Learning Data Structures and Algorithms

Video description

In this Learning Data Structures and Algorithms video training course, Rod Stephens will teach you how to analyze and implement common algorithms used in data processing. This course is designed for the absolute beginner, meaning no previous programming experience is required.

You will start by learning about the complexity theory, then jump into learning about numerical algorithms, including randomizing arrays, prime factorization, and numerical integration. From there, Rod will teach you about linked lists, such as singly linked lists, sorted, and doubly linked lists. This video tutorial also covers arrays, stacks and queues, and sorting. You will also learn about searching, hash tables, recursion, and backtracking algorithms. Finally, you will cover trees, balanced trees, decision trees, and network algorithms.

Once you have completed this video training course, you will be fully capable of analyzing and implementing algorithms, as well as be able to select the best algorithm for various situations. Working files are included, allowing you to follow along with the author throughout the lessons.

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Table of contents

  1. Chapter 1 - Introduction
    1. Introduction And Course Overview
    2. About The Author
  2. Chapter 2 - Complexity Theory
    1. Complexity Theory
    2. Big O Notation
    3. Typical Runtime Functions
    4. Comparing Runtime Functions
    5. P And NP
  3. Chapter 3 - Numerical Algorithms
    1. Random Numbers
    2. Linear Congruential Generators
    3. Randomizing Arrays - Part 1
    4. Randomizing Arrays - Part 2
    5. GCD
    6. LCM
    7. Prime Factorization - Part 1
    8. Prime Factorization - Part 2
    9. Finding Primes
    10. Testing Primality
    11. Numerical Integration
  4. Chapter 4 - Linked Lists
    1. Singly Linked Lists - Part 1
    2. Singly Linked Lists - Part 2
    3. Sorted Linked Lists
    4. Sorting With Linked Lists
    5. Doubly Linked Lists
  5. Chapter 5 - Arrays
    1. One-Dimensional Arrays
    2. Triangular Arrays - Part 1
    3. Triangular Arrays - Part 2
    4. Sparse Arrays - Part 1
    5. Sparse Arrays - Part 2
  6. Chapter 6 - Stacks And Queues
    1. Stacks
    2. Stack Algorithms
    3. Double Stacks
    4. Queues
  7. Chapter 7 - Sorting
    1. Sorting Algorithms
    2. Insertionsort
    3. Selectionsort
    4. Quicksort - Part 1
    5. Quicksort - Part 2
    6. Heapsort - Part 1
    7. Heapsort - Part 2
    8. Heapsort - Part 3
    9. Mergesort - Part 1
    10. Mergesort - Part 2
    11. Bubblesort - Part 1
    12. Bubblesort - Part 2
    13. Countingsort - Part 1
    14. Countingsort - Part 2
    15. Sorting Summary
  8. Chapter 8 - Searching
    1. Linear Search
    2. Binary Search
    3. Interpolation Search
  9. Chapter 9 - Hash Tables
    1. Hash Tables
    2. Chaining
    3. Open Addressing - Basics
    4. Open Addressing - Linear Probing
    5. Open Addressing - Quadratic Probing
    6. Open Addressing - Double Hashing
  10. Chapter 10 - Recursion
    1. Recursion Basics
    2. Fibonacci Numbers
    3. Tower Of Hanoi
    4. Koch Curves
    5. Hilbert Curves
    6. Gaskets
    7. Removing Tail Recursion
    8. Removing Recursion With Stacks
    9. Fixing Fibonacci
    10. Selections
    11. Permutations
  11. Chapter 11 - Backtracking Algorithms
    1. Backtracking
    2. The Eight Queens Problem - Part 1
    3. The Eight Queens Problem - Part 2
    4. The Eight Queens Problem - Part 3
    5. The Knights Tour
  12. Chapter 12 - Trees
    1. Tree Terms
    2. Binary Tree Properties
    3. Traversals - Preorder
    4. Traversals - Postorder
    5. Traversals - Inorder
    6. Traversals - Breadth-First
    7. Building Sorted Trees
    8. Editing Sorted Trees
  13. Chapter 13 - Balanced Trees
    1. Why Do You Need Balanced Trees?
    2. B-Trees - B-Tree Basics
    3. B-Trees - Adding Items
    4. B-Trees - Removing Items
  14. Chapter 14 - Decision Trees
    1. Definition
    2. Exhaustive Search
    3. Branch And Bound
    4. Heuristics
  15. Chapter 15 - Network Algorithms
    1. Network Terminology
    2. Network Classes
    3. Depth-First Traversal
    4. Breadth-First Traversal
    5. Spanning Trees - Part 1
    6. Spanning Trees - Part 2
    7. Shortest Paths - Part 1
    8. Shortest Paths - Part 2
  16. Chapter 16 - Wrap-Up
    1. Wrap-Up

Product information

  • Title: Learning Data Structures and Algorithms
  • Author(s):
  • Release date: February 2015
  • Publisher(s): Infinite Skills
  • ISBN: 9781771373470