Lecture4.7-Functions-Inductive Reasoning

List of Lecture Topics
Lecture 1 – Introduction to Python:
• Knowledge
• Machines
• Languages
• Types
• Variables
• Operators and Branching
Lecture 2 – Core elements of programs:
• Bindings
• Strings
• Input/Output
• IDEs
• Control Flow
• Iteration
• Guess and Check
Lecture 3 – Simple Programs:
• Approximate Solutions
• Bisection Search
• Floats and Fractions
• Newton-Raphson
Lecture 4 – Functions:
• Decomposition and Abstraction
• Functions and Scope
• Keyword Arguments
• Specifications
• Iteration vs Recursion
• Inductive Reasoning
• Towers of Hanoi
• Fibonacci
• Recursion on non-numerics
• Files
Lecture 5 – Tuples and Lists:
• Tuples
• Lists
• List Operations
• Mutation, Aliasing, Cloning
Lecture 6 – Dictionaries:
• Functions as Objects
• Dictionaries
• Example with a Dictionary
• Fibonacci and Dictionaries
• Global Variables
Lecture 7 – Debugging:
• Programming Challenges
• Classes of Tests
• Bugs
• Debugging
• Debugging Examples
Lecture 8 – Assertions and Exceptions
• Assertions
• Exceptions
• Exception Examples
Lecture 9 – Classes and Inheritance:
• Object Oriented Programming
• Class Instances
• Methods
• Classes Examples
• Why OOP
• Hierarchies
• Your Own Types
Lecture 10 – An Extended Example:
• Building a Class
• Viualizing the Hierarchy
• Adding another Class
• Using Inherited Methods
• Gradebook Example
• Generators
Lecture 11 – Computational Complexity:
• Program Efficiency
• Big Oh Notation
• Complexity Classes
• Analyzing Complexity
Lecture 12 – Searching and Sorting Algorithms:
• Indirection
• Linear Search
• Bisection Search
• Bogo and Bubble Sort
• Selection Sort
• Merge Sort
Lecture 13 – Visualization of Data:
• Visualizing Results
• Overlapping Displays
• Adding More Documentation
• Changing Data Display
• An Example
Lecture 14 – Summary