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Tree UML videos

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Adding Children

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Last modified by: Russell Feldhausen Jul 1, 2024

Computational Core Logo

  • 0. Introduction
    • 1. Course Introduction
    • 2. Navigating Canvas & Codio
    • 3. Where to Find Help
    • 5. How to Learn Programming
    • 6. Spring 2024 Syllabus
    • 7. Plagiarism Policy
  • 1. Python Review
    • 1. Programming Overview
    • 2. Flowcharts and Pseudocode
    • 3. Syntax Overview
    • 4. Running Code
    • 5. Debugging
    • 6. Variables
    • 7. Conditionals
    • 8. Loops
    • 9. Lists
    • 10. Variable Roles
    • 11. Strings
    • 12. Exceptions
    • 13. I/O
    • 14. Documentation
    • 15. Style
    • 16. Review Summary
  • 2. OOP Review
    • 1. Object-Oriented Programming
    • 2. Functions
    • 3. Classes & Objects
    • 4. Information Hiding
    • 5. Inheritance
    • 6. Associations
    • 7. Functions
    • 8. Overloading
    • 9. Classes
    • 10. Attributes
    • 11. Methods
    • 12. Inheritance & Polymorphism
    • 13. Static and Abstract
    • 14. Object Oriented Programming Summary
  • 3. Introduction to Data Structures & Algorithms
    • 1. Data Structures
    • 2. Linear Structures
    • 3. Lists
    • 4. Stacks and Queues
    • 5. Sets
    • 6. Maps
    • 7. Non-Linear Structures
    • 8. Graphs
    • 9. Trees
    • 10. Heaps
    • 11. Algorithms
    • 12. Brute Force
    • 13. Divide and Conquer
    • 14. Greedy
    • 15. Recursion
    • 16. Graph Traversal
    • 17. Programming by Contract
    • 18. Preconditions
    • 19. Postconditions
    • 20. Unit Testing
    • 21. Data Structures & Algorithms Summary
  • 4. Lists
    • 1. What is a Stack?
    • 2. Stacks in the Real World
    • 3. Stacks in Code
    • 4. Stack Operations
    • 5. Using a Stack
    • 6. Path Finding Algorithm
    • 7. What is a Queue?
    • 8. Queues in the Real World
    • 9. Queues in Code
    • 10. Using Operations
    • 11. Using a Queue
    • 12. Windshield Station Example
    • 13. What is a List?
    • 14. Lists in the Real World
    • 15. Lists in Code
    • 16. Doubly Linked Lists
    • 17. List Iterators
    • 18. List-Based Queues
    • 19. Lists Summary
  • 5. Recursion
    • 1. Introducing Recursion
    • 2. Example: Reversing a String
    • 3. Implementing Recursion
    • 4. Example: Factorials
    • 5. Tree Recursion
    • 6. Example: Fibonacci Numbers
    • 7. Example: Tower of Hanoi
    • 8. Converting Recursion to Iteration
    • 9. Recursion Summary
  • 6. Searching & Sorting
    • 1. Searching
    • 2. Linear Search
    • 3. Searching for a Value
    • 4. Searching for the Last Value
    • 5. Recursive Linear Search
    • 6. Searching for a Minimum
    • 7. Linear Search Time Complexity
    • 8. Sorting
    • 9. Selection Sort
    • 10. Selection Sort Pseudocode
    • 11. Selection Sort Time Complexity
    • 12. Bubble Sort
    • 13. Bubble Sort Pseudocode
    • 14. Bubble Sort Time Complexity
    • 15. Merge Sort
    • 16. Merge Sort Pseudocode
    • 17. Merge Sort Time Complexity
    • 18. Quicksort
    • 19. Quicksort Pseudocode
    • 20. Quicksort Time Complexity
    • 21. Performance of Sorting Algorithms
    • 22. Binary Search
    • 23. Iterative Binary Search
    • 24. Recursive Binary Search
    • 25. Binary Search Time Complexity
    • 26. The Importance of Sorting
    • 27. Searching & Sorting Summary
  • 7. Hash Tables
    • 1. What are Hash Tables?
    • 2. Hash Tables in Code
    • 3. Hash Functions
    • 4. Tuples
    • 5. Hash Table Operations
    • 6. Hash Table Based Sets
    • 7. Hash Tables Summary
  • 8. Performance & String Builder
    • 1. Choosing the Right Structures
    • 2. Data Structure Performance
    • 3. Comparing Data Structures
    • 4. Lists
    • 5. Hash Tables
    • 6. Algorithms
    • 7. Choosing an Algorithm
    • 8. Data Structure Uses
    • 9. Python Standard Types
    • 10. String Builder
    • 11. Theory
    • 12. Memory Example
    • 13. Limitations in Python
    • 14. Summary
  • 9. Trees
    • 1. Introduction
    • 2. General Terms
    • 3. What Makes a Tree a Tree
    • 4. Tree Operations
      • 5. Tree UML videos
    • 5. Terms I
    • 6. Terms II
    • 7. Terms III
    • 8. Binary Tree
    • 9. Binary Tree Examples
    • 10. Binary Tree Traversals
    • 11. In-Order Traversal
    • 12. Balance
    • 13. Summary
  • 10. Graphs
    • 1. Introduction
    • 2. Terms I
    • 3. Graph Features
    • 4. Weighted Graphs
    • 5. Directed Graphs
    • 6. Example
    • 7. Matrix Representation
    • 8. Introduction
    • 9. List Representation
    • 10. Dense VS Sparse
    • 11. List Graph UML
    • 12. Summary
  • 11. Graph Algorithms
    • 1. Introduction
    • 2. Depth First
    • 3. Breadth First
    • 4. Limitations
    • 5. Pathfinding
    • 6. In Practice
    • 7. MST Introduction
    • 8. Minimum Spanning Trees
    • 9. Kruskal
    • 10. Prim
    • 11. Traveling Salesperson
  • 12. Priority Queues
    • 1. Introduction
    • 2. Node Relationships
    • 3. Priority Queues
    • 4. Dijkstras
  • 13. Performance
    • 1. Introduction
    • 2. Trees
    • 3. Graphs
    • 4. Priority Queues
    • 5. Summary 1
    • 6. Tree Algorithms
    • 7. Graph Algorithms
    • 8. Summary 2
  • 14. Requirements Analysis
    • 1. Intro
    • 2. Types of Data
    • 3. Trees
    • 4. Graphs
    • 5. Priority Queues
    • 6. Examples

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