Algorithms and Data Structures Learning Repository

Overview

Welcome to my learning repository! This repository is dedicated to my journey of mastering difficult and complex concepts in JavaScript, programming, algorithms, and data structures. Below is a curated list of topics I plan to cover along with resources and progress tracking.

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)

   • Beginner:

     • Class

     • Object

     • Encapsulation

     • Inheritance

     • Polymorphism

     • Abstraction

     • Association, Aggregation, and Composition

     • DynamicBinding

     • MessagePassing

     • Modularity

     • Cohesion And Coupling

     • Interfaces And Abstract Classes

     • Static And Instance Members

   • Medium:

     • Overriding And Overloading

     • Constructors And Destructors

     • Getter And Setter

     • Access Modifiers

     • Dependency Injection

     • Object-Oriented-Design-Patterns

       • Introduction Design Patterns
       • Design Patterns : Elements of Reusable Object-Oriented Software

3. Basic Algorithms

4. Introduction of Data Structure

5. String Manipulation and Algorithms

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

7. Search Algorithm

8. Testing and Debugging Techniques

9. Pseudo codes

Medium:

10. Data Structures

11. Big O Notation

12. Software Engineering Principles

13. Coding Challenges

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

15. Dynamic Programming

16. Software Design Patterns

17. Performance Analysis of Presentations and Objects

18. Real-world Case Studies

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

Advanced:

20. Performance Analysis of Presentations and Objects

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

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

23. Concurrent Programming and Parallel Algorithms

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

25. Graph Preview

26. Binary Pyramids

27. Problem solving approach

28. Bubble Sort

29. Selective Sorting

30. Insertion Sort

31. Comparison of Bubble and Selection and Insertion Sort

32. Merge Sort

33. Quick Sort

34. Basic Sort

35. Linked and One-way Lists

36. Two-way Linked Lists

37. Stacks and Queues

38. Binary Search Trees

39. Tree Navigation

40. Binary Pyramids

41. Hash Tables

42. Graphs

43. Graph Preview

44. Dijkstra's Algorithm

45. Optimization Algorithms

46. Advanced Software Design Patterns

47. Quantum Computing Concepts

48. Parallel Computing Techniques

49. Familiarity with Advanced Graph Algorithms

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

51. 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(⭐)
• MDN
• GeeksforGeeks(⭐)
• educative
• stackify
• press.rebus.community
• enjoyalgorithms
• scoutapm
• coursera
• medium(⭐)
• linkedin
• altcademy
• digitalocean
• boardinfinity
• baeldung
• dev.to(⭐)

Project

1. ...

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.