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This comprehensive course teaches data structures and algorithms using Python, starting from the basics and progressing to more advanced problem-solving techniques. It is designed for beginners who want to strengthen their programming and algorithmic thinking skills.
The course begins with an introduction to time and space complexity, also known as Big O notation, which helps you analyze how efficient your code is. You will then learn about Python basics to ensure you have the foundation needed for the rest of the course.
Next, you will explore essential data structures such as static and dynamic arrays, as well as strings, and understand how they work in memory. The course then covers linked lists, including singly and doubly linked lists, which are important for dynamic data management.
You will also study hash tables, sets, and maps, which allow fast data lookup and storage. Additional topics include stacks and queues for structured data processing, recursion for solving problems through self-repetition, and binary search for efficient searching techniques.
Finally, you will learn about binary trees and binary search trees, which are fundamental structures used in many advanced algorithms.
By the end of this course, you will have a strong foundation in DSA and be able to solve coding problems efficiently using Python.