Publisher's Synopsis
What You Will Learn in This Book
- Master 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
