Algorithms and Data Structures Learning Repository

Overview

Greetings! This repository serves as your comprehensive guide to mastering the intricate worlds of algorithms and data structures. Here, you'll embark on a meticulously crafted learning path designed to equip you with the fundamental programming concepts, problem-solving prowess, and efficient data management techniques required for success in the programming domain.

What You'll Learn:

• Programming Fundamentals: Gain a solid foundation in core programming concepts, building blocks for any programming language you choose to tackle.
• Algorithmic Problem Solving: Develop your problem-solving skills with a focus on algorithms, the step-by-step instructions that computers follow to solve problems.
• Data Structure Mastery: Explore various data structures, the organized ways to store and manage data efficiently within your programs.
• Advanced Concepts: As you solidify your knowledge, delve into more advanced topics like Big O Notation, Design Patterns, and potentially explore specific algorithms related to different programming areas.

Delving Deeper:

As you solidify your knowledge base, you'll be prepared to tackle more advanced topics. This includes delving into Big O Notation, a crucial tool for analyzing algorithm performance, and exploring the fascinating world of Design Patterns – reusable solutions to common software design problems. Additionally, the curriculum may encompass specific algorithms relevant to diverse programming domains, further expanding your skillset.

Structured Learning Path:

The learning journey is meticulously organized into difficulty levels: Beginner, Intermediate, Advanced, and Expert. Each level offers a curated list of topics with resources and progress tracking to keep you focused and on track.

A Wealth of Learning Resources

A comprehensive list of trusted learning resources awaits you, featuring highly regarded websites such as Wikipedia, Refactoring Guru, MDN, and GeeksforGeeks. Explore articles, tutorials, and documentations to find the learning materials that best suit your individual preferences.

Learning list:

Simple:

1. Introduction to Algorithms and Problem Solving

   • Only to the extent of introducing the algorithm

   • Introduction to Algorithms - Download

   • Grokking Algorithms - Download

2. Object-Oriented Programming (OOP)

3. Basic Algorithms

4. Introduction of Data Structure

5. String Manipulation and Algorithms

   • PDF Helper - Download

6. Basic Sorting (e.g., Bubble Sort, Selection Sort, Insertion Sort)

• 6/5: Selection Algorithm : A general term for a class of algorithms that aim to find a specific element in a data set, such as the minimum, maximum, or kiloth smallest element. -> It is not necessary to understand by reading this article, but it is good to know

  • Selection-Sort - selection sort is a type of selection algorithm

  • Bubble

  • Insertion

7. Search Algorithm

8. Testing and Debugging Techniques

   • Debug

   • Test

9. Additional Concept - (Not Necessary)

   • Clean Code
     • Book

   • Utils :(It is not related to data structure and algorithm- Most of this part is my own additional learning roadmap)

     • Version Control Systems (VCS): (Git)
     • Command Line Interface (CLI)
     • Continuous Integration/Continuous Delivery (CI/CD)
     • Task Runners: (Gulp, Grunt)
     • API Documentation tools
       • Swagger&OpenAPI
     • Database (Redis,PostgreSQL)
     • Authentication(OAuth)
     • Scaling Databases(DatabaseIndexes)
     • Architectural Patterns(MonolithicApp-Microservices-SQA)
     • MessageBrokers(RabbitMQ||Kafka)
     • Containerization: (Docker, Kubernetes)
     • SearchEngines(Elasticsearch)
     • WebServers(Nginx || Apache)
     • RealTimeData(WebSockets)
     • GraphQl
     • Bug Tracking Systems: (Jira, Bugzilla)
     • Building for Scale()
   • Finally - > Challenges >> challenge coding and implementing concepts

Medium:

10. Data Structures

11. Big O Notation

12. Software Engineering Principles

13. Additional Data Structures (e.g., Linked Lists, Stacks, Queues, Hash Tables)

14. Dynamic Programming

15. Software Design Patterns

16. Performance Analysis of Presentations and Objects

17. Real-world Case Studies

18. Graph Algorithms (e.g., Graphs, Dijkstra's Algorithm)

Advanced:

19. Performance Analysis of Presentations and Objects

20. Advanced Data Structures (e.g., Binary Search Trees, Tree Navigation)

21. Advanced Sorting Algorithms (e.g., Merge Sort, Quick Sort)

22. Concurrent Programming and Parallel Algorithms

23. Additional Topics (e.g., Binary Pyramids, Problem-Solving Patterns)

24. Graph Preview

25. Binary Pyramids

26. Problem solving approach

27. Bubble Sort

28. Selective Sorting

29. Insertion Sort

30. Comparison of Bubble and Selection and Insertion Sort

31. Merge Sort

32. Quick Sort

33. Basic Sort

34. Linked and One-way Lists

35. Two-way Linked Lists

36. Stacks and Queues

37. Binary Search Trees

38. Tree Navigation

39. Binary Pyramids

40. Hash Tables

41. Graphs

42. Graph Preview

43. Dijkstra's Algorithm

44. Optimization Algorithms

45. Advanced Software Design Patterns

46. Quantum Computing Concepts

47. Parallel Computing Techniques

48. Familiarity with Advanced Graph Algorithms

49. Advanced Graph Algorithms (e.g., Minimum Spanning Trees, Network Flow Algorithms)

50. Machine Learning Basics

More Advanced:

1. Artificial Intelligence

2. Parallel Computing Models (e.g., SIMD, MIMD)

3. Distributed Systems and Algorithms

4. Machine Learning Algorithms and Techniques

5. Natural Language Processing (NLP) Algorithms

6. Evolutionary Algorithms and Genetic Programming

7. Computational Complexity Theory

8. Cryptography and Cryptanalysis Algorithms

Learning Resources

Sites with ⭐ represent the most used

• wikipedia(⭐)
• refactoring (⭐)
• MDN
• GeeksforGeeks(⭐)
• educative
• stackify
• press.rebus.community
• enjoyalgorithms
• scoutapm
• stackoverflow
• medium(⭐)
• linkedin
• altcademy
• digitalocean
• boardinfinity
• baeldung
• dev.to(⭐)
• tutorialspoint
• freecodecamp
• techopedia
• programiz
• javatpoint
• tricentis
• maze
• browserstack ⭐
• techtarget ⭐

Project

Attention : Projects and solution of different algorithms or design patterns are solved in this organization

Organization

String Manipulation and Algorithms

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Design Pattern

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Organizations

• Algorithmic Solutions solution of all kinds of algorithms
• Testing implement all types of tests and test techniques

Collaboration and Feedback

I welcome collaboration and feedback from the community! Feel free to open issues or pull requests with suggestions, corrections, or questions.

Documentation and Notes

I'll be keeping detailed documentation and notes on each topic as I study them. This will serve as a valuable reference for future review and reinforcement of concepts.

Reflection and Updates

I'll periodically reflect on my learning progress and update this README with any insights, challenges, or breakthroughs I've experienced along the way.