In this video, we solve the Climbing Stairs problem (LeetCode 70) using Dynamic Programming in Python, starting from a brute force recursive approach and gradually optimizing it step by step.
🔹 Problem Link:
https://leetcode.com/problems/climbing-stairs/description/?envType=problem-list-v2&envId=dynamic-programming
Docs Link:
https://docs.google.com/document/d/1J3BEjjyFDhzWqtBynwqaVrDdCp2wK2EWGK7VKoVoMAQ/edit?usp=sharing
This video is part of my Dynamic Programming YouTube Series, where I explain DP problems using the Leap of Faith approach, helping you build a strong DP mindset instead of memorizing solutions.
🔹 What you will learn in this video:
Understanding the Climbing Stairs problem statement
Identifying overlapping subproblems
Recursive solution (Beginner friendly)
Why recursion fails (Time Limit Exceeded)
Top-Down DP using Memoization
Bottom-Up DP using Tabulation
Space Optimized DP solution
🔹 Why this video is important:
Perfect for DP beginners
Asked frequently in coding interviews
Helps you transition from recursion to DP
Builds foundation for advanced DP problems
🔹 Who should watch this:
Beginners learning Dynamic Programming
Python programmers
LeetCode problem solvers
Students preparing for FAANG / Product-based companies
Anyone struggling to understand DP intuition
Dynamic Programming
Climbing Stairs DP
Climbing Stairs Python
LeetCode 70
DP for Beginners
Recursion to DP
Memoization DP
Tabulation DP
Python Dynamic Programming
DP Interview Questions
LeetCode DP Series
Climbing Stairs Explanation
Leap of Faith DP
