This course introduces the fundamentals of data structures and algorithms using Python, focusing on the essential concepts needed for programming, problem-solving, and technical interviews.
The course begins with time and space complexity, explaining Big O notation and how to analyze algorithm efficiency. Learners understand how to evaluate performance based on input size and scalability.
It then covers static arrays, dynamic arrays, and strings, explaining how data is stored and manipulated in memory, along with their time complexity characteristics.
The course continues with linked lists, including both singly and doubly linked lists. It explains how nodes are connected dynamically and how linked lists differ from arrays in terms of flexibility and performance.
Next, it introduces hash tables, including hash functions, sets, and maps. This section explains how key-value storage works and why hash tables provide efficient average-time operations for searching, inserting, and deleting data.
The course also includes a full Python beginner section, helping learners build foundational programming skills before diving deeper into data structures.
By the end of this course, learners will have a strong understanding of core data structures, algorithm complexity, and Python-based implementation concepts essential for software development and coding interviews.
