Unit 1: Why Algorithms Matter
Unit 2: Understanding Big O Notation
Unit 3: Python's Built-in Data Structures
Python Data Structures & Algorithms for Backend Development & Data Engineering
Master fundamental data structures and algorithms in Python to build efficient, scalable solutions for backend systems and robust data engineering pipelines.
Unit 1: Arrays: The Foundation
Unit 2: Linked Lists: A Flexible Alternative
Unit 3: Doubly Linked Lists: Bi-Directional Power
Unit 1: Stack Fundamentals and Implementations
Unit 2: Stack Applications
Unit 3: Queue Fundamentals and Implementations
Unit 4: Queue Applications
Unit 1: Hashing Fundamentals
Unit 2: Building a Basic Hash Table
Unit 3: Collision Resolution Strategies
Unit 4: Performance and Applications
Unit 1: Tree Fundamentals
Unit 2: Binary Tree Basics
Unit 3: Binary Tree Traversal
Unit 4: Tree Operations & Analysis
Unit 1: BST Fundamentals and Structure
Unit 2: Core BST Operations
Unit 3: BST Performance and Balance
Unit 4: BST Applications
Unit 1: Heap Fundamentals
Unit 2: Implementing Heaps with Arrays
Unit 3: Priority Queues
Unit 4: Heap Applications
Unit 1: Foundations of Sorting
Unit 2: Simple Sorting Algorithms
Unit 3: Efficient Comparison Sorts
Unit 4: Heap Sort and Non-Comparison Sorts
Unit 5: Sorting Algorithm Comparison & Selection
Unit 1: Introduction to Searching
Unit 2: Divide and Conquer Paradigm
Unit 3: Binary Search: The Efficient Way
Unit 4: Applications and Comparison
Unit 1: Graph Basics: The Connected World
Unit 2: Representing Graphs in Python
Unit 3: Breadth-First Search (BFS)
Unit 4: Depth-First Search (DFS)
Unit 1: BFS & DFS in Action
Unit 2: Performance & Complexity
Unit 3: Real-World Graph Applications
Unit 4: Identifying Graph Scenarios
Unit 1: Mastering Recursion
Unit 2: Greedy Algorithms
Unit 3: Strategic Problem Solving