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Graphs Data Structures Algorithms

Track :

Programming

Lessons no : 33

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What will you learn in this course?
  • Understand different types of graphs including directed, undirected, weighted, and unweighted graphs for real-world applications
  • Implement graph traversal algorithms such as BFS and DFS to solve complex problems efficiently
  • Apply shortest path algorithms like Dijkstra’s and Bellman-Ford for network routing and navigation systems
  • Analyze graph algorithms to determine their time and space complexity for optimized performance
  • Design and implement algorithms for minimum spanning trees using Prim’s and Kruskal’s methods
  • Utilize graph algorithms to solve problems in social networks, transportation, and data analysis
  • Identify and resolve common challenges in graph data structures such as cycles, connectivity, and bipartiteness
  • Develop skills to model real-world systems using graphs for effective data representation and problem-solving
  • Evaluate the suitability of different graph algorithms for specific scenarios and datasets
  • Enhance problem-solving skills by applying graph algorithms to complex, real-world data structures

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Lessons | 33


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A graph is a non-linear kind of data structure made up of nodes or vertices and edges. The edges connect any two nodes in the graph, and the nodes are also known as vertices .