Lecture 1: Introduction to Programming in Python

Jul 16, 2024

Lecture 1: Introduction to Programming in Python

Instructor Information:

  • Name: Anna Bell (First name: Anna, Last name: Bell)
  • Department: ECS
  • Experience: Lecturer for almost 10 years, teaching introductory courses

Course Overview:

  • Course Title: 6100a (Introduction to Programming in Python)
  • Focus: Computational thinking, Python programming, and problem-solving skills

Lecture Outline:

  1. Course administrative information
  2. High-level overview of computers and how they work
  3. Introduction to Python basics and interactive coding

Important Points:

Administrative Details:

  • Download lecture slides beforehand for notes and code execution
  • Lectures are interactive with breaks (referred to as "UTRI breaks") for hands-on coding
  • Participation and practice are highly encouraged for skill development
  • Learning programming is similar to learning math or reading; it requires regular practice

Course Goals:

  • Knowledge of Concepts: Computer science ideas and principles
  • Programming Skill: Ability to write and understand code
  • Problem Solving Skills: Translating problems from English to computer science concepts and programming solutions

Topics Covered:

  1. Computational Thinking: Applying computational methods to solve problems
  2. Python Programming Language: Basics of Python coding
  3. Code Structuring: Organizing code for readability and modularity
  4. Basic Algorithms: Foundational algorithms used in computer science
  5. Algorithmic Complexity: Evaluating the efficiency of programs and algorithms

Key Concepts in Computer Science and Programming:

Declarative vs Imperative Knowledge:

  • Declarative Knowledge: Statement of fact (e.g., mathematical definitions)
  • Imperative Knowledge: Step-by-step instructions or recipes (e.g., algorithms)

Example: Finding Square Roots:

  • Declarative Statement: The square root of X is Y such that Y * Y = X
  • Imperative Recipe: Steps to calculate the square root using an initial guess and iterative improvement

Algorithms:

  • Sequence of steps, control flow (conditions and loops), and a stopping point
  • Computers execute algorithms as instructed, storing massive amounts of data and performing operations quickly

Programming Basics:

  • Fixed Program Computers: Limited functionality like pocket calculators
  • Stored Program Computers: Store and execute instructions using a program counter and memory operations
  • Interpreter: Executes stored instructions, basic operations like arithmetic and logic
  • Alan Turing's Contribution: Any computable problem can be represented and computed in any programming language

Python Programming:

  • Primitives, expressions, and types
  • Types in Python: INT, FLOAT, BOOL, NONE
  • Use of commands like type() to check types of objects

Variable Binding and Naming Conventions:

  • Variables: Names that hold values or reference objects in memory
  • Assignment Statements: Bind a variable to a value (=)
  • Naming Rules: Variables should be descriptive and avoid single letters or non-descriptive names
  • Rebinding: Changing the value a variable points to

Writing Programs:

  • Combining objects into expressions and using operators
  • Importance of comments and code readability

Operations and Precedence in Python:

  • Mathematical Operations: Addition, subtraction, multiplication, division, floor division (//), modulus (%), exponentiation (**)
  • Operator Precedence: Exponentiation > Multiplication/Division/Modulus > Addition/Subtraction
  • Type of Result: Generally, if one operand is a float, the result is a float; division always results in a float

Practical Examples and Exercises:

  • Code snippets to exemplify concepts like variable assignment, type checking, and mathematical operations
  • Python tutor as a debugging tool to step through code execution line by line

Conclusion:

  • Summary: Review of creating and manipulating objects in Python, importance of types, variables, expressions, and the difference between math and programming equality
  • Next Lecture: Introduce decision-making in programs (control flow)

Notes on Lecture 1: Introduction to Programming in Python from ECS Department with Anna Bell. Key concepts include computational thinking, Python basics, algorithms, and variable binding. Provided a practical guide and fundamental concepts for beginners to understand Python programming. 📋