Introduction to Dynamic Programming

Dynamic Programming is a powerful technique used to solve complex problems efficiently. It is an algorithmic paradigm that breaks down a problem into smaller overlapping subproblems and stores the solutions of these subproblems to avoid redundant computations.

The key concept behind dynamic programming is reusing computed solutions to subproblems, which allows for a significant improvement in efficiency.

As a senior engineer with 10 years of programming experience, you are likely familiar with the concept of optimization. Dynamic programming is a form of optimization that aims to find the most effective and elegant solutions to a wide range of problems.

By mastering dynamic programming, you will be able to effectively solve optimization problems commonly encountered in programming interviews. Dynamic programming is frequently used as a problem-solving strategy by product-based businesses to assess the problem-solving abilities of candidates.

In this lesson, we will explore the fundamental principles of dynamic programming, including memoization, top-down and bottom-up approaches, optimal substructure, overlapping subproblems, and common dynamic programming problems. We will also delve into various dynamic programming techniques and analyze the time and space complexity of dynamic programming solutions.

Let's dive into the fascinating world of dynamic programming!