https://github.com/josephakaro/30-days_of_algorithms

Creating a structured 30-day challenge to learn data structures and algorithms is a fantastic idea! Checkout the README.md for in-depth guideline.
https://github.com/josephakaro/30-days_of_algorithms

30-days-of-code 30daysofcode algorithm algorithms algorithms-and-data-structures data-structures python python3

Last synced: 22 days ago
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Creating a structured 30-day challenge to learn data structures and algorithms is a fantastic idea! Checkout the README.md for in-depth guideline.

• Host: GitHub
• URL: https://github.com/josephakaro/30-days_of_algorithms
• Owner: josephakaro
• License: mit
• Created: 2024-04-15T20:58:33.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-04-16T09:20:05.000Z (10 months ago)
• Last Synced: 2024-11-15T05:28:37.947Z (3 months ago)
• Topics: 30-days-of-code, 30daysofcode, algorithm, algorithms, algorithms-and-data-structures, data-structures, python, python3
• Homepage: https://30daysofcode.josephakaro.tech
• Size: 3.91 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Week 1: Introduction to Data Structures and Algorithms

## `Day 1:` Introduction to Data Structures and Algorithms

    Overview of basic terminology, importance, and applications

## `Day 2:` Arrays and Strings

    Understanding arrays and strings

    Operations, common problems, and their solutions

## `Day 3:` Linked Lists

    Types of linked lists (singly, doubly, circular)

    Implementations and common operationsDay 4: Stacks and Queues

    Understanding stacks and queues

    Implementations, operations, and real-world applications

## `Day 5:` Recursion

    Understanding recursion and recursive algorithms

    Examples and practice problems

## `Day 6:` Time Complexity Analysis

    Big O notation and analyzing algorithmic complexity

    Best, worst, and average-case time complexities

## `Day 7:` Space Complexity Analysis

    Analyzing space complexity of algorithms

    Examples and practice problems

# Week 2: Sorting and Searching Algorithms

## `Day 8:` Bubble Sort and Selection Sort

    Understanding basic sorting algorithms

    Implementations, complexities, and optimizations

## `Day 9:` Insertion Sort and Merge Sort

    Understanding more efficient sorting algorithms

    Implementations, complexities, and comparisons

## `Day 10:` Quick Sort

    Understanding the Quick Sort algorithm

    Partitioning, complexities, and optimizations

## `Day 11:` Heap Sort

    Understanding the Heap Sort algorithm

    Heap data structure, operations, and complexities

## `Day 12:` Binary Search

    Understanding binary search algorithm

    Implementation, complexities, and applications

# Week 3: Advanced Data Structures

## `Day 13:` Trees

    Introduction to tree data structure

    Binary trees, binary search trees, and their operations

## `Day 14:` AVL Trees

    Understanding balanced binary search trees

    Rotations, insertions, and deletions

## `Day 15:` Graphs

    Introduction to graph data structure

    Representations, traversals, and common algorithms

## `Day 16:` Graph Algorithms

    Depth-first search (DFS) and Breadth-first search (BFS)

    Shortest path algorithms (Dijkstra's, Bellman-Ford)

## `Day 17:` Hash Tables

    Understanding hash tables and hash functions

    Implementations, collisions, and handling

## `Day 18:` Trie

    Introduction to trie data structure

    Insertions, deletions, and search operations

## `Day 19:` Segment Trees

    Understanding segment tree data structure

    Construction, queries, and updates

# Week 4: Problem Solving and Practice

## `Day 20-30:` Problem Solving and Practice

    Solve a variety of problems from online platforms like LeetCode, HackerRank, or Codeforces

    Focus on applying learned concepts to solve algorithmic problems

# Recommended Resources:

### Books:

- "Introduction to Algorithms" by Thomas H. Cormen, Charles E. Leiserson, Ronald L.

- Rivest, and Clifford Stein

- "Algorithms" by Robert Sedgewick and Kevin Wayne

- "Cracking the Coding Interview" by Gayle Laakmann McDowell

### Online Courses:

- Coursera: "Algorithms" by Princeton University

- Udemy: "Data Structures and Algorithms: Deep Dive Using Java" by Tim Buchalka

- edX: "Algorithm Design and Analysis" by PennX

### Websites and Platforms:

- LeetCode

- HackerRank

- Codeforces

- GeeksforGeeks

# Documentation and Tutorials:

- GeeksforGeeks: Provides comprehensive tutorials and explanations for various data structures and algorithms.

- Topcoder Algorithm Tutorials: Offers tutorials on advanced algorithms and problem-solving techniques.

- Stack Overflow and various online forums: Great for finding explanations and discussions on specific problems and concepts.