Fall 2026 · Lecture 1 · August 24, 2026
Introduction and logistics
What computational data analysis asks, how the course fits together, and what students will learn this semester.
Learning goals
- Frame machine learning as learning from experience.
- Identify the major themes and expectations of the course.
- Understand how lecture materials will be organized and updated.
Materials
Lecture notes
Concise notes, worked examples, visuals, and references will be added after class.
Lecture extensions
Course materials and optional topics
Four independently reviewed sections
Assignment pending
Develop the assigned part of the lecture’s core course materials.
The course team will assign this section through a GitHub issue.
Assignment pending
Develop the assigned part of the lecture’s core course materials.
The course team will assign this section through a GitHub issue.
Assignment pending
Develop an optional extension, application, or related topic assigned for this lecture.
The course team will assign this section through a GitHub issue.
Assignment pending
Develop an optional extension, application, or related topic assigned for this lecture.
The course team will assign this section through a GitHub issue.