Data Structures and Algorithm Design using Python

Data Structures and Algorithm Design using Python

By CLCODING

Master the foundations of computer science with real-world Python examples.

Whether you're preparing for coding interviews, pursuing academic success, or simply strengthening your problem-solving skills, this book is your complete guide to data structures, algorithmic thinking, and Python programming. Designed for learners at all levels, it blends theory with practical implementation to help you build efficient and scalable programs.

🔍 What’s Inside:

✅ Introduction to Python & Algorithmic Thinking
Refresher on Python basics, Big-O notation, recursion, and iterative logic to lay a solid foundation.

✅ Linear & Linked Data Structures
Work with arrays, lists, stacks, queues, and all types of linked lists, along with real-world use cases.

✅ Recursion & Backtracking
Dive into recursion, tail recursion, and solve classic problems like N-Queens and maze traversal.

✅ Trees & Advanced Tree Structures
Understand binary trees, BSTs, AVL trees, heaps, and use them in applications like expression parsing and Huffman coding.

✅ Hashing & Dictionaries
Learn how Python dictionaries work under the hood, handle collisions, and explore efficient hash table strategies.

✅ Graph Algorithms
Build graphs and implement BFS, DFS, shortest paths (Dijkstra’s, Bellman-Ford), spanning trees, and more.

✅ Sorting & Searching Techniques
From basic sorts to quicksort, mergesort, heapsort, and counting/radix sort, with complexity breakdowns.

✅ Greedy, Divide & Conquer, and Dynamic Programming
Understand key algorithm design strategies with practical examples: LCS, Knapsack, Coin Change, and Matrix Chain Multiplication.

✅ Algorithm Design Patterns
Master brute force, greedy methods, dynamic programming, backtracking, and branch & bound strategies.

✅ Real-World Case Studies & Interview Practice
Includes challenges from platforms like LeetCode and HackerRank, Pythonic optimization tips, and mock interview questions.

Bonus Appendices:
Python libraries (collections, heapq, bisect), asymptotic analysis cheat sheets, and graded practice problems with solutions.

Data Structures and Algorithm Design using Python is more than just a textbook—it's your learning companion for developing efficient, real-world Python solutions.