30 Days of Problem Solving Excellence
Welcome to Your Coding Journey!
Embark on a transformative 30-day coding challenge designed to enhance your problem-solving skills, algorithmic thinking, and programming proficiency. Each day presents a carefully curated problem that builds upon previous concepts while introducing new challenges.
This comprehensive guide covers fundamental data structures, algorithms, and programming patterns that are essential for technical interviews and competitive programming.
📊 Problem Categories
Arrays, Strings, Linked Lists, Trees, Graphs, Dynamic Programming, Sorting, Searching, and Mathematical Problems
⏱️ Time Commitment
30-60 minutes per day for 30 days. Each problem includes detailed explanations and multiple solution approaches
🎯 Skill Level
Beginner to Advanced – Problems are carefully ordered from basic concepts to complex algorithmic challenges
Your Progress Journey
Track your daily progress and build momentum with consistent practice
Week 1: Building Strong Foundations
Master the basics of arrays, strings, and fundamental algorithms
1
Two Sum Problem
Easy
Find two numbers in an array that add up to a target sum.
Example:
Input: nums = [2,7,11,15], target = 9Output: [0,1] (because nums[0] + nums[1] = 2 + 7 = 9)
2
7
11
15
Target: 9 → Found: 2 + 7 = 9
Time Complexity
O(n)
Space Complexity
O(n)
2
Reverse String
Easy
Reverse a string in-place using two pointers technique.
Example:
Input: [“h”,”e”,”l”,”l”,”o”]Output: [“o”,”l”,”l”,”e”,”h”]
def reverseString(s):
left, right = 0, len(s) – 1
while left < right:
s[left], s[right] = s[right], s[left]
left += 1
right -= 1
3
Palindrome Check
Easy
Determine if a given string is a palindrome, ignoring spaces and case.
Example:
Input: “A man a plan a canal Panama”Output: true
4
Maximum Subarray
Medium
Find the contiguous subarray with the maximum sum using Kadane’s Algorithm.
Example:
Input: [-2,1,-3,4,-1,2,1,-5,4]Output: 6 (subarray [4,-1,2,1])
5
Move Zeros
Easy
Move all zeros to the end while maintaining relative order of non-zero elements.
Example:
Input: [0,1,0,3,12]Output: [1,3,12,0,0]
6
Best Time to Buy Stock
Easy
Find the maximum profit from buying and selling stock once.
Example:
Input: [7,1,5,3,6,4]Output: 5 (buy at 1, sell at 6)
7
Contains Duplicate
Easy
Check if an array contains any duplicate values.
Example:
Input: [1,2,3,1]Output: true
Week 2: Exploring Data Structures
Dive into linked lists, stacks, queues, and hash tables
8
Valid Parentheses
Easy
Check if parentheses, brackets, and braces are properly balanced using a stack.
Example:
Input: “([{}])”Output: true
9
Merge Two Sorted Lists
Easy
Merge two sorted linked lists into one sorted list.
Example:
Input: 1→2→4, 1→3→4Output: 1→1→2→3→4→4
10
Remove Duplicates
Easy
Remove duplicates from a sorted array in-place.
Example:
Input: [1,1,2]Output: [1,2] (length = 2)
11
Implement Queue using Stacks
Easy
Create a queue data structure using two stacks.
class MyQueue:
def __init__(self):
self.stack1 = []
self.stack2 = []
def push(self, x):
self.stack1.append(x)
12
First Unique Character
Easy
Find the first non-repeating character in a string.
Example:
Input: “leetcode”Output: 0 (character ‘l’)
13
Reverse Linked List
Easy
Reverse a singly linked list iteratively and recursively.
Example:
Input: 1→2→3→4→5Output: 5→4→3→2→1
14
Intersection of Two Arrays
Easy
Find the intersection of two arrays using hash sets.
Example:
Input: nums1 = [1,2,2,1], nums2 = [2,2]Output: [2]
Week 3: Mastering Algorithms
Sorting, searching, and advanced algorithmic techniques
15
Binary Search
Easy
Implement binary search algorithm for finding target in sorted array.
Time Complexity
O(log n)
Space Complexity
O(1)
16
Merge Sort Implementation
Medium
Implement merge sort algorithm with divide and conquer approach.
Example:
Input: [38,27,43,3,9,82,10]Output: [3,9,10,27,38,43,82]
17
Find Peak Element
Medium
Find a peak element in an array using binary search approach.
Example:
Input: [1,2,3,1]Output: 2 (index of peak element 3)
18
Quick Sort
Medium
Implement quicksort with pivot partitioning.
def quicksort(arr, low, high):
if low < high:
pi = partition(arr, low, high)
quicksort(arr, low, pi - 1)
quicksort(arr, pi + 1, high)
19
Search in Rotated Array
Medium
Search for target in a rotated sorted array.
Example:
Input: nums = [4,5,6,7,0,1,2], target = 0Output: 4
20
Valid Anagram
Easy
Check if two strings are anagrams using character frequency.
Example:
Input: s = “anagram”, t = “nagaram”Output: true
21
Top K Frequent Elements
Medium
Find k most frequent elements using heap or bucket sort.
Example:
Input: nums = [1,1,1,2,2,3], k = 2Output: [1,2]
Week 4: Advanced Problem Solving
Trees, graphs, dynamic programming, and complex algorithms
22
Binary Tree Inorder
Medium
Traverse binary tree in inorder (left, root, right) pattern.
Example:
Tree: [1,null,2,3]Output: [1,3,2]
23
Maximum Depth of Tree
Easy
Find the maximum depth of a binary tree using recursion.
def maxDepth(root):
if not root:
return 0
return 1 + max(maxDepth(root.left),
maxDepth(root.right))
24
Symmetric Tree
Easy
Check if a binary tree is symmetric around its center.
Example:
Tree: [1,2,2,3,4,4,3]Output: true
25
Path Sum
Easy
Determine if tree has root-to-leaf path with given sum.
Example:
Tree: [5,4,8,11,null,13,4,7,2,null,null,null,1]Target: 22, Output: true
26
Climbing Stairs
Easy
Count ways to climb n stairs (1 or 2 steps at a time) using dynamic programming.
Example:
Input: n = 3Output: 3 (ways: 1+1+1, 1+2, 2+1)
27
House Robber
Medium
Rob houses to maximize money without robbing adjacent houses using DP.
Example:
Input: [1,2,3,1]Output: 4 (rob house 0 and 2: 1 + 3 = 4)
28
Fibonacci Number
Easy
Calculate nth Fibonacci number using dynamic programming optimization.
Example:
Input: n = 4Output: 3 (sequence: 0,1,1,2,3)
def fibonacci(n):
if n <= 1:
return n
a, b = 0, 1
for i in range(2, n + 1):
a, b = b, a + b
return b
29
Longest Common Subsequence
Medium
Find length of longest common subsequence between two strings using 2D DP.
Example:
Input: text1 = “abcde”, text2 = “ace”Output: 3 (LCS is “ace”)
Time Complexity
O(m×n)
Space Complexity
O(m×n)
30
Number of Islands
Medium
Count number of islands in a 2D grid using DFS/BFS traversal.
Example:
Input: grid = [[“1″,”1″,”0″,”0″,”0”],[“1″,”1″,”0″,”0″,”0”],[“0″,”0″,”1″,”0″,”0”],[“0″,”0″,”0″,”1″,”1”]]Output: 3
Grid Visualization:
1 1 0 0 0
1 1 0 0 0
0 0 1 0 0
0 0 0 1 1
1 1 0 0 0
0 0 1 0 0
0 0 0 1 1
Islands found: 3 (connected components of 1s)
💡 Pro Tips for Success
🎯 Focus on Understanding: Don’t just memorize solutions. Understand the underlying patterns and algorithms. Each problem teaches valuable problem-solving techniques.
📝 Practice Regularly: Consistency is key. Dedicate 30-60 minutes daily to coding practice. Regular practice builds muscle memory and improves pattern recognition.
🔄 Review and Optimize: After solving a problem, review your solution. Can you optimize time or space complexity? Are there alternative approaches?
🤝 Learn from Others: Study different solution approaches. Multiple perspectives help you understand various problem-solving strategies.
⏰ Time Management: Practice solving problems within time constraints. This builds confidence for technical interviews and competitive programming.
🧠 Think Out Loud: Verbalize your thought process. This helps in interviews and improves your problem-solving communication skills.
📈 Progress Tracking & Next Steps
Monitor your growth and plan your continued learning journey
✓
Week 1 Complete
Skills Gained: Array manipulation, string processing, basic algorithms, two-pointer techniques
Key Achievements:
• Mastered fundamental array operations• Learned efficient string manipulation
• Implemented sliding window techniques
• Understood time/space complexity analysis
✓
Week 2 Complete
Skills Gained: Stack operations, queue implementation, linked list manipulation, hash table usage
Key Achievements:
• Implemented stack-based solutions• Mastered linked list operations
• Used hash tables for optimization
• Solved bracket matching problems
✓
Week 3 Complete
Skills Gained: Binary search, sorting algorithms, divide and conquer, frequency analysis
Key Achievements:
• Implemented efficient search algorithms• Mastered sorting techniques
• Applied divide and conquer strategy
• Optimized solutions using heaps
✓
Week 4 Complete
Skills Gained: Tree traversal, dynamic programming, graph algorithms, advanced problem solving
Key Achievements:
• Mastered tree data structures• Implemented dynamic programming
• Solved graph traversal problems
• Developed advanced algorithmic thinking
🎖️ Difficulty Progression Analysis
Understanding the learning curve and skill development
Easy Problems
16
Foundation building problems focusing on basic concepts and simple implementations
Medium Problems
12
Intermediate challenges requiring algorithm optimization and advanced data structures
Hard Problems
2
Complex algorithmic challenges requiring advanced problem-solving skills
Difficulty Distribution
Easy (53%)
Medium (40%)
Hard (7%)
🚀 Beyond the 30-Day Challenge
📚 Advanced Topics to Explore: After completing this challenge, consider diving deeper into advanced algorithms like Union-Find, Segment Trees, Trie data structures, and advanced graph algorithms.
🏆 Competitive Programming: Join platforms like Codeforces, AtCoder, or TopCoder to participate in competitive programming contests and solve more challenging problems.
💼 Interview Preparation: Practice system design questions, behavioral interviews, and company-specific problem patterns to prepare for technical interviews.
🔄 Continuous Learning: Set up a routine to solve 1-2 problems daily. Consistency in practice is more valuable than intensive but irregular sessions.
👥 Community Engagement: Join coding communities, participate in discussions, and help others. Teaching concepts to others reinforces your own understanding.
🎯 Congratulations on Your Journey!
You’ve embarked on a comprehensive 30-day coding challenge that covers essential algorithms and data structures. Each problem is carefully designed to build upon previous concepts while introducing new challenges.
Remember: The key to success in programming is consistent practice, understanding underlying concepts, and never stopping your curiosity to learn. This challenge is just the beginning of your coding excellence journey!
Keep coding, keep learning, and keep growing! 🚀
