[Y] Palindrome Detection: Write a program to determine whether a given string is a palindrome (reads the same backward as forward).
[Y] Anagram Detection: Determine if two given strings are anagrams of each other.
[Y] Factorial Calculation: Write a function to calculate the factorial of a number both iteratively and recursively.
[Y] Fibonacci Sequence: Generate the Fibonacci sequence up to a specified number, either using recursion or iteration.
[Y] Prime Number Generation: Write a program to generate a list of prime numbers up to a given limit.
[Yna] Sorting Algorithms: Implement and compare various sorting algorithms like Bubble Sort, Quick Sort, Merge Sort, and Insertion Sort.
Binary Search: Implement a binary search algorithm to find an element in a sorted array.
Linked List Operations: Create a linked list data structure and perform common operations like insertion, deletion, and reversing.
Stack and Queue Implementation: Implement a stack and a queue using arrays or linked lists, and perform basic operations on them.
Tree Traversal: Write code to traverse a binary tree in-order, pre-order, and post-order.
Graph Algorithms: Implement common graph algorithms like Depth-First Search (DFS) and Breadth-First Search (BFS).
Dynamic Programming: Solve classic dynamic programming problems like the Fibonacci sequence, coin change problem, and knapsack problem.
String Manipulation: Write code to perform string operations like string reversal, substring search, and character counting.
Matrix Operations: Implement matrix multiplication, transpose, and other basic matrix operations.
Recursion Practice: Solve problems that require recursive solutions, such as computing the Tower of Hanoi or solving the N-Queens problem.
Regular Expressions: Write regular expressions to match and extract specific patterns from text data.
File I/O: Create programs to read and write data to files, perform data processing, and analyze data.
Web Scraping: Write scripts to extract information from websites using libraries like BeautifulSoup or Scrapy (Python).
API Integration: Develop applications that interact with external APIs, such as weather data, social media, or mapping services.
Database Operations: Perform database operations like creating tables, inserting data, querying data, and updating records.
Concurrency and Multithreading: Solve problems related to parallel programming, synchronization, and managing threads in a multithreaded environment.
Networking: Create programs that involve socket programming, network communication, and building client-server applications.
Data Structures: Implement data structures like hash tables, heaps, AVL trees, and more, and perform operations on them.
Machine Learning and AI Problems: If you're interested in machine learning and AI, tackle problems like image classification, text generation, or sentiment analysis.
Divide and Conquer - Merge Sort: Implement the Merge Sort algorithm using the divide and conquer approach to sort an array.
Divide and Conquer - Binary Search in a Rotated Array: Find an element in a rotated sorted array using a modified binary search algorithm.
Divide and Conquer - Closest Pair of Points: Given a set of points in a 2D plane, find the closest pair of points.
Dynamic Programming - Longest Common Subsequence: Find the longest common subsequence of two strings using dynamic programming.
Dynamic Programming - Longest Increasing Subsequence: Determine the longest increasing subsequence in an array.
Dynamic Programming - Matrix Chain Multiplication: Find the optimal way to multiply a series of matrices to minimize the number of scalar multiplications.
Dynamic Programming - Edit Distance (Levenshtein Distance): Calculate the minimum number of edits (insertions, deletions, substitutions) required to convert one string into another.
Knapsack Problem - 0/1 Knapsack: Solve the classic 0/1 knapsack problem, where you need to select a combination of items to maximize their total value without exceeding a weight limit.
Knapsack Problem - Fractional Knapsack: Solve the fractional knapsack problem, where you can take fractions of items to maximize their total value within a weight limit.
Coin Change Problem: Find the number of ways to make change for a given amount using a set of coin denominations.
Topological Sort: Implement a topological sort algorithm for directed acyclic graphs (DAGs).
Shortest Path Algorithms: Implement algorithms like Dijkstra's or Bellman-Ford to find the shortest paths in a weighted graph.
Maximum Subarray Sum: Find the contiguous subarray with the largest sum within an array, known as the Kadane's algorithm.
Backtracking - N-Queens Problem: Place N queens on an N×N chessboard so that no two queens attack each other.
Backtracking - Sudoku Solver: Create a program that solves Sudoku puzzles using backtracking.