Dijkstra's and Bellman-Ford: Shortest Path Algorithms Explained

Finding the most efficient path through a network is a fundamental challenge in computer science, powering everything from map navigation to internet routing. This course demystifies Dijkstra's and Bellman-Ford algorithms, breaking down complex graph theory into easy-to-digest written explanations and logical steps. You will transition from a beginner to confidently analyzing and implementing single-source shortest path algorithms, understanding how to represent graphs in code, trace algorithm execution, and choose the right approach based on graph constraints like negative edge weights. What you'll learn: - Understand core graph theory concepts, including vertices, edges, weights, and directed versus undirected graphs. - Implement Dijkstra's algorithm using priority queues to find the shortest path in non-negative weighted graphs. - Apply the Bellman-Ford algorithm to handle graphs with negative edge weights and successfully detect negative cycles. - Analyze the time and space complexity of both algorithms to make optimal design choices for real-world scenarios. - Practice tracing algorithms manually with clear written walkthroughs and writing structured code representations. The course begins with foundational graph terminology and basic representations before guiding you through the step-by-step logic, pseudocode, and code implementation of both Dijkstra's and Bellman-Ford algorithms. It is designed for beginner programmers, computer science students, and self-taught developers looking to strengthen their algorithmic problem-solving skills with no advanced prerequisites required. Start reading today to master the core algorithms that power modern routing and navigation systems.