Basic Graph Algorithms in Python: Pathfinding and Network Optimization

Graph algorithms are the backbone of modern routing systems, logistics pipelines, and network designs. Understanding how to represent and traverse these structures is essential for solving complex pathfinding and optimization challenges. This text-only course guides you from the absolute basics of graph theory to implementing modified pathfinding algorithms in Python. You will learn how to model networks, minimize traversal costs, and solve real-world routing constraints with confidence. What you'll learn: - Understand core graph concepts, terminology, and representation methods like adjacency lists and matrices - Implement fundamental traversal algorithms including Breadth-First Search (BFS) and Depth-First Search (DFS) in Python - Master Dijkstra's algorithm and modify it to handle specific cost and hop constraints - Write clean, modern Python code using type hints and dataclasses to model graph structures - Analyze the time and space complexity of different pathfinding approaches - Apply graph-solving techniques to model and optimize network routing scenarios You will start with foundational definitions and data structures before progressing to hands-on algorithmic logic. Through clear written explanations and step-by-step code walkthroughs, you will build a solid intuition for network optimization. Designed for beginner developers and computer science enthusiasts, this course requires only a basic familiarity with Python variables and loops. Start reading today to build a strong foundation in graph-based problem-solving.