Data Structures and Algorithms with Python

Course Overview: This comprehensive course is designed to provide an in-depth understanding of Data Structures and Algorithms (DSA) using Python. It is tailored to equip learners with the foundational skills and practical knowledge needed to excel in solving complex computational problems. From the basics of arrays and lists to advanced topics like graph theory and hashing, this course covers all essential concepts with a strong focus on real-world applications.

Course Content:

• Overview of DSA: Understand the importance and practical applications of DSA in computer science and software engineering.
• Time and Space Complexity: Learn to evaluate algorithms with Big-O notation and analyze the best, average, and worst-case scenarios.
• Basic Data Structures: Explore the fundamental operations of arrays and lists, and delve deeper into the specifics of Python's lists and tuples, including slicing, indexing, and built-in functions.
• Stacks and Queues: Study the concept, implementation, and real-world applications of stacks using lists and queues using Python's collections deque.
• Linked Lists: Grasp the concept and operations of singly linked lists, and extend your knowledge to doubly linked lists and their operations.
• Trees and Tree Traversals: Gain insights into tree structures, including binary trees and binary search trees, and master tree traversal techniques such as inorder, preorder, and postorder.
• Graphs: Learn the basics of graph theory, including graph representations using adjacency matrices and lists.
• Sorting and Searching Algorithms: Get hands-on with popular sorting algorithms like Bubble Sort, Insertion Sort, Selection Sort, Quick Sort, and Merge Sort, along with searching techniques such as Linear Search and Binary Search.
• Hashing: Understand the principles of hashing, including hash tables and hash functions.

This course is ideal for students, professionals, and anyone looking to strengthen their problem-solving skills and prepare for technical interviews. With a blend of theoretical knowledge and practical coding exercises, you will be well-prepared to tackle a wide range of computational challenges.