This course path focuses on the algorithms and data structures that form the foundation of many programming interviews and practical software engineering tasks. It is designed for learners who already have some Python experience and want to strengthen their problem-solving skills. You will work with graphs, trees, linked lists, stacks, queues, heaps, dictionaries, sets, and hashing. Along the way, you will practice traversal strategies such as breadth-first search and depth-first search, compare sorting and searching techniques, and reason about time and space complexity. By the end of the path, you will be better prepared to recognize which data structure or algorithm fits a given problem, implement it in Python, and explain the reasoning behind your solution clearly.
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Syllabus
- Implement graph representations using adjacency lists and adjacency matrices
- Apply breadth-first search and depth-first search to graph and tree problems
- Build and use binary trees, binary search trees, heaps, linked lists, stacks, and queues
- Analyze time and space complexity for common data structures and algorithms
- Compare sorting and searching algorithms and choose appropriate approaches
- Use hashing, dictionaries, and sets to solve algorithmic problems efficiently
- Explain solution strategies for interview-style coding challenges