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💻 Introduction
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⌨️ Timestamps
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⌨️ Script and Visuals
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⌨️ References + Research
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⌨️ Questions
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⌨️ Shameless Plug
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⌨️ What are Data Structures?
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⌨️ Series Overview
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💻 Measuring Efficiency with BigO Notation
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⌨️ Time Complexity Equations
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⌨️ The Meaning of BigO
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⌨️ Why BigO?
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⌨️ Quick Recap
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⌨️ Types of Time Complexity Equations
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⌨️ Final Note on Time Complexity Equations
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💻 The Array
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⌨️ Array Basics
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⌨️ Array Names
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⌨️ Parallel Arrays
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⌨️ Array Types
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⌨️ Array Size
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⌨️ Creating Arrays
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⌨️ Populate-First Arrays
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⌨️ Populate-Later Arrays
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⌨️ Numerical Indexes
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⌨️ Replacing information in an Array
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⌨️ 2-Dimensional Arrays
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⌨️ Arrays as a Data Structure
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⌨️ Pros and Cons
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💻 The ArrayList
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⌨️ Structure of the ArrayList
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⌨️ Initializing an ArrayList
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⌨️ ArrayList Functionality
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⌨️ ArrayList Methods
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⌨️ Add Method
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⌨️ Remove Method
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⌨️ Get Method
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⌨️ Set Method
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⌨️ Clear Method
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⌨️ toArray Method
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⌨️ ArrayList as a Data Structure
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⌨️ Comparing and Contrasting with Arrays
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💻 The Stack
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⌨️ The Different types of Data Structures
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⌨️ Random Access Data Structures
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⌨️ Sequential Access Data Structures
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⌨️ Stack Basics
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⌨️ Common Stack Methods
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⌨️ Push Method
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⌨️ Pop Method
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⌨️ Peek Method
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⌨️ Contains Method
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⌨️ Time Complexity Equations
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⌨️ Uses for Stacks
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💻 The Queue
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⌨️ Queue Basics
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⌨️ Common Queue Methods
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⌨️ Enqueue Method
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⌨️ Dequeue Method
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⌨️ Peek Method
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⌨️ Contains Method
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⌨️ Time Complexity Equations
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⌨️ Common Queue Uses
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💻 The Linked List
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⌨️ LinkedList Visualization
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⌨️ Adding and Removing Information
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⌨️ Time Complexity Equations
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⌨️ Uses for LinkedLists
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💻 The Doubly-LinkedList
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⌨️ Visualization
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⌨️ Adding and Removing Information
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⌨️ Time Complexity Equations
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⌨️ Uses of a Doubly-LinkedList
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💻 The Dictionary
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⌨️ Dictionary Basics
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⌨️ Indexing Dictionaries
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⌨️ Dictionary Properties
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💻 Hash Table Mini-Lesson
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⌨️ Time Complexity Equations
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💻 Trees
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⌨️ Introduction to Hierarchical Data
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⌨️ Formal Background on the Tree
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⌨️ Tree Terminology and Visualization
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⌨️ Different types of Trees
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⌨️ Uses for the Tree
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💻 Tries
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⌨️ Trie Basics
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⌨️ Trie Visualization
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⌨️ Flagging
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⌨️ Uses for Tries
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💻 Heaps
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⌨️ Heap Basics
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⌨️ Min-Heaps
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⌨️ Max-Heaps
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⌨️ Building Heaps
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⌨️ Deleting from Heaps
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⌨️ Heap Implementations
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💻 Graphs
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⌨️ Graph Basics
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⌨️ Directed vs. Undirected Graphs
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⌨️ Cyclic vs. Acyclic Graphs
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⌨️ Weighted Graphs
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⌨️ Types of Graphs
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💻 Conclusion
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💻 Shameless Plug
Description:
Dive into a comprehensive 3-hour lecture-style course on data structures in computer science. Explore the fundamentals of data structures, learn how to measure their efficiency using Big O notation, and delve into 12 of the most common data structures essential for any computer science journey. Cover arrays, ArrayLists, stacks, queues, linked lists, doubly-linked lists, dictionaries, hash tables, trees, tries, heaps, and graphs. Gain insights into their structure, implementation, time complexity, and real-world applications. Perfect for beginners and those looking to solidify their understanding of these crucial computer science concepts.

An Introduction to Data Structures

Coding Tech
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#Computer Science #Algorithms and Data Structures #Data Structures #Hash Tables #Stacks #Queues #Linked Lists #Doubly Linked List
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💻 Introduction