MIT 计算机科学及编程导论 Python 笔记 1

计算机科学及编程导论在 MIT 的课程编号是 6.00.1，是计算机科学及工程学院的经典课程。之前，课程一直使用 Scheme 作为教学语言，不过由于 Python 简单、易学等原因，近年来已经改用 Python 作为教学语言了。更多介绍

最初知道这个课程的时候大概是在 2014 年，对于做事拖沓的我，这门课程已经从低清随堂录制变成了 edX 平台的一门 高清的 MOOC，转眼间已经大三，希望自己能够完成自己曾经定下的计划。以下是在我在学习本课程时的一些笔记，在此与大家共享、共勉。

What does a computer do?

• Fundamentally a computer:
  • Performs some calculations
  • Remembers results
• What calculations?
  • Built in primitives
  • Creating our own methods of calculating

Simple calculations are not enough, so good algorithm design also needed to accomplish a task.

Despite its speed and storage, a computer does have limitations

• Some problems still too complex
• Some problems are fundamentally impossible to computer (e.g. Turing's Halting Problem)

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Knowledge

• Declarative
• Imperative (likes a recipe, "how-to")

Computers

• Fixed-program computers (earliest computers)
  
  To solve specific problems
  • Atanasoff (1941) - linear equations
  • Turing bombe

• Stored-program computers
  
  

• Program is a recipe. Each programming language provides a set of primitive operations.
• Given a fixed set of primitives, a good programmer can program anything.

• Anything you can do with a language, you can do with another.

About python

• High(√) vs. Low
• General(√) vs. Targetted
• Interpreted(√) vs. Compiled

Aspects of languages & Common Errors

Aspects	Description
Primitive constructs	numbers, strings, simple operators
Syntax	which strings of charactres and symbols are well-formed
Static semantics	which syntactically valid strings have a meaning
Full semantics	what is the meaning associated with a syntactically correct string of symbols with no static semantic errors

• 语法用来描述语言中，什么表述是合法的。
• 静态语义表示什么程序是有意义的，哪种表达是有意义的。
• 完整语义即程序想达到什么目的，运行程序会产生什么效果。

Goal

• Learn the syntax and semantics of a programming language.
• Learn how to use those elements to translate “recipes” for solving a problem into a form that the computer can use to do the work for us.
• Computational modes of thought enable us to use a suite of methods to solve problems.

References

• MIT麻省理工学院公开课：计算机科学及编程导论 Python 笔记1-3
• 麻省理工公开课《计算机科学及编程导论》中文笔记（第1讲）
• 【MIT计算机科学与编程导论】打卡及笔记