Ace Data Structures and Algorithm in 9 steps

Data structure and Algorithm are crucial but intimidating at the same time. However, with proper routine and practice they can become easier to conquer, so here are a few tips for you to ace the Data Structure and Algorithm
1: Prioritize quality over quantity.

When you thoroughly examine an issue, it means you can:

1. code it rapidly.

2. You can code it with proper syntax, indicating that you are proficient in the language.

3. Because it's second nature to you, you can write clean code in one go.

4. You can rapidly adapt the same code to a different situation.

5. You understand the data structure you're employing and can put it into action if necessary.

To do so, you must concentrate on a few representative problems. After a few attempts, you'll begin to see trends. You also begin to improve your coding skills

You're free to solve as many problems as you like now. And the greatest part is that you won't have to code many of them. Find a solution, and if it's comparable to one of your main problems(which it almost always is), you're done. You don't need to code or debug it because you're already capable of doing it.

2: Concentrate on the most important questions.

Create a list of 100 core problems. Many websites provide you with a list of 100 handpicked problems. Another option is to consult various books.

3: Become an expert on each data structure.

Start with the essentials now that you've completed your list. Every data structure should be understood.

Learn how to use each of your language's data structures.

Learn how to put them into action as well. Interviewers may inquire about the internals of the data structure. Many problems need data structures to be modified or re-engineered for a specific use case. You must understand how they function to effectively utilize them.

List of data structures to master :

· Arrays and Lists

· 2D Arrays

· Strings

· Linked List

· Stack

· Queue

· Hash Table & Hash Set

· Heap

· Graphs

· Binary Tree

· Binary Search Tree

What's the best way to go about it? Assume your core problems are separated by a data structure. When you begin each section, you will be able to master each data structure. Alternatively, you can learn them all at once.

4: Repetition at Regular Intervals

What should you do if you've practiced a lot of questions but have forgotten most of them after a week? So, what are we going to do about it?

The idea is to forget about the solutions. The trick is to put them into practice. When you observe an issue, you should be able to break it down and recreate the answer very instantaneously. This is not the same as rote learning. You're identifying several components, breaking them down, and resolving the issue.

The most effective method we've observed is to solve the problem again in three days. After that, after a week. After that, after a month. You'll be able to do it without thinking.

5: Identify strategies that are often employed.

This is when the Depth-First strategy comes into play. You'll start to discover trends as you answer these puzzles.

Assume you solved five problems using Binary Search. You may practice the Binary Search code by isolating it again and again. You already know it'll be employed in similar situations.

And this is only one of several options available. Here are a few more popular examples:

· Depth First Search

· Recursion + Memoization

· Hash Table + Linked List combination

· Searching a Binary Tree etc.

Now, you have a collection of techniques you can apply to new problems.

6: Expansion

Assume you've mastered your key problems. You're used to working with typical data structures. You may now expand your search outside your core set of skills. You don't even have to code all the new queries because you've already integrated so many ways.

Attempt to tackle actual interview challenges throughout this time. When you grow proficient at anything, you have a propensity to focus on the most difficult difficulties. "If I can solve these incredibly difficult issues, then interview difficulties will be a piece of cake!" the thought process goes. That isn't always the case. Techniques used in really difficult situations frequently have little to do with difficulties at the interview level.

7: Put your skills to the test on paper.

At some point throughout your preparation, we recommend practicing on paper. It gets you out of your comfort zone to develop without an IDE and Stack Overflow.

The following are some of the advantages of practicing on paper:

1. You must design your code before you write it. You can’t just go back and retype.

2. You will begin to understand proper syntax and data structure use. Code is used to write itself while using an IDE.

3. You may practice anyplace with a piece of paper and a pen.

8: Watch others solve questions

We suggest you watch videos where an expert solves questions related to data structures and algorithms. Now how this helps you is that you can understand how a person thinks before solving any question. You will be able to understand how specific types of questions have different types of approaches. Overtime by repeating this procedure of watching others solve problems, you can inculcate different techniques and approaches while solving problems.

9: Watch others solve questions

We suggest you watch videos where an expert solves questions related to data structures and algorithms. Now how this helps you is that you can understand how a person thinks before solving any question. You will be able to understand how specific types of questions have different types of approaches. Over time, by repeating this procedure of watching others solve problems, you can inculcate different techniques and approaches while solving problems.

These are 9 steps you can follow while preparing for Data Structure and Algorithm. Remember the process isn't easy but it's worth the reward.