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Welcome to Week 10 Lecture 8 of the course "Mathematics for Data Science I" by Profs. Neelesh Upadhye, Madhavan Mukund. Full Course: https://study.iitm.ac.in/ds/course_pages/BSMA1001.html Video Overview This lecture revisits Breadth-First Search (BFS) and Depth-First Search (DFS), analyzing their performance with different graph representations: Adjacency Matrices and Adjacency Lists. We carefully examine the time complexity of BFS and DFS in each case, showing the trade-offs and highlighting why adjacency lists are often more efficient in bounded degree graphs. The lecture also discusses graph properties such as degrees, complete graphs, and how these affect algorithmic performance. By the end, you’ll understand the computational implications of choosing one representation over the other for graph algorithms. About IIT Madras' online Bachelor of Science programme IIT Madras offers four-year BS programmes that aim to provide quality education to all, irrespective of age, educational background, or location. The BS programme has multiple levels, which provide flexibility to students to exit at any of these levels. Depending on the courses completed and credits earned, the learner can receive a Foundation Certificate from IITM CODE (Centre for Outreach and Digital Education), Diploma(s) from IIT Madras, or BSc/BS Degrees from IIT Madras. For more details, visit: https://www.iitm.ac.in/academics/study-at-iitm/non-campus-bs-programmes #BFS #DFS #BreadthFirstSearch #DepthFirstSearch #GraphAlgorithms #AdjacencyMatrix #AdjacencyList #GraphRepresentation #TimeComplexity #AlgorithmAnalysis #GraphTheory #DataStructures #Degrees #CompleteGraph #BoundedDegree #Algorithms #ComputerScience #Lecture #Tutorial #GraphTraversal
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