What You Will Learn in This BookMaster the foundational concepts of Data Structures and Algorithms (DSA), including performance analysis using Big O notation and choosing the right tools for the job.Leverage Python's capabilities for DSA implementation, from built-in types to advanced object-oriented programming techniques and standard library modules like collections.Implement and analyze core data structures such as arrays, linked lists (singly, doubly, and circular), stacks, queues, and hash tables from scratch.Understand and apply tree-based data structures, including general trees, binary trees, Binary Search Trees (BSTs), and heaps, along with their practical applications in priority queues.Navigate and build graph-based solutions, learning different representations, traversal algorithms (BFS and DFS), and essential algorithms like Dijkstra's and Prim's for shortest paths and minimum spanning trees.Grasp fundamental algorithmic paradigms including brute force, greedy algorithms, divide and conquer, dynamic programming, and backtracking to solve a wide range of computational problems.Implement and compare various sorting and searching algorithms, understanding their efficiency trade-offs and Python's built-in optimized sorting methods.Solve complex string manipulation problems using advanced algorithms like KMP and Rabin-Karp for pattern matching.Bridge theory to practice by exploring real-world applications of DSA in areas like search engines, social networks, databases, and operating systems.Develop a strategic approach to problem-solving, enabling you to analyze problems, choose appropriate data structures and algorithms, and optimize solutions for efficiency.Prepare for technical interviews by understanding common interview questions and patterns related to DSA, and by building a strong portfolio of practical implementations
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