Linked List, DSA Complete Syllabus

Course Curriculum: Mastering Linked List Data Structure and Algorithms

This comprehensive course covers every aspect of linked lists, from the basics to advanced concepts and applications. By the end of this course, learners will have mastered linked lists and be equipped to handle both theoretical and practical challenges involving this versatile data structure.

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Module 1: Introduction to Linked Lists

1. Understanding Data Structures
   • Overview of Linear and Non-linear Data Structures.
   • Linked lists vs Arrays.
2. What is a Linked List?
   • Definition and basic structure.
   • Nodes, pointers, and dynamic memory allocation.
3. Types of Linked Lists
   • Singly Linked List.
   • Doubly Linked List.
   • Circular Linked List.
4. Real-world Applications of Linked Lists
   • Implementation of stacks and queues.
   • Dynamic memory management.
   • Hash maps (separate chaining).
5. Environment Setup
   • Tools and programming environments for linked list practice.

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Module 2: Implementing Linked Lists

1. Node Structure
   • Definition of a node.
   • Creating nodes in memory.
2. Singly Linked List
   • Representation and traversal.
   • Insertion at head, tail, and any position.
   • Deletion from head, tail, and any position.
3. Doubly Linked List
   • Structure and traversal in both directions.
   • Insertion and deletion operations.
4. Circular Linked List
   • Representation and traversal.
   • Operations: insertion and deletion.
5. Memory Allocation and Deallocation
   • Dynamic memory management in linked lists.
   • Preventing memory leaks.

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Module 3: Basic Operations and Applications

1. Linked List Traversal
   • Iterative traversal.
   • Recursive traversal.
2. Length of a Linked List
   • Finding length using iteration and recursion.
3. Search in a Linked List
   • Linear search.
   • Recursive search.
4. Reversing a Linked List
   • Iterative and recursive methods.
5. Merging Two Linked Lists
   • Merging sorted and unsorted lists.
6. Middle Element of a Linked List
   • Efficient methods using slow and fast pointers.

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Module 4: Advanced Operations

1. Detecting and Removing a Loop
   • Techniques to detect loops (Floyd's Cycle Detection Algorithm).
   • Breaking loops in a linked list.
2. Intersection of Two Linked Lists
   • Finding intersection points.
   • Optimized approaches using hashing or two-pointer technique.
3. Nth Node from the End
   • Using two-pointer and iterative methods.
4. Sorting a Linked List
   • Merge sort on linked lists.
   • Quick sort on linked lists.
5. Cloning a Linked List
   • With and without random pointers.
6. Flattening a Multi-level Linked List
   • Recursive and iterative approaches.

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Module 5: Specialized Linked Lists

1. Skip Lists
   • Concept and applications in search operations.
   • Implementation and traversal.
2. Self-adjusting Linked Lists
   • Move-to-front heuristic.
   • Transpose and frequency count methods.
3. Unrolled Linked Lists
   • Efficient representation for large data blocks.
   • Real-world use cases.
4. XOR Linked Lists
   • Memory-efficient linked lists.
   • Implementation and traversal.
5. Multi-linked Lists
   • Representation and real-world applications.

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Module 6: Variants and Optimizations

1. Doubly Circular Linked List
   • Traversal and operations.
   • Applications in real-world systems.
2. Sparse Matrix Representation
   • Using linked lists for sparse data storage.
3. Partitioning a Linked List
   • Segregating even and odd nodes.
   • Rearranging based on pivot elements.
4. Handling Large Data
   • Optimizing traversal for large linked lists.
   • Memory management techniques.

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Module 7: Linked Lists in Complex Data Structures

1. Hashing with Linked Lists
   • Separate chaining.
   • Applications in hash maps.
2. Adjacency List Representation
   • Graph representation using linked lists.
   • BFS and DFS with adjacency lists.
3. Trie Data Structure
   • Role of linked lists in Tries.
   • Optimizing Tries for memory efficiency.
4. Custom Data Structures
   • Design patterns using linked lists.
   • Implementation in stacks and queues.

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Module 8: Practical Projects and Case Studies

1. Text Editor Implementation
   • Using linked lists for text storage and editing.
2. Music Playlist Manager
   • Circular doubly linked list for playlist management.
3. Custom Memory Allocator
   • Using linked lists to manage free and allocated memory blocks.
4. Sparse Matrix Operations
   • Efficient storage and operations with linked lists.

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Module 9: Competitive Programming with Linked Lists

1. Common Linked List Problems
   • Practice problems from platforms like Codeforces, LeetCode, and HackerRank.
2. Problem-Solving Techniques
   • Identifying linked list-based solutions.
   • Debugging common errors.
3. Optimizing Time and Space
   • Efficient use of memory.
   • Optimized algorithms for common operations.

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Module 10: Advanced Real-world Applications

1. Database Systems
   • Linked lists in indexing and transaction logs.
2. Operating Systems
   • Process scheduling using circular linked lists.
   • Memory management applications.
3. Network Simulations
   • Linked list in packet queue management.
   • Dynamic routing table implementations.
4. Machine Learning and AI
   • Using linked lists for data preprocessing.
   • Applications in neural networks and decision trees.

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Module 11: Final Assessment and Mastery

1. Comprehensive Coding Projects
   • Implementing a file system using linked lists.
   • Designing a task scheduler.
2. Capstone Project
   • Develop a real-world application or library centered around linked lists.
3. Final Examination
   • Theory and practical coding exam to assess mastery.
4. Feedback and Next Steps
   • Personalized feedback for improvement.
   • Recommendations for further study and advanced topics.

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This syllabus ensures complete mastery of linked lists, covering theoretical concepts, practical applications, and real-world use cases. It is designed for learners who wish to gain a thorough understanding of linked lists and their applications in software development.