Instructor: Dan Ryan

Welcome and Getting Started

Agenda

• Who am I?
• Why are we here?
• Who are you?
• What will we do?
• Teachable Machine

Computational Reasoning 2025

Instructor

Teaching Professor in Computer Science

Dan Ryan

Why are we here?

See What this course is and is not

Who are you?

What will we do?

Requirements/Grading

Preclass work is ungraded but credit is given only when it is submitted on time. Expect 23 assignments. On 4 point scale (A=4.0), % of submissions = grade. E.g, 10/23=1.73 = ~C-

Post Class Reviews similarly (these can include use an LLM to talk about how something works and report on what you learned) Some are timed quizzes?

Week One essay (gets you to address abstraction, decomposition, complexity, alignment) or series of questions that gets recapitulated in final week. Or just an exam before the course begins?

explain abstraction

why does a teacher's plan for each child in the class to send a valentines day card to each other child get tricky when the class is large?

how does HTTPS work?  what is crypto? how does AI differ from ML?
Projects: sketch out an idea for how to (1) build something with teachable machine, (2) create an actually useful GPT, (3) propose a blockchain application that could help solve an actual problem worth solving, (4)
rate anonymous feedback on your ideas.

Read a book. Show that you've purchased it and written in it. Updates throughout the semester. Book review at the end.
 

Teachable Machine