markdown file used to create the lectures (.Rmd), pre-recorded video(s), and any materials used during synchronous class sessions.

Organizing files and folders

HTML

Organizing files and folders

.Rmd

Organizing files and folders

Video recordings (2022)

Lecture for Week 1, Organizing and IO: Section 1 to 2.2 (01/07/22) - Working Directory
Lecture for Week 1, Organizing and IO: Section 2.3 to 2.4 (01/07/22) - File Paths and Navigating
Lecture for Week 1, Organizing and IO: Section 2.5 to 2.4 (01/07/22) - Example Project Directory
Lecture for Week 1, Organizing and IO: Section 3 (01/07/22) - Organizing R Script
Lecture for Week 1, Organizing and IO: Section 4 (01/07/22) - Downloading and Unzipping
Lecture for Week 1, Organizing and IO: Section 5 (01/07/22) - Readr Package
Lecture for Week 1, Organizing and IO: Section 6 (01/07/22) - Readxl Package
Lecture for Week 1, Organizing and IO: Section 7 (01/07/22) - Haven Package
Lecture for Week 1, Organizing and IO: Section 8 (01/07/22) - Saving and Loading R Objects

Video recordings (2021)

Lecture for Week 2, Organizing and IO: Sections 1-4 (01/15/21) - Organizing & Reading/Writing data

Visualizations using ggplot

HTML

Visualizations using ggplot

.Rmd

Visualizations using ggplot

Video recordings (2022)

Lecture for Week 2, Visualizations using ggplot: Section 1 (01/14/22) - Introduction
Lecture for Week 2, Visualizations using ggplot: Section 2 (01/14/22) - Concepts
Lecture for Week 2, Visualizations using ggplot: Section 3.1 (01/14/22) - ggplot() and aes() functions
Lecture for Week 2, Visualizations using ggplot: Section 3.2 (01/14/22) - Adding geometric layers
Lecture for Week 2, Visualizations using ggplot: Section 3.3 (01/14/22) - Small multiples using faceting
Lecture for Week 2, Visualizations using ggplot: Section 4.1 (01/14/22) - Labels
Lecture for Week 2, Visualizations using ggplot: Section 4.2 (01/14/22) - Scales
Lecture for Week 2, Visualizations using ggplot: Section 4.3 (01/14/22) - Colors
Lecture for Week 2, Visualizations using ggplot: Section 4.4 (01/14/22) - Themes
Lecture for Week 2, Visualizations using ggplot: Section 5 (01/14/22) - Exporting plots

Git and GitHub

HTML

Git and GitHub

.Rmd

Git and GitHub

Video recordings (2022)

Introduction:

Command Line:

Overview of core concepts and workflow:

Lecture for Week 3, Git and GitHub: Section 3 (01/21/22)

Getting started: Git Repository:

Git commands: Observing your repository:

Lecture for Week 3, Git and GitHub: Section 5.1 (01/21/22)

Lecture for Week 3, Git and GitHub: Section 5.2 (01/21/22)

Lecture for Week 3, Git and GitHub: Section 5.3 (01/21/22)

Git:Under the hood:

Lecture for Week 4, Git and GitHub: Section 6.1 (01/28/22)

Lecture for Week 4, Git and GitHub: Section 6.2.1 (01/28/22)

Lecture for Week 4, Git and GitHub: Section 6.2.2 (01/28/22)

Lecture for Week 4, Git and GitHub: Section 6.2.3 (01/28/22)

Lecture for Week 4, Git and GitHub: Section 6.2.4 (01/28/22)

Lecture for Week 4, Git and GitHub: Section 6.2.5 (01/28/22)

Lecture for Week 4, Git and GitHub: Section 6.3 (01/28/22)

Lecture for Week 4, Git and GitHub: Section 6.4 (01/28/22)

Git Commands:Undoing changes:

Lecture for Week 4, Git and GitHub: Section 7 (02/03/23)

Branching:

For Section 8: Branching, see 2021 video

Merging:

For Section 9: Merging, see 2021 video

Appendix:

Lecture for Week 4, Git and GitHub: Section 11 (01/28/22)

Video recordings (2021)

Lecture for Week 3, Git and GitHub (01/22/21) - Overview
Lecture for Week 3, Git and GitHub (01/22/21) - Git walkthrough
Lecture for Week 4, Git and GitHub (01/29/21) - Section 7: Undoing changes
Lecture for Week 5, Git and GitHub (02/05/21) - Section 8: Branching
Lecture for Week 5, Git and GitHub (02/05/21) - Section 9: Merging
Lecture for Week 5, Git and GitHub (02/05/21) - Resolving merge conflicts

Programming

HTML

Programming

.Rmd

Programming

Video recordings (2022)

Lecture for Week 8, Programming (02/25/22) - Section 5.1 to 5.3.1: Functions
Lecture for Week 8, Programming (02/25/22) - Section 5.3.2:Dot-dot-dot
Lecture for Week 8, Programming (02/25/22) - Section 5.3.3:Checking Values
Lecture for Week 8, Programming (02/25/22) - Section 5.4.1: Return Values
Lecture for Week 8, Programming (02/25/22) - Section 5.4.2 to 5.4.3: Return Values
Lecture for Week 8, Programming (02/25/22) - Section 5.4.4: Return Values

Video recordings (2021)

Lecture for Week 6, Programming (02/12/21) - Section 1: Introduction
Lecture for Week 6, Programming (02/12/21) - Section 3: Iteration 3.1-3.3
Lecture for Week 6, Programming (02/12/21) - Section 3: Iteration 3.4-3.5
Lecture for Week 7, Programming (02/19/21) - Problem set 7 overview
Lecture for Week 7, Programming (02/19/21) - Section 4: Conditional execution
Lecture for Week 7, Programming (02/19/21) - Section 5: Functions 5.1-5.2
Lecture for Week 8, Programming (02/26/21) - Section 5: Functions 5.3-5.4

Strings and regex

HTML

Strings and regex

.Rmd

Strings and regex

Video recordings (2022)

Lecture for Week 9, Strings and Regex (03/04/22) - Section 1: Introduction
Lecture for Week 9, Strings and Regex (03/04/22) - Section 2.1 Str_view() and Str_view_all()
Lecture for Week 9, Strings and Regex (03/04/22) - Section 2.2 and 2.3: Special Characters
Lecture for Week 9, Strings and Regex (03/04/22) - Section 3: Regular Expression Basics
Lecture for Week 9, Strings and Regex (03/04/22) - Section 3: Regular Expression Basics Cont.
For sections 3.2-3.5, see 2021 videos below
Lecture for Week 10, Strings and Regex (03/11/22) - Section 4.0.1: Application for Webscraping
Lecture for Week 10, Strings and Regex (03/11/22) - Section 4.1: Stringr Package Overview
Lecture for Week 10, Strings and Regex (03/11/22) - Section 4.2 to 4.4: Str_detect(), Str_subset(), Str_Extract()

Video recordings (2021)

Lecture for Week 9, Strings and regex (03/05/21) - Section 1 & 2 - : Introduction and Prerequisites
Lecture for Week 9, Strings and regex (03/05/21) - Section 3: Regex basics 3.1-3.3
Lecture for Week 9, Strings and regex (03/05/21) - Section 3: Regex basics 3.4-3.5
Lecture for Week 10, Strings and regex (03/12/21) - Section 4: Regex with stringr functions
Lecture for Week 10, Strings and regex (03/12/21) - R learning next steps & resources

Readings & Assignments

Weekly pre-recorded lectures, lecture notes (html), readings, and problem sets will be posted on the class website a week in advance. Students are expected to work through the asynchronous lecture materials (videos, notes, etc.) and submit the problem set prior to the synchronous class meeting.

Week 1 (Do after 1/13/23 class)

Required readings

Absolute and Relative Paths video
Syllabus
From Organizing files and folders lecture:

Section 1: Introduction
Section 2: Organizing project directory
Section 3: Organizing R script
Section 4: Downloading & unzipping data
Section 5: readr package
Section 6: readxl package
Section 7: haven package
Section 8: Saving and loading R objects

Encouraged readings

From R for Data Science (Grolemund & Wickham, 2016):

Chapter 11: Data import

Problem set 1 due 1/20/23 @ 9am

Problem set files

Week 2 (Do after 1/20/23 class)

Required readings

Helping my students overcome command-line bullshittery
From Git and GitHub lecture:

Section 1: Introduction
Section 2: Command line
Section 3: Overview of core concepts and workflow
Section 4: Getting started: Git repository
Section 5: Git commands: Observing your repository
Section 11.1: Appendix

Bash cheat sheet (skip creating custom commands)

Encouraged readings

Problem set 2 due 1/27/23 @ 9am

Problem set files

Week 3 (Do after 1/27/23 class)

Required readings

From ggplot lecture:

Section 1: Introduction
Section 2: Concepts
Section 3: Creating graphs using ggplot
Section 4: Customization
Section 5: Exporting plots
ggplot cheatsheet:

Problem set 3 due 2/3/23 @ 9am

Problem set files

Week 4 (Do after 2/3/23 class)

Required readings

From Git and GitHub lecture:

Section 6: Git: Under the hood
Section 7: Git commands: Undoing changes

The Git Object Model
git reset vs git revert

Encouraged readings

Problem set 4 due 2/10/23 @ 9am

Problem set files

Week 5 (Do after 2/10/23 class)

Required readings

From Git and GitHub lecture:

Section 8: Branching
Section 9: Merging

Git Branch
Git Merge
Git merge conflicts

Encouraged readings

From Git and GitHub lecture:

Section 10: Pull Requests

What is Pull Request? video

Problem set 5 due 2/17/23 @ 9am

Problem set files

Problem set 5 pdf

Problem set 5 .Rmd

Problem set 5 Solutions RMD

Problem set 5 Solutions R Script

Week 6 (Do after 2/17/23 class)

Required readings

From Programming lecture:

Section 1: Introduction
Section 2: Foundational Concepts
Section 3: Iterations

From R for Data Science (Grolemund & Wickham, 2016):

Chapter 21 (only 21.1-21.3): Iteration

Encouraged readings

From Advanced R (Wickham, 2014):

Chapters 2: Names and values
Chapters 3: Vectors
Chapters 4: Subsetting

From R for Data Science (Grolemund & Wickham, 2016):

Chapter 21 (only 21.1-21.3): Iteration

Problem set 6 due 2/24/23 @ 9am

Problem set files

Week 7 (Do after 2/24/23 class)

Required readings

From Programming lecture:

Section 4: Conditional execution
Section 5: Functions (5.1 - 5.2)

From R for Data Science (Grolemund & Wickham, 2016):

Chapter 19 (only 19.1-19.4) : Functions

Problem set 7 due 3/3/23 @ 9am

Problem set files

Week 8 (Do after 3/3/23 class)

Required readings

From Programming lecture:

Section 5: Functions (5.3 - 5.4)

From R for Data Science (Grolemund & Wickham, 2016):

Chapter 19 (only 19.5-19.6) : Functions

Problem set 8 due 3/10/23 @ 9am

Problem set files

Week 9 (Do after 3/10/23 class)

Required readings

From Strings and Regular Expressions lecture:

Section 1: Introduction
Section 2: Prerequisites to regex
Section 3: Regular expression basics

Problem set 9 due 3/17/23 @ 9am

Problem set files

Week 10 (Do after 3/17/23 class)

Required readings

From Strings and Regular Expressions lecture:

Section 4: Regex with stringr functions
Section 5: Appendix

From R for Data Science (Grolemund & Wickham, 2016):

Chapter 14 (only 14.4-14.5): Strings

Problem set 10 due 3/24/23 @ 9am

Problem set files

Course Communication

GitHub is the industry standard platform used by programmers to collaborate on projects. We will use GitHub for course communication and discussion.

Ask course questions using GitHub issues

You will be using GitHub issues to post any questions you have relating to the course material. When you open an issue, please title it appropriately with the question you have and make sure to tag the instructors in your post. We encourage students to answer each other's questions as well and discuss ideas.

Class announcements with GitHub Discussions

We will be posting all class announcements using GitHub Discussions. The GitHub team discussions feature allows for quick and seamless communication to all members of an organization or team – in this case, to all students with a GitHub account enrolled in the course. You will also be creating separate teams for your problem set groups.

Email instructors for private questions

If you have a personal question or issue, you can email the instructor or TA directly. Additionally, we are available for office hours or by appointment if there is anything you would like to discuss with us in private.

Email Ozan