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JavaScript Algorithms - The Fundamentals
Getting Started
Welcome to the Course! (0:58)
What & Why (6:42)
Join the Learning Community
Measuring Algorithm Performance & Time Complexity (9:31)
Big O Notation (6:57)
Deriving the Time Complexity / Big O of an Algorithm (11:27)
Constant Time (4:50)
Using Big O For Algorithm Comparison (3:42)
A First Task! (2:13)
Solution & A Gotcha (10:01)
About this Course & Outline (5:30)
Module Resources
The Academind Pro Referral Program
Math Algorithms & Practicing The Basics
Module Introduction (1:38)
The Fibonacci Problem (3:30)
The Fibonacci Solution (5:42)
Fibonacci Big O (Time Complexity) (4:17)
The "Is Prime" Problem (2:33)
The "Is Prime" Solution (3:56)
"Is Prime", Big O & Multiple Cases (12:48)
"Is Prime" - Improved Version (6:44)
Time to Practice (Problem) (1:27)
Time to Practice (Solution) (12:50)
Identifying Big O Quickly (5:53)
Is Power Of Two Algorithm (8:06)
Logarithmic Time Complexity (7:29)
Bitwise Operators & Power Of Two (8:19)
Again: Identifying Big O Quickly (2:50)
The Factorial Algorithm (5:12)
Module Resources
Recursion & Dynamic Programming
Module Introduction (1:06)
Recursion in Algorithms (8:30)
Exponential Time Complexity (11:30)
Quadratic Time Complexity vs Exponential Time Complexity (5:08)
What is "Dynamic Programming"? (3:25)
"Dynamic Programming" in Action (9:22)
The "Bottom Up" Approach (4:37)
Module Resources
Search Algorithms
Module Introduction (2:04)
What Search Algorithms Are About (1:19)
Introducing Linear Search (1:41)
Linear Search in Action (10:39)
Linear Search Time Complexity (4:21)
Binary Search in Theory (2:50)
Binary Search in Action (11:46)
Binary Search Time Complexity (3:20)
Recursive Binary Search (13:05)
The Master Theorem (10:39)
Module Resources
Sorting Algorithms
Module Introduction (0:52)
What are Sorting Algorithms About? (1:11)
Bubble Sort - Theory (5:07)
Bubble Sort in Action (17:31)
Bubble Sort Time Complexity (3:41)
Quicksort - Theory (2:55)
Quicksort in Action (13:14)
Quicksort Time Complexity (8:04)
Merge Sort - Theory (4:09)
Merge Sort in Action (16:38)
Merge Sort Time Complexity (4:01)
Summary (2:04)
Module Resources
Space Complexity
Module Introduction (1:13)
Introducing Space Complexity (3:02)
Deriving Space Complexity (2:39)
Factorial Algorithm (Loop) - Space Complexity (5:06)
Factorial Algorithm (Recursive) - Space Complexity (3:58)
Linear Search - Space Complexity (3:23)
Binary Search - Space Complexity (2:24)
Bubble Sort - Space Complexity (2:04)
Quicksort - Space Complexity (6:00)
Merge Sort - Space Complexity (2:13)
Module Resources
Sets (Array) Algorithms
Module Introduction (1:50)
An Introduction to Sets (3:17)
The Cartesian Product Algorithm (5:11)
Cartesian Product - Time Complexity (5:10)
The Cartesian Product Algorithm - Without Limits (16:37)
The Permutations Algorithms (3:27)
Permutations without Repetitions (19:00)
Understanding Permutations (4:44)
Permutations without Repetitions - Big O (3:53)
Permutations WITH Repetitions (15:15)
Module Resources
More Complex Algorithms & How To Solve Code Problems
Module Introduction (1:07)
Solving Problems In A Structured Way (7:06)
Simplifying Problems (4:00)
Practice Makes Perfect! (1:35)
The Knapsack Problem (0/1) (1:47)
A Wrong Approach (5:21)
Approaching the Problem Differently (5:26)
A Working Knapsack Solution (18:21)
An Improved Knapsack Algorithm (14:47)
Greedy vs Dynamic Algorithms (3:48)
A Greedy Knapsack Algorithm (9:46)
A New Problem Solving Plan (2:50)
The Change Making Problem (3:31)
A Greedy Change Making Algorithm (12:40)
A Variation to the Change Making Problem (13:17)
Module Resources
Roundup & Next Steps
Course Roundup (6:23)
Permutations without Repetitions - Big O
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