Foundations of Algorithms Masterclass
Beginner
5h
By: Shaun Pelling
Overview
The Foundations of Algorithms Masterclass offers a practical, language-agnostic introduction to algorithm fundamentals. It starts with the basics of algorithm structure and pseudocode, then moves into efficiency analysis using Big O notation. The course covers recursion, memoization, and space/time complexity. Learners explore search and sorting algorithms through both theory and implementation. A toolkit of advanced problem-solving techniques is included, followed by hands-on coding challenges.
Modules
1. Introduction
1.1 Introduction to Algorithms2 min
1.2 What is an Algorithm?9 min
1.3 Using Pseudocode to Help Solve Problems6 min
1.4 VS Code Setup & Course Files2 min
2. Algorithm Efficiency & Big O Notation
2.1 Introduction to Time Complexity5 min
2.2 Introduction to Big O Notation3 min
2.3 Constant Time Complexity5 min
2.4 Linear Time Complexity4 min
2.5 Quadratic Time6 min
2.6 CHALLENGE - Time Complexity Quiz1 min
2.7 SOLUTION - Time Complexity Quiz5 min
2.8 Logarithmic Time9 min
2.9 CHALLENGE - Only Positive Numbers2 min
2.10 SOLUTION - Only Positive Numbers4 min
2.11 CHALLENGE - Staircase Problem4 min
2.12 SOLUTION - Staircase Problem11 min
2.13 Arrays & Objects5 min
2.14 Space Complexity3 min
3. Recursion
3.1 Introduction to Recursion4 min
3.2 ASIDE - The Call Stack6 min
3.3 Recursion Example7 min
3.4 CHALLENGE - Recursive Fibonacci1 min
3.5 SOLUTION - Recursive Fibonacci5 min
3.6 Time Complexity of Recursive Algorithms3 min
3.7 Introduction to Memoization2 min
3.8 Adding Memoization to a Recursive Algorithm8 min
3.9 CHALLENGE - Memoization Staircase
3.10 SOLUTION - Memoization Staircase2 min
3.11 Space Complexity with Recursion2 min
4. Search Algorithms
4.1 Introduction to Search Algorithms2 min
4.2 Linear Search Theory1 min
4.3 Linear Search Implementation4 min
4.4 Binary Search Theory3 min
4.5 Binary Search Implementation9 min
4.6 CHALLENGE - Recursive Binary Search2 min
4.7 SOLUTION - Recursive Binary Search4 min
5. Sorting Algorithms
5.1 Introduction to Sorting1 min
5.2 Bubble Sort Theory4 min
5.3 Bubble Sort Implementation6 min
5.4 CHALLENGE - Optimizing Bubble Sort3 min
5.5 SOLUTION - Optimizing Bubble Sort4 min
5.6 Selection Sort Theory2 min
5.7 CHALLENGE - Selection Sort Implementation1 min
5.8 SOLUTION - Selection Sort Implementation8 min
5.9 Merge Sort Theory4 min
5.10 Merging Two Arrays Together11 min
5.11 CHALLENGE - Merge Sort Implementation2 min
5.12 SOLUTION - Merge Sort Implementation9 min
6. The Algorithm Solver's Toolbelt
6.1 Divide & Conquer7 min
6.2 Dynamic Programming11 min
6.3 Frequency Counting8 min
6.4 Multiple Pointers5 min
6.5 Sliding Window10 min
7. Algorithm Challenges
7.1 Challenges Introduction1 min
7.2 CHALLENGE - Greatest Common Divisor5 min
7.3 SOLUTION - Greatest Common Divisor5 min
7.4 CHALLENGE - Cartesian Product1 min
7.5 SOLUTION - Cartesian Product3 min
7.6 CHALLENGE - Palindromes1 min
7.7 SOLUTION - Palindromes3 min
7.8 CHALLENGE - Longest Substring2 min
7.9 SOLUTION - Longest Substring8 min
7.10 CHALLENGE - Minimum Coin Change4 min
7.11 SOLUTION - Minimum Coin Change11 min
7.12 Wrap Up1 min
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