🚀 3 Days into My DSA Journey: Brute-Forcing My Way into Better Thinking

Published on May 24, 2025 | 4 min read
By: Piyush Kumar | Portfolio | GitHub

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TL;DR: Starting my Data Structures and Algorithms journey with brute force solutions. Here's what I learned solving Two Sum, Longest Substring, and Palindrome problems in 3 days - plus all my code and key insights for fellow beginners.

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Why I'm Documenting My DSA Journey Publicly

If you're a beginner programmer or computer science student wondering whether to start DSA, this post is for you. I'm sharing my raw, unfiltered experience because:

• 📈 Accountability: Public learning keeps me consistent

• 🤝 Community: Help others avoid my mistakes

• 💡 Growth: Teaching reinforces my own learning

The Reality Check: You don't need to be perfect to start. You just need to start.

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🧠 Day 1: Time Complexity Reality Check - Two Sum Problem

The Problem That Humbled Me

Problem: Two Sum (LeetCode Easy)
My Approach: Brute Force (Nested Loops)
Time Complexity: O(n²)
Space Complexity: O(1)

# My first attempt - brute force
def two_sum_brute_force(nums, target):
    for i in range(len(nums)):
        for j in range(i + 1, len(nums)):
            if nums[i] + nums[j] == target:
                return [i, j]

💡 Key Learnings:

• Big O isn't just theory - it's the language of scalable code

• Nested loops = performance nightmare for large datasets

• Sometimes brute force helps you understand the problem better

What's Next:

• Implement HashMap solution (O(n) time complexity)

• Compare performance with larger datasets

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💡 Day 2: String Manipulation Challenge - Longest Substring

When "Medium" Feels Like "Hard"

Problem: Longest Substring Without Repeating Characters
Difficulty: Medium (felt like Expert 😅)
My Approach: Brute Force with Set
Time Complexity: O(n³)

# Character tracking gets messy fast!
def lengthOfLongestSubstring(str1):
    max_length = 0
    n = len(str1)

    for i in range(n):
        sub1 = []
        for j in range(i, n):
            if str1[j] not in sub1:
                sub1.append(str1[j])
            else:
                break
        max_length = max(max_length, len(sub1))  

    return max_length

🎯 Breakthrough Moments:

• Character tracking is trickier than it looks

• Sliding window technique exists for a reason (implementing next!)

• Brute force taught me the core challenge before optimization

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🔁 Day 3: Pattern Recognition - Palindrome Validation

Finally, A Win That Felt Good!

Problem: Valid Palindrome
Difficulty: Easy
Approach: Two-Pointer Technique
Time Complexity: O(n)

class Solution:
    def lengthOfLongestSubstring(self, s: str) -> int:
        max_length = 0
        n = len(s)

        for i in range(n):
            sub1 = []
            for j in range(i, n):
                if s[j] not in sub1:
                    sub1.append(s[j])
                else:
                    break 
            max_length = max(max_length, len(sub1))  

        return max_length

🚀 Why This Felt Different:

• Two-pointer technique clicked immediately

• Clean string manipulation made the solution elegant

• First time I felt "this is how algorithms should work"

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📊 My 3-Day Progress Analytics

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🎯 Key Insights for Fellow Beginners

✅ What's Working:

1. Start with brute force - understand the problem first

2. Document everything - your future self will thank you

3. Time complexity awareness - changes how you think about code

4. Consistency > perfection - small daily progress compounds

🚫 What I'm Avoiding:

• Comparing my Day 3 to someone's Day 300

• Skipping the "boring" fundamentals

• Optimizing before understanding

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🔮 What's Coming Next Week

Immediate Goals:

• Optimize existing solutions using better algorithms

• Master sliding window technique for substring problems

• Implement HashMap solutions for O(n) time complexity

• Document daily learnings on Twitter

Learning Resources I'm Using:

• LeetCode for problems

• YouTube for visual explanations

• GitHub for code organization

• This blog for accountability

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🤝 Join My Learning Journey

Are you learning DSA too? Let's grow together!

Connect with me:

• 🐦 Twitter: @CodeWithPiyush - Daily updates

• 💼 LinkedIn: Piyush Kumar - Professional updates

• 💻 GitHub: DSA Problems Repository - All my code

• 🌐 Portfolio: aiwithpiyush.netlify.app - Full projects

How You Can Help:

• ⭐ Star my repo if you find it helpful

• 💬 Share your own DSA journey in the comments

• 🔄 Retweet to help other beginners find this

• 📨 DM me your questions - I'll try to help!

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📚 Recommended for Beginners

If you're just starting:

1. Don't skip Big O notation - it's fundamental

2. Code along, don't just read - muscle memory matters

3. Explain your solution out loud - teaches you to think clearly

4. Join online communities - learning together is faster

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Remember: Every expert was once a beginner. Every pro was once an amateur. Every icon was once an unknown.

The best time to start was yesterday. The second best time is now.

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Found this helpful? Follow my journey and let's master DSA together! Drop a comment below with your own learning experiences.

Tags: #DSA #DataStructures #Algorithms #Programming #Python #LeetCode #TechCareer #CodingJourney #BeginnerFriendly #TechBlog

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About the Author:
I am a passionate developer documenting My journey from beginner to proficient in Data Structures and Algorithms. Follow my daily progress and learn together with the community.