This course offers an in-depth exploration of graph algorithms, essential for solving complex problems in computer science, data analysis, and network design. Participants will learn about various types of graphs, fundamental concepts, and a range of algorithms used to traverse, search, and manipulate graph structures.
Key Topics Covered:
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Introduction to Graphs:
- Understanding graph theory fundamentals, including definitions, terminology, and types of graphs (directed, undirected, weighted, unweighted).
- Representation of graphs using adjacency lists, adjacency matrices, and edge lists.
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Graph Traversal Algorithms:
- Depth-First Search (DFS): Implementation, applications, and complexity analysis.
- Breadth-First Search (BFS): Implementation, applications, and complexity analysis.
- Comparison of DFS and BFS in various scenarios.
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Shortest Path Algorithms:
- Dijkstra’s Algorithm: Finding the shortest path in weighted graphs.
- Bellman-Ford Algorithm: Handling graphs with negative weights.
- Floyd-Warshall Algorithm: All-pairs shortest path solution.
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Minimum Spanning Tree (MST):
- Understanding the concept of minimum spanning trees.
- Prim’s Algorithm: Step-by-step implementation and applications.
- Kruskal’s Algorithm: Union-Find data structure and its role in MST.
By the end of this course, participants will have a solid understanding of graph algorithms and their applications, enabling them to tackle complex problems in various domains. This course is ideal for computer science students, software engineers, data scientists, and anyone interested in enhancing their algorithmic problem-solving skills.
- Teacher: Zaien Aji Trahutomo