Algorithm

Binary Search

The classic O(log n) algorithm for finding a target in a sorted array using repeated halving, with correct boundary handling.

Heap Sort and Counting Sort

How heap sort uses a binary heap for guaranteed O(n log n) in-place sorting, and how counting sort achieves linear time for bounded integers.

Quicksort and Mergesort

Deep dive into two classic divide-and-conquer sorts: quicksort's in-place partitioning and mergesort's stable merging.

Searching Algorithms Comparison

Comparing linear search, binary search, and hash-based lookup across time complexity, prerequisites, and practical trade-offs.

Sorting Algorithms Overview

A survey of classic sorting algorithms, their complexities, stability, and when to choose each one.

Activity Selection Problem

Select the maximum number of non-overlapping activities from a schedule using a greedy earliest-finish-time strategy.

Algorithm Analysis and Complexity

Learn Big-O, Big-Omega, and Big-Theta notation to analyze and compare the time and space efficiency of algorithms.

Algorithm Complexity Cheat Sheet

A reference summary of time and space complexities for the major algorithms covered in this course.

Algorithm Design Paradigms Overview

A map of the major algorithm design paradigms, divide and conquer, greedy, dynamic programming, and backtracking, with canonical examples.

Common Algorithm Interview Questions

A curated set of frequently asked algorithm interview questions with clear, technically accurate answers.

Bellman-Ford Algorithm

A single-source shortest path algorithm that handles negative edge weights and detects negative-weight cycles.

Closest Pair of Points

Use divide and conquer with a strip-checking merge step to find the closest pair among n points in O(n log n).

The Divide and Conquer Paradigm

Learn how divide, conquer, and combine steps break large problems into smaller solvable subproblems.

Floyd-Warshall Algorithm

A dynamic-programming algorithm that computes shortest paths between every pair of vertices in O(V^3) time.

Fractional Knapsack Problem

Maximize the value of items packed into a capacity-limited knapsack when items can be split, using a greedy value-density strategy.

The Greedy Algorithm Paradigm

Learn how greedy algorithms build solutions one locally optimal choice at a time, and when that strategy actually yields a global optimum.

Huffman Coding

Build optimal prefix-free binary codes for data compression using a greedy, frequency-driven priority-queue algorithm.

Longest Palindromic Substring

Find the longest substring that reads the same forwards and backwards using the expand-around-center technique.

Network Flow Basics

An introduction to max-flow/min-cut and the Ford-Fulkerson and Edmonds-Karp methods for computing maximum flow.

The Quickselect Algorithm

Find the k-th smallest element in linear average time using a partition-based divide-and-conquer approach.

Rabin-Karp Algorithm

Search for a pattern in a text using rolling hashes to compare substrings in constant time on average.

Trie-Based String Algorithms

Learn how a trie (prefix tree) organizes strings for fast insertion, search, and prefix queries.

FCFS and SJF Scheduling

First-Come-First-Served and Shortest-Job-First scheduling, worked through Gantt charts with exact waiting/turnaround-time math.

Multilevel Queue Scheduling

How fixed-priority multilevel queues differ from adaptive multilevel feedback queues, and how each handles process movement.