The world has been progressing fast, and with time, new technologies are being introduced day by day since the invention of the machine called the computer. Computers have played an important role in the evolution of mankind from the stone age to the age of digitization. As it is the modern age of computers, we need to make our children learn and be up to date about various things about computers. These days kids are getting involved in coding, programming, developing, and much more. All these are important basic skills that they learn to be in the long run for a better future. However, have you ever got the idea about where all this starts from? What is the origin of all this? What do computers work on? Well, if yes, then we are here to answer this question. Computers work completely based on **Algorithms**. Do you not know what it is? Then let us find out **what an algorithm is **and why it is important for your children but let us discuss something new first.

## Computational Thinking

To learn **how to write algorithms,** you need first to have an understanding of Computational Thinking. It is defined as the thinking or analysis of the procedures that need to be involved in solving or creating a problem. It is generally a practice that needs to be learned and done to solve a problem. This is an essential thing if you want to learn how to write programming **algorithms**.

**What is an algorithm**?

An **algorithm** is a formula or a basic technique used for solving a problem. It is usually based on several decisions or protocols that need to be appropriately followed. A computer program is also based entirely on **Algorithms** from top to bottom. In mathematics, **algorithms** mean a small procedure that is followed to solve a problem.

**Algorithms** are something that is being used widely in the field of computer science and technology because of their various functions. One such example is the **US Department of Defense algorithm** for encryption and decryption of data for sending over long lines and using them for long military operations.

## How to write an **Algorithm**

To learn **how to make algorithms**, you need to be open-minded while dealing with the problem at hand. This is something that not everyone could do with ease—nothing to worry about as long as you are a good reader. You need to follow the following steps to make **computer algorithms**.

### Step 1: Description of the Problem

The very first thing is to get a description of the **algorithm** you want to write. The description of the problem is the general idea of what the **algorithm** should contain, so make sure you have all the descriptions needed. There are defects in the description, such as incomplete information, miscommunication, and much more. Make sure you have all the essential details about the whole thing before starting the **algorithm**.

### Step 2: Problem Analysis

The aim behind this step is to decide both the beginning and the ending of the problem. This step is to get an idea of what should be done. For this to take place, you need to have a proper description of the problem.

When starting from the beginning, ask yourself the following questions.

- What data do I have?
- What is to be analyzed?
- What data should be used, and what should be left?

For the ending point, you need to consider the following questions. These can help you with the final analysis.

- What will be the end?
- What changes will occur?
- What will be the outcome?

### Step 3: Developing a high-level **Algorithm**.

The final step of writing a proper **algorithm** is to start writing. Start the **algorithm** by writing it in the form of steps. This can be done with a simple notation as "STEP 1". Make the statements clear and do not try to be vague in any sense. Being vague can cause a lot of trouble for you in your **algorithm** as it will affect the whole structure. Try to summarize your **computer algorithms** as much as you can. Make sure it does not seem too wordy or over-stacked with lots of phrases. Keep it simplified as much as you can. As **algorithms** can help you solve many problems, do not worry about what kind of structure it has. Make sure you find all the necessary information from the description and write all the conditions in your **algorithm**.

### Step 4: Reviewing the **Algorithm**

Once you have written your **algorithm** and are satisfied that all the conditions and demands have been met, it's time to give a final touch. Make sure that all the things are mentioned. It does not have any vague presence and follows a standard of writing. Also, double-check that all the data has been appropriately discussed and does not violate any basic arithmetic rules.

With the basic steps learned on how to write an **algorithm**, it is time for us to move on to the next point and learn about the types of **algorithms** that we have.

## Types of **algorithms**

### Brute Force **Algorithm**

A brute force **algorithm** endeavors every one of the odds until a worthy outcome is found. This is the most central and least complex kind of **algorithms**. These kinds of **algorithms** are used to find the ideal or best arrangement as it checks every one of the possible outcomes making it one of the best choices. It is also used to find one of the most agreeable solutions if none is being completely accurate as an outcome. It is one of the best ways to deal with a problem and is often used by data scientists.

### Recursive **Algorithm**

This type of **algorithm** is entirely based on recursion.** **In recursion, a problem is understood by breaking it into subproblems of the same level and working with it again and again till it gets its solution with the help of the original problem. It finds the solution to the original issue and afterward recurs with a more simpler input during every iteration. It is used to handle the problems which could be broken into less complex or more modest problems of the same sort.

### Dynamic Programming **Algorithm**

This kind of **algorithm** is additionally called the remembrance method. This is on the basis that, in this, the contemplation is to store the as of late resolved result to make an effort not to figure it again and again. The Dynamic Programming Algorithm breaks the issue into more unassuming, covering subproblems and taking care of the result later. In straightforward language, we can say that it remembers the past result and uses it to find new results.

### Divide and Conquer **Algorithm**

In the Divide and Conquer **algorithm**, the method handles the issue in two parts; the central part is to break the issue into subproblems of a comparative sort. The second part is to address the more unobtrusive issue independently and, a short time later, add the joined result to make the last reaction to the issue.

### Greedy **Algorithm**

In a greedy **algorithm**, the problem is divided and solved parts by parts. The finding to choose the accompanying job is cultivated because it gives abrupt assistance, and it never considers the alternatives that had been accepted of late.

## Randomized **Algorithm**

In this **algorithm**, a random number is chosen for making decision at least once during computations. The random number is chosen spontaneously and has no selection criteria.

## Backtracking **Algorithm**

In this kind of **algorithm**, the issue is worked out consistently; for instance, it is an **algorithm**ic system for dealing with problems recursively by endeavoring to develop an answer consistently, each piece, thus, taking out those arrangements that disregard to satisfy the states of the circumstance any time of time.

## Characteristics of **Algorithm**

### Specified

An **algorithm** should be specified to its goals, and input and outputs should be cleared. Input precision requires that you get what kind of data, how much and what structure the data should be. Output precision requires that you get what kind of data, how much and what structure the yield ought to be.

### Clear Phrasing

**Algorithms** should decide each progression, and every one of its means ought to be clear in all practices and should direct to just one significance. That is the reason the **algorithm** should be unambiguous. Portions of each progression should be in a like manner and clarified. It should contain everything quantitative and not emotional.

### Autonomous

An **algorithm** ought to have bit-by-bit headings, which ought to be free of any programming code. It ought to be with the ultimate objective that it might be an abrupt spike sought after for any programming vernaculars.

### Plausible

The **algorithm** ought to be viable, which infers that that load of implies expected to yield should be attainable with the open assets. It should not contain any trivial and abundance propels which could make an **algorithm** ineffective.

### Limit

The **algorithm** should stop in the long run. Halting may infer that you get the typical yield. **Algorithms** should end after a set number of steps. An **algorithm** ought not to be vast and reliably end after a limited number of steps. There is no justification for developing an **algorithm** that is boundless as it will be silly for us.

## Applications of **Algorithms**

There are so many applications of **Algorithms** in our daily lives that it is almost impossible to enlist all of them. Some common applications used in the industries are as follows.

- The web is particularly significant for our everyday life, and we cannot envision our existence without the web, and it is the result of intelligent and inventive
**algorithms**. Various locales on the web can work and misrepresent this enormous number of information just with the assistance of these**algorithms**. - The regular electronic trade exercises are greatly dependent upon our information, for instance, credit or check card numbers, passwords, OTPs, and some more. The middle advancements utilized join public-key cryptographic money and computerized marks, which rely upon numerical
**algorithms**. - Indeed, even an application that needs not bother with algorithm content at the application level relies overwhelmingly upon the algorithm. The application depends upon equipment, GUI, systems administration, or article course. These make considerable utilization of
**algorithms**.

## Why should children learn **Algorithms**?

There are many reasons you should make your children learn to understand what **Algorithms** are and what they are used for. **Algorithms** are utilized in all aspects of software engineering. They structure the field's basic structure. In software engineering, an **algorithm** gives the PC a particular arrangement of directions, which permits the PC to do everything, be it running a mini-computer or running a rocket. PC programs are, at their center, **algorithms** sent in programming dialects that the PC can comprehend. **Algorithms** assume a significant part in how social media functions: which posts appear, which promotions are seen, etc. Algorithms make these choice**s**. Google's software engineers use **algorithms** to advance inquiries, anticipate what clients will type, and then some. A major piece of PC writing computer programs is realizing how to form an algorithm in critical thinking.

Regardless of whether we are not aware of it, we use **algorithms** constantly. Figuring out **how to make algorithms** establishes a solid framework in programming abilities. It helps create consistent deduction abilities past composing PC code—having the option to comprehend and carry out an **algorithm** in code expects understudies to rehearse their organized reasoning and thinking capacities. Since the fundamental advances are not excessively confounded, a large part of crafted by rehashed computation and thought is moved to the PC. That is the worth of an **algorithm** and why they are so helpful in PC programming to separate undertakings into pieces that can be addressed through explicit executions.