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152 lines
4.3 KiB
Markdown
152 lines
4.3 KiB
Markdown
# 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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