DSA with C++ & Python Programming by Aravind choudhary

DSA with C++ & Python Programming is a practical and comprehensive guide to learning Data Structures and Algorithms using C++ and Python. The book combines programming fundamentals with essential data structures, algorithmic techniques, and problem-solving strategies to help readers develop strong programming and computational thinking skills. Starting with C++ and Python programming fundamentals, the book gradually progresses to arrays, strings, collections, recursion, searching, sorting, linked lists, stacks, queues, hashing, trees, heaps, and graphs. The book also introduces the C++ Standard Template Library (STL) and Python's built-in data structures and collections. Advanced algorithmic techniques such as divide and conquer, greedy algorithms, dynamic programming, recursion and backtracking, and graph algorithms are explained with practical examples. With coding examples in both C++ and Python, problem-solving exercises, and real-world applications, this book is designed for students, programmers, developers, and interview candidates who want to strengthen their DSA skills using two powerful programming languages. What You Will Learn C++ Programming Fundamentals Python Programming Fundamentals Variables, Data Types, and Operators Conditional Statements and Loops Functions and Methods Arrays and Multidimensional Arrays Strings and String Manipulation Pointers and References in C++ Dynamic Memory Management Classes and Objects in C++ Object-Oriented Programming Constructors and Destructors Encapsulation, Inheritance, and Polymorphism Templates and Exception Handling Python Lists, Tuples, Sets, and Dictionaries List and Dictionary Comprehensions Object-Oriented Programming with Python Introduction to Data Structures Abstract Data Types Algorithm Fundamentals Problem-Solving Techniques Time and Space Complexity Big-O, Big-Theta, and Big-Omega C++ Standard Template Library (STL) Vector, List, Deque, Stack, and Queue Set, Map, Multiset, and Multimap Priority Queue Iterators and STL Algorithms Python Collections and Built-in Data Structures Arrays and Array-Based Problems Searching Algorithms Linear Search Binary Search Sorting Algorithms Bubble Sort Selection Sort Insertion Sort Merge Sort Quick Sort Heap Sort Linked Lists Singly Linked Lists Doubly Linked Lists Circular Linked Lists Stack Data Structure Stack Using Arrays and Linked Lists Applications of Stacks Queue Data Structure Circular Queue Priority Queue Deque Hashing and Hash Tables HashMap, HashSet, and Python Dictionaries Collision Handling Trees and Tree Terminology Binary Trees Binary Search Trees Tree Traversal Techniques Heaps and Priority Queues Min Heap and Max Heap Graph Data Structures Graph Representation Breadth-First Search (BFS) Depth-First Search (DFS) Shortest Path Algorithms Minimum Spanning Tree Recursion and Backtracking Divide and Conquer Greedy Algorithms Dynamic Programming Memoization and Tabulation Algorithm Optimization Competitive Programming Fundamentals Coding and Interview Problems Real-World Applications of Data Structures and Algorithms