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AI 基础原理课

可授课的 AI 基础原理与本机小实验 / A teachable AI fundamentals course with local mini-labs

我的角色 / My Role · 课程设计 / Curriculum Design课包已成型 / Pack ready to teach
AI 基础原理课

项目介绍 / Project Overview

AI 基础原理课面向入门选修:先建立可核对的基本概念(什么在算、输入输出怎么走、结果为什么会偏),再配本机可运行的小型代码实验。课次按原理推进,实验用来验证原理,而不是用演示替代讲解。 / AI Fundamentals is an entry elective: first, checkable basics (what is being computed, how input becomes output, why results drift), then small runnable labs on a laptop. Lessons follow the principles; labs verify them—demos do not replace the explanation.

问题 / THE PROBLEM

解决什么问题 / What problem it solves

课堂谈 AI 时,容易停在口号和成品演示:学生记住几个词,却说不清输入、模型与输出的关系,也很少在本机复现一次。缺的是一条原理课 + 小实验的开课路径。 / AI classes often stall on slogans and finished demos: students keep a few terms, cannot state how input, model and output connect, and rarely reproduce a run locally. What is missing is a principles course with small labs.

理念 / RATIONALE

原理要能在本机被看见 / Principles should be visible on a laptop

理念来源 / Source · 本课包提出 · Fundamentals + local labs

把入门课写成「原理课次 + 可运行实验」:先说明机制,再改一处参数看输出怎么变。目标是能解释,而不是只会跟着点。 / Write the entry course as principle beats plus runnable labs: explain the mechanism, then change one parameter and watch the output. The aim is explanation, not click-along.

先机制后操作 / Mechanism before clicks

课次围绕输入、处理、输出与局限。 / Beats cover input, process, output and limits.

小实验验证 / Labs verify

本机跑通最小例子,对照课上的原理。 / Run a minimal local example against the lecture.

边界要写清 / Name the limits

会错、会偏、依赖数据,写进课次而不是附录。 / Error, drift and data dependence sit in the lesson, not an appendix.

操作 / HOW IT RUNS

怎么实际操作 / How it works

老师按课次讲原理 → 学生本机跑对应实验 → 改一处观察差异 → 课末核对概念。 / Teacher covers the principle → students run the matching lab → change one thing → close by checking the concept.

  1. 01

    讲原理 / Principle

    当节只攻一个可陈述的机制。 / One period, one statement students can repeat.

  2. 02

    跑实验 / Lab

    本机完成最小可运行版本。 / Finish a minimal local run.

  3. 03

    对照改参 / Tweak

    改提示或参数,对照原理解释变化。 / Tweak prompt or parameter; explain the change with the principle.

进度 / WHERE IT IS NOW

现在到哪一步 / Where it is now

课包已成型,可直接用于授课准备;本页说明课次结构。具体实验截图会继续补。 / Pack is ready for teaching prep; this page covers the lesson structure. Lab screenshots will follow.

产品形象:AI 基础原理课 / Product art: AI fundamentals course
产品形象:AI 基础原理课 / Product art: AI fundamentals course

我的工作 / My Contribution

负责课程结构、原理课次与本机实验路径,把材料整理到可以直接开课。 / Owned course structure, principle beats and local lab path, packed so a class can start.

01

原理可核对 / Checkable principles

概念写成能提问、能动手验证的课次。 / Concepts written as questions you can test by running something.

02

实验跟课 / Labs follow the lecture

每段原理配一个本机小实验,不空讲。 / Each principle beat has a local mini-lab.

03

可开课 / Teachable

材料按课次排好,适合选修或拓展课。 / Sequenced for elective or enrichment periods.