Data Structures for Coding Interviews in Python

Module 1: Complexity Analysis

⏳ ~2 hours

• Topics: Asymptotic notation, loop analysis, nested behavior, complexity trade-offs.

• Hands-on: Compute Big‑O for various code snippets and solve complexity-specific quizzes.

Module 2: Lists & Arrays

⏳ ~4 hours

• Topics: Python list operations, slicing, in-place algorithms, and subarray manipulation.

• Hands-on: Solve problems such as two-sum, rotate list, and maximum subarray.

Module 3: Linked Lists

⏳ ~4 hours

• Topics: Singly and doubly linked list implementation, reversal, cycle detection, merging.

• Hands-on: Build core list features and solve interview-style list algorithm problems.

Module 4: Stacks, Queues & Deques

⏳ ~3 hours

• Topics: Stack/queue behavior, deque implementation, LRU cache design patterns.

• Hands-on: Implement data structures and solve stack/queue coding problems.

Module 5: Trees & Graphs

⏳ ~6 hours

• Topics: Binary tree/BST traversal, graph adjacency lists, BFS/DFS, connectivity.

• Hands-on: Code traversal methods and solve graph-based interview patterns.

Module 6: Heaps & Priority Queues

⏳ ~2 hours

• Topics: Heap operations, top‑K elements, heap‑based problem-solving.

• Hands-on: Build heap structures and apply them to interview-friendly tasks.

Module 7: Hash Maps & Sets

⏳ ~3 hours

• Topics: Dictionary internals, hash collisions, set use-cases, frequency counting.

• Hands-on: Implement hash-based problems like first unique, anagrams detection.

Module 8: Comprehensive Review & Mixed Challenges

⏳ ~5 hours

• Topics: Recap all data structures, complexity comparisons, review patterns.

• Hands-on: Tackle mixed-interview challenges and simulate timed assessments.

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