“Grokking Dynamic Programming Patterns for Coding Interviews” is one of the best tools to help equip you with the knowledge of solving algorithmic problems and arming you with the ability to recognize and solve dynamic programming problems.

Imagine you’re in an interview at a huge tech firm where you’ve always dreamt of working. You’re in the hot seat and this problem is presented to you:

*“Write a function that finds any term in the Fibonacci sequence.”*

On seeing this, a few things will happen; first you’ll wonder what the Fibonacci sequence is if you’ve never seen nor heard about it before.

Perhaps the interviewer is kind enough to explain it to you –

*“The Fibonacci Sequence is a series of numbers starting with 0 and 1 where the value of any term on the series, called a Fibonacci Number, is equal to the sum of the last two terms”*.

You’ll wonder where to begin solving the problem: You know how to write functions in code, but how do you represent the Fibonacci pattern in code?

Questions like this may seem difficult. This is why coding interviews have been rumoured to be daunting and difficult to ace.

This is where dynamic programming is very helpful, and Educative.io’s intuitively titled course “Grokking Dynamic Programming Patterns for Coding Interviews” is one of the best tools to help equip you with the knowledge of solving algorithmic problems and arming you with the ability to recognize the patterns in these problems while teaching you the steps to solve them correctly.

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**What is “Grokking Dynamic Programming Patterns for Coding Interviews”?.**

The word “Grokking” is an English word that means to “understand (something) intuitively or by empathy.”

Therefore, “Grokking Dynamic Programming Patterns for Coding Interviews” is an online course designed to mirror the standing of developers as novices and equip them with the different techniques necessary for recognizing and solving dynamic programming problems often asked in dynamic programming interviews, such as the Fibonacci Sequence mentioned above.

But what exactly is dynamic programming all about?

**What is Dynamic Programming?**

How would you feel if you were asked to repeatedly solve an equation for which you already have an answer?

It is needless to repeat it. That will be a waste of time and mental resources, using the previous result would be much quicker. Unless you don’t remember what the result is, in which case you’re bound to repeat it.

A popular aphorism goes thus,

“Those who cannot remember the past are doomed to repeat it”,

That’s what Dynamic Programming is about, To *always* remember answers to the problems or sub-problems you’ve already solved.

According to Educative.io, Dynamic Programming (DP) is an algorithmic technique for solving an optimization problem by breaking it down into simpler sub-problems and utilizing the fact that the optimal solution to the overall problem depends upon the optimal solution to its sub-problems.

In simple terms, Dynamic programming is a method of solving problems where a complex problem is split into simpler problems, which are then solved. The solutions of all the simpler problems or sub-problems are used to solve the complex problem.

Dynamic programming is usually employed in cases where it is possible to split a problem into smaller problems, which are all quite similar.

### How Grokking Dynamic Programming Patterns for Coding Interviews helps.

DP problems may seem hard at first and strike fear in one’s heart, except one is trained to recognize the patterns in these problems and equipped with the right techniques to solve them.

This is where the course “Grokking Dynamic Programming Patterns for Coding Interviews” proves a valuable resource.

For example, here’s the solution to the Fibonacci problem, a common dynamic programming problem explained in detail as outlined in the course:

“Let’s take the example of the **Fibonacci numbers**. As we all know, Fibonacci numbers are a series of numbers in which each number is the sum of the two preceding numbers. The first few Fibonacci numbers are 0, 1, 1, 2, 3, 5, and 8, and they continue on from there.

If we are asked to calculate the nth Fibonacci number, we can do that with the following equation.

Fib(n) = Fib(n-1) + Fib(n-2), for n > 1

As we can clearly see here, to solve the overall problem (i.e. Fib(n)), we broke it down into two smaller sub-problems,

(which are Fib(n-1) and Fib(n-2)). This shows that we can use DP to solve this problem.

Below is the solution written in JavaScript:

```
const calculateFibonacci = function(n) {
const memoize = [];
function fib(n) {
if (n < 2) return n;
// if we have already solved this subproblem, simply return the result from the cache
if (memoize[n]) return memoize[n];
memoize[n] = fib(n - 1) + fib(n - 2);
return memoize[n];
}
return fib(n);
};
console.log(`5th Fibonacci is ---> ${calculateFibonacci(5)}`);
//result is 5
console.log(`6th Fibonacci is ---> ${calculateFibonacci(6)}`);
//result is 8
console.log(`7th Fibonacci is ---> ${calculateFibonacci(7)}`);
//result is 13
```

**A closer look at “Grokking Dynamic Programming Patterns For Coding Interviews**“

As you read in the first paragraph, Grokking Dynamic Programming Patterns For Coding Interviews is a dynamic programming course that comes to your aid when you are nervous about taking an interview to land your dream tech job.

**Lesson Structure**

The 38 lessons in the course are meticulously structured to reflect your standing as a novice and help you ease into the make-believe complex world of dynamic programming – taking you from basic level to mastery.

Every chapter is designed with an objective to leave you prepared for the next, up until you attain mastery. The course is uniquely text-based, the reason for this is that programming videos are *“…holding you back. The average video tutorial is spoken at 150 words per minute, while you can read at 250. That’s why the courses are text-based*.

There are about 28 challenges within the course to help you polish your skills. The course presents a hands-on learning approach with coding environments that require no setup. No SDKs (software development kits), no IDEs, because “*you don’t get better at swimming by watching others. Coding is no different. Practice as you learn with live code environments inside your browser.”*

### What language is the course presented in?

In this dynamic programming course, solutions are not only implemented in Javascript. The same solution is represented in Python, Java and C++ as well, which makes the course suitable for any developer with some knowledge of these languages.

The course is filled with several illustrations to help you visualize the problem before attempting to code it out. *“Rather than just having you try to memorize solutions, you’ll be walked through five underlying DP patterns that can then be applied to solve 35+ DP problems*“.

In each pattern, the course presents a recursive or non-dynamic approach to solve the problem, which is the best way to start solving a DP problem. *“Once we have a recursive solution, we’ll then apply the advanced DP methods of Memoization and Tabulation.”*

The practice problems in this course were carefully chosen, covering the most frequently asked DP questions in dynamic programming interviews.

**Who the course is for.**

“Grokking Dynamic Programming Patterns for Coding interviews” is designed for :

- Developers who want to pass their coding interviews with ease,
- Teachers who are seeking excellent material to teach dynamic programming to students, and
- Tech companies who are looking for an excellent resource to set up test questions for dynamic programming interviews.

### Conclusion

“Grokking Dynamic Programming Patterns for Coding interviews” is the best fit for any developer or teacher who wants to learn or teaching dynamic programming concepts.

A lot of success stories have been recorded from the time this course was first put out, which is enough to convince anyone that it is worth the time and resources invested in taking the course.