# Java Program to Check Whether a Number is Prime or Not

#### In this article, you’ll learn to check whether a number is prime or not. This is done using a for loop and while loop in Java.

A prime number is a number which is divisible by only two numbers: 1 and itself. So, if any number is divisible by any other number, it is not a prime number.

## Example 1: Program to Check Prime Number using a for loop

```
public class Main{
public static void main(String[] args){
int num = 29;
boolean flag = false;
for(int i = 2; i <= num/2; ++i)
{
// condition for nonprime number
if(num % i == 0)
{
flag = true;
break;
}
}
if (!flag)
System.out.println(num + " is a prime number.");
else
System.out.println(num + " is not a prime number.");
}
}
```

**Output**

29 is a prime number.

In the above program, for loop is used to determine if the given number `num` is prime or not.

**Here, note that we are looping from 2 to num/2. It is because a number is not divisible by more than its half.**

Inside the `for`

loop, we check if the number is divisible by any number in the given range `(2...num/2)`

.

- If
`num`is divisible,`flag`is set to`true`

and we break out of the loop. This determines`num`is not a prime number. - If
`num`isn’t divisible by any number,`flag`is false and`num`is a prime number.

## Example 2: Program to Check Prime Number using a while loop

```
public class Main{
public static void main(String[] args){
int num = 33, i = 2;
boolean flag = false;
while(i <= num/2)
{
// condition for nonprime number
if(num % i == 0)
{
flag = true;
break;
}
++i;
}
if (!flag)
System.out.println(num + " is a prime number.");
else
System.out.println(num + " is not a prime number.");
}
}
```

**Output**

33 is not a prime number.

In the above program, while loop is used instead of a for loop. The loop runs until `i <= num/2`

. On each iteration, whether `num` is divisble by `i` is checked and the value of `i` is incremented by 1.

# Python Example for Beginners

## Two Machine Learning Fields

There are two sides to machine learning:

**Practical Machine Learning:**This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.**Theoretical Machine Learning**: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.

**Data Science Resources: Data Science Recipes and Applied Machine Learning Recipes**

**Introduction to Applied Machine Learning & Data Science for Beginners, Business Analysts, Students, Researchers and Freelancers with Python & R Codes @ Western Australian Center for Applied Machine Learning & Data Science (WACAMLDS) !!!**

Latest end-to-end Learn by Coding Recipes in Project-Based Learning:

**Applied Statistics with R for Beginners and Business Professionals**

**Data Science and Machine Learning Projects in Python: Tabular Data Analytics**

**Data Science and Machine Learning Projects in R: Tabular Data Analytics**

**Python Machine Learning & Data Science Recipes: Learn by Coding**

**R Machine Learning & Data Science Recipes: Learn by Coding**

**Comparing Different Machine Learning Algorithms in Python for Classification (FREE)**

Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause.The information presented here could also be found in public knowledge domains.