Welcome to the Data Structures and Algorithms (DSA) course! This repository is designed to guide you through the essential concepts and implementations of data structures and algorithms in a practical, hands-on manner. Whether you are preparing for coding interviews or simply looking to strengthen your understanding of computer science fundamentals, this course will provide you with the tools you need to succeed.
This course covers the following key topics:
- Overview of Data Structures and Algorithms
- Time and Space Complexity: Big O Notation
- Algorithm Analysis Techniques
- Arrays
- Linked Lists (Singly, Doubly,Circular, DoubleCircular)
- Stacks
- Queues
- Hash Tables
- Trees (Binary Trees, Binary Search Trees, AVL Trees, Heaps)
- Graphs (Graph Representations, Traversal Algorithms)
- Tries
- Sorting Algorithms (Quick Sort, Merge Sort, Bubble Sort, etc.)
- Searching Algorithms (Binary Search, Linear Search)
- Graph Algorithms (Dijkstra, BFS, DFS, etc.)
- Dynamic Programming
- Greedy Algorithms
- Divide and Conquer
- Coding Interview Problems
- Real-life problem-solving with DSA
- Competitive Programming Techniques
- Comprehensive Learning: Detailed explanations and practical examples.
- Hands-on Coding: Each concept is accompanied by code implementations in popular programming languages such as Python, Java, and C++.
- Visualizations: Graphical representations of data structures and algorithms for better understanding.
- Real-world Applications: Learn how data structures and algorithms are used in solving real-world problems.
- Interview Focus: Problem-solving techniques and interview questions commonly asked by top tech companies.
- Languages: Python, Java, C++
- Tools: Visual Studio Code, GitHub, Jupyter Notebooks
- Libraries: Matplotlib (for visualizations), Numpy
- Clone the repository to your local machine:
git clone https://github.com/yourusername/dsa-course.git
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