Data Structures and Algorithms in Python is a comprehensive course designed to provide you with the foundational knowledge and skills needed to tackle complex programming challenges. This course covers everything from the basics of data structures and algorithms to advanced topics, ensuring you can apply these concepts effectively in real-world scenarios.
This course is ideal for aspiring software developers, computer science students, and anyone looking to enhance their problem-solving skills and understanding of data structures and algorithms. Beginners will find a structured approach to learning, while those with some experience can deepen their understanding and enhance their skills.
You will start with an introduction to data structures and algorithms, understanding their importance and key concepts like Big O notation. A Python basics refresher will ensure you are comfortable with Python syntax, functions, and modules.
The course covers essential data structures like arrays, lists, and linked lists, teaching you to create and manipulate these structures in Python. You'll explore stacks and queues, understanding their operations and applications, and dive into trees, including binary trees, binary search trees, and advanced tree structures.
Graph theory is another crucial area, where you'll learn about graph representations, traversal algorithms like DFS and BFS, and advanced graph algorithms such as Dijkstra's and Prim's. Hashing and hash tables will teach you about hash functions, collision resolution, and implementing hash tables in Python.
Sorting and searching algorithms are covered in detail, from basic algorithms like bubble sort and linear search to advanced techniques like quicksort, merge sort, and binary search. You'll also explore dynamic programming, understanding its principles and solving classic problems like the knapsack and longest common subsequence.