Algorithms & Data Structures (LeetCode Preparation)
Master algorithmic problem-solving with a comprehensive, beginner-friendly guide that takes you from fundamentals to advanced techniques. This section is specifically designed for LeetCode preparation and technical interview success, with a carefully structured learning path that builds knowledge progressively.
Learning Objectives
By the end of this section, you will be able to:
- Analyze complexity: Understand and analyze time and space complexity using Big O notation
- Solve systematically: Apply structured problem-solving strategies to break down complex problems
- Master fundamentals: Implement and manipulate core data structures (arrays, strings, trees, graphs)
- Apply advanced techniques: Use dynamic programming, greedy algorithms, and backtracking effectively
- Optimize solutions: Recognize patterns and choose optimal algorithms for different problem types
- Prepare for interviews: Develop confidence in technical interviews through systematic practice
Learning Path
Prerequisites
- Basic programming knowledge in any language (Python, Java, C++, JavaScript)
- Understanding of basic programming concepts (variables, loops, conditionals, functions)
- Familiarity with basic data types (integers, strings, arrays)
- Mathematical foundation (basic algebra and logic)
What's in scope
- Fundamentals: Time/space complexity analysis, basic data structures, and essential programming techniques
- Core Topics: Arrays & strings, hash tables & sets, linked lists, stacks & queues, trees & binary trees, and graphs
- Advanced Algorithms: Dynamic programming, greedy algorithms, backtracking, and binary search
- Specialized Areas: Bit manipulation, mathematical algorithms, advanced data structures, and string algorithms
- Real-world Applications: System design for algorithms and problem-solving strategies for interviews
How to use this section
- Beginners: Start with Problem-Solving Strategies to learn the methodology, then proceed to Fundamentals & Prerequisites and follow the learning path sequentially
- Intermediate: Jump to specific topics like Dynamic Programming or Graphs based on your needs
- Interview Prep: Focus on Problem-Solving Strategies for methodology and practice with the categorized problems
- Advanced: Explore Advanced Data Structures and System Design for Algorithms
"The best way to learn algorithms is to understand the patterns, not memorize solutions. Focus on the 'why' behind each technique, and the 'how' will follow naturally." — Donald Knuth
🗃️ Problem-Solving Strategies
3 items
🗃️ Fundamentals & Prerequisites
3 items
🗃️ Arrays & Strings
4 items
🗃️ Hash Tables & Sets
2 items
🗃️ Linked Lists
2 items
🗃️ Stacks & Queues
3 items
🗃️ Trees & Binary Trees
3 items
🗃️ Heaps & Priority Queues
2 items
🗃️ Graphs
3 items
🗃️ Dynamic Programming
4 items
🗃️ Greedy Algorithms
3 items
🗃️ Backtracking
3 items
🗃️ Binary Search
2 items
🗃️ Sorting & Searching
2 items
🗃️ Bit Manipulation
2 items
🗃️ Math & Number Theory
2 items
🗃️ Advanced Data Structures
4 items
🗃️ String Algorithms
2 items
🗃️ Geometry & Computational Geometry
2 items
🗃️ System Design for Algorithms
2 items