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docs/roadmap/dsa/dsa.md
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# Table of Content
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1. [Language-Agnostic DSA Roadmap](#language-agnostic-dsa-roadmap)
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2. [Language-Agnostic DSA Resources](#language-agnostic-dsa-resources)
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# Language-Agnostic DSA Roadmap
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## Learning Path Visualization
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[](https://mermaid.live/edit#pako:eNp9kstuwjAQRX_F8hp-IItKIQ9YFBUprJqwGOIhsRTbkR9IFPHvdZyYLtrizdiec0dzx77TVjGkCe00jD055o0kfqV1ZUHbE1mv38imPmjl80Jw2ZENGN4a8nEhqbyRd5Cdgw5Ps24TBFkdIJKDBVJZ7VrrNJqFyQKTL0w6dEpz24uYzkO6qFN2Bdki-6dKEbDyB_tVqAzEdmr-PKAglRquk4EDWItaRmwbsF1djdhyGPiXr3VUo_fogRkx7jyPp6GlcpKB5Uo2dLE8B5TsDzxTGkmmfIOjNVGRLUZfCZ-25laitFisvZLuwXh_tyjZzmH3lNAVFagFcOaf_T5dN9T2KLChid8yvIAb7CR_eBScVdVNtjTxL4ArqpXr-nhwo58F5hym30GTCwzG344gP5WK58c3ZK7B-A)
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## Detailed Breakdown
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### Foundation (2-3 weeks)
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- Time & Space Complexity
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- Big O Notation
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- Memory concepts
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- Basic programming constructs
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- Problem-solving methodology
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### Core Concepts (8-10 weeks)
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1. Basic Data Structures
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- Arrays
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- Linked Lists
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- Stacks
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- Queues
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- Hash Tables
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- Basic Trees
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2. Basic Algorithms
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- Searching
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- Sorting
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- Recursion
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- Two Pointers
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- Sliding Window
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### Advanced Topics (10-12 weeks)
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1. Advanced Data Structures
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- Advanced Trees
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- Graphs
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- Heaps
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- Tries
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- Segment Trees
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- Bloom Filters
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2. Advanced Algorithms
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- Dynamic Programming
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- Greedy Algorithms
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- Backtracking
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- Graph Algorithms
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- String Algorithms
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### Mastery (Ongoing)
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1. Problem Solving Patterns
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- Pattern recognition
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- Optimization techniques
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- System design basics
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- Interview preparation
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2. Specialized Topics
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- Computational Geometry
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- Network Flow
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- Advanced String Algorithms
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- Parallel Algorithms
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# Language-Agnostic DSA Resources
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## Online Courses
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1. [Algorithms Part I - Princeton](https://www.coursera.org/learn/algorithms-part1)
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- Fundamental algorithms
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- Theoretical foundation
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- Programming assignments
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2. [Algorithm Specialization - Stanford](https://www.coursera.org/specializations/algorithms)
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- Comprehensive coverage
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- Advanced topics
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- Real-world applications
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## Books
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1. "Introduction to Algorithms" (CLRS)
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- Comprehensive coverage
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- Theoretical foundation
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- Problem sets
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2. "Algorithm Design Manual" by Skiena
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- Practical approach
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- Real-world examples
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- Problem-solving strategies
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3. "Grokking Algorithms" by Bhargava
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- Visual explanations
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- Simple examples
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- Beginner-friendly
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## Online Platforms
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1. [LeetCode](https://leetcode.com/)
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- Structured problems
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- Company-specific lists
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- Discussion forums
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2. [AlgoExpert](https://www.algoexpert.io/)
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- Curated problems
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- Video explanations
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- Interview preparation
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3. [InterviewBit](https://www.interviewbit.com/)
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- Programming interview focus
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- Company-wise problems
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- Mock interviews
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## Websites
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1. [Visualgo](https://visualgo.net/)
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- Algorithm visualization
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- Interactive learning
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- Step-by-step execution
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2. [USACO Guide](https://usaco.guide/)
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- Competitive programming
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- Comprehensive tutorials
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- Practice problems
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## YouTube Channels
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1. [Back To Back SWE](https://www.youtube.com/channel/UCmJz2DV1a3yfgrR7GqRtUUA)
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- Detailed explanations
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- Visual presentations
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- Interview preparation
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2. [Abdul Bari](https://www.youtube.com/channel/UCZCFT11CWBi3MHNlGf019nw)
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- Algorithm explanations
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- Mathematical approach
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- Theoretical foundation
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## Practice Platforms
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1. [AtCoder](https://atcoder.jp/)
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- Regular contests
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- Various difficulty levels
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- Active community
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2. [SPOJ](https://www.spoj.com/)
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- Classical problems
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- Judge system
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- Multiple languages
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## GitHub Resources
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1. [Coding Interview University](https://github.com/jwasham/coding-interview-university)
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- Complete study plan
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- Resource compilation
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- Interview preparation
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2. [JavaScript Algorithms](https://github.com/trekhleb/javascript-algorithms)
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- DSA implementations
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- Explanations
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- Examples
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166
docs/roadmap/dsa/dsaUsingC.md
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docs/roadmap/dsa/dsaUsingC.md
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# Table of Contents
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1. [C Language DSA Roadmap](#c-language-dsa-roadmap)
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2. [C Language DSA Resources](#c-language-dsa-resources)
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# C Language DSA Roadmap
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## Learning Path Visualization
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[](https://mermaid.live/edit#pako:eNqFUrluwzAM_RVBczL0mDwUcKxcQ4AA7lQ7A2MxtgFLCnQECIL8exUd7VC01SKR7_GJetSNdoojLWiv4TyQd9ZK4lfZ1Ba0PZD5_I0smoqsnOQgUFqYzCFyFgGsmh0Kpa9kBxJ6fFASXgWcNQswY0cYWCC11a6zTmPWYIGzbEp-Adkh_5O2SlLl1Cs92kFkeBng9bfKD8YqMmKwDsGm2Wt1nFCQWk2XUfaJugnotqmvxnqQoRl76bGIGneMTrV0P4BB8lT4h4a-TEuTMXFDyX-tei5ItC3XVP_XvPiblEbC6jJXpWkt0yP_13gtSDYpayRTNnHbfmnQGRWoBYzc_47bI91SO_gBt7TwR44ncJN9qNw9FZxV9VV2tPCzwxnVyvVDDtyZg0U2gm9G5OQZ5IdSPjz5L4X3TwxRxxs)
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## Detailed Breakdown
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### Phase 1: C Fundamentals (2-3 weeks)
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- Pointers and pointer arithmetic
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- Dynamic memory allocation
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- Structures and unions
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- File handling
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- Preprocessor directives
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- Makefile creation
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### Phase 2: Memory Management (2 weeks)
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- Stack vs Heap
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- Memory leaks
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- Buffer overflows
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- Pointer safety
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- Valgrind usage
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- GDB debugging
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### Phase 3: Core DSA (8-10 weeks)
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1. Basic Data Structures
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- Arrays and strings
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- Linked lists (single, double, circular)
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- Stacks
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- Queues
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- Hash tables
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2. Advanced Data Structures
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- Trees (Binary, BST, AVL)
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- Graphs (Adjacency matrix/list)
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- Heaps
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- Tries
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- Disjoint sets
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3. Basic Algorithms
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- Searching (Linear, Binary)
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- Sorting (Bubble, Selection, Insertion)
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- Recursion
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- Basic graph traversals
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### Phase 4: Advanced Topics (8-10 weeks)
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1. Advanced Algorithms
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- Advanced sorting (Quicksort, Mergesort, Heapsort)
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- Dynamic Programming
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- Greedy Algorithms
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- Advanced graph algorithms
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- String algorithms
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2. Problem Solving
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- LeetCode problems
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- Competitive programming
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- System design basics
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- Code optimization
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# C Language DSA Resources
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## Online Platforms
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1. [GeeksforGeeks C Programming](https://www.geeksforgeeks.org/c-programming-language/)
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- Extensive C tutorials
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- DSA implementations in C
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- Practice problems
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2. [CodeForces](https://codeforces.com/)
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- Competitive programming platform
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- Many solutions in C
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- Regular contests
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3. [HackerRank C Practice](https://www.hackerrank.com/domains/c)
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- Structured C programming tasks
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- Gradually increasing difficulty
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- Immediate feedback
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## Books
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1. "Data Structures Using C" by Reema Thareja
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- Comprehensive coverage
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- Practical examples
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- Exercise problems
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2. "The C Programming Language" by Kernighan and Ritchie
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- Fundamental C concepts
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- Written by C's creators
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- Essential reference
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3. "Mastering Algorithms with C" by Kyle Loudon
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- Focus on implementation
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- Performance analysis
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- Real-world applications
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## GitHub Repositories
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1. [C Data Structures](https://github.com/fragglet/c-algorithms)
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- Common DSA implementations
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- Well-documented code
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- Testing included
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2. [C Programming Resources](https://github.com/aleksandar-todorovic/awesome-c)
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- Curated list of resources
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- Frameworks and libraries
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- Learning materials
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## Interactive Learning
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1. [CS50x](https://cs50.harvard.edu/x/)
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- Harvard's intro course
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- Strong C foundation
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- Hands-on projects
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2. [Learn-C.org](https://www.learn-c.org/)
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- Interactive tutorials
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- Practice exercises
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- Immediate feedback
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## Online Platforms
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1. [LeetCode](https://leetcode.com/)
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- Structured problems
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- Company-specific lists
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- Discussion forums
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2. [AlgoExpert](https://www.algoexpert.io/)
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- Curated problems
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- Video explanations
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- Interview preparation
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3. [InterviewBit](https://www.interviewbit.com/)
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- Programming interview focus
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- Company-wise problems
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- Mock interviews
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## Websites
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1. [Visualgo](https://visualgo.net/)
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- Algorithm visualization
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- Interactive learning
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- Step-by-step execution
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2. [USACO Guide](https://usaco.guide/)
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- Competitive programming
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- Comprehensive tutorials
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- Practice problems
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## YouTube Channels
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1. [Back To Back SWE](https://www.youtube.com/channel/UCmJz2DV1a3yfgrR7GqRtUUA)
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- Detailed explanations
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- Visual presentations
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- Interview preparation
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2. [Abdul Bari](https://www.youtube.com/channel/UCZCFT11CWBi3MHNlGf019nw)
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- Algorithm explanations
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- Mathematical approach
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- Theoretical foundation
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|
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## Practice Platforms
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1. [AtCoder](https://atcoder.jp/)
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- Regular contests
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- Various difficulty levels
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- Active community
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2. [SPOJ](https://www.spoj.com/)
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- Classical problems
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- Judge system
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- Multiple languages
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