Introduction to 6.111: Lecture 1

Course Introduction

• Recorded for OCW: Future lectures will be recorded. Avoid front rows if you don't want to be filmed.
• Lecturers: Anna Bell (EECS Department) and later Prof. Eric Grimson.
• Content Overview:
  • Basic administrivia
  • Course information
  • What is computation?
  • Python basics
  • Mathematical operations in Python
  • Python variables and types

Lecture Tips

• Preparation: Download slides and code before lecture.
• Practice: Key to success; programming needs consistent practice like math and reading.
• Fear: Don’t fear breaking your computer by trying out code.

Course Roadmap

• Three Goals:
  1. Knowledge of concepts
  2. Programming skills
  3. Problem-solving abilities
• Practice: Emphasis on practice throughout the course.
• Course Breakdown:
  1. Learning how to program (objects, data structures, control flow)
  2. Writing good quality code (style, readability, organization, modularity)
  3. Computer Science fundamentals (comparing programs, algorithm efficiency)

Understanding Computation

• Fundamental Tasks:
  • Perform calculations
  • Store results in memory
• Types of Calculations: Built-in language operations (addition, subtraction, etc.) and user-defined calculations.

Knowledge Types

• Declarative Knowledge: Statements of fact (e.g., “someone will win a prize”)
• Imperative Knowledge: Sequence of steps or how-to (e.g., steps to determine prize winner)
• Example: Using Python to choose a random winner for a raffle.

Algorithms

• Definitions and Examples: Recipe-like instructions for problem-solving.
• Algorithm Example: Calculating the square root through iterative guesses.
• Algorithm Parts:
  1. Sequence of steps
  2. Flow of control (decisions, loops)
  3. Stopping criterion

Types of Computers

• Fixed-Program Computers: Limited to specific tasks (e.g., early calculators)
• Stored-Program Computers: Can store and execute various sequences of instructions.

Basic Machine Architecture

• Components:
  • Memory: Stores data and instructions
  • Input/Output
  • ALU (Arithmetic Logic Unit)
  • Control Unit: Manages instruction execution
• Instruction Execution Process: Fetch, decode, execute, and store results.
• Primitives: Basic operations like addition, subtraction, logic tests, etc.

Programming Languages

• Built from basic primitives defined by Turing's principles.
• Key Fact: Anything computable in one language is computable in any other language.

Python Basics

• Everything is an Object: All data in Python is treated as objects.
• Object Types: Scalar (indivisible) and non-scalar (compositional).
  • Scalar Types: Integers, floats, booleans, none type
• Finding and Converting Types: Use type() and appropriate conversion functions (e.g., float(), int())

Printing and Expressions

• Output: Use print() to display results explicitly.
• Operators:
  • Arithmetic: +, -, *, /
  • Special: % (remainder), ** (power)
• Syntax and Semantics:
  • Expressions must be syntactically and semantically valid.
  • Programs must have clear single meanings—errors arise when there's a mismatch in programmer's intent and code execution.***

Variable Assignment

• Assignments: Bind names to values using =, enabling reusability and readability.
• Importance of Naming: Choose descriptive names to make code understandable.
• Rebounding Values: Variables can be reassigned new values; previous values may persist in memory but lose reference.
• Distinction from Math: = is assignment, not equality.

Conclusion

• Next Lecture: Introduction to control flow in Python.