The most featured programming languages

The world of technology is constantly evolving, and with it, the programming languages used to build software applications. Among the myriad of programming languages, there is one that stands out as the most dominant and popular language in today's tech industry. This language has a vast community of developers, a vast array of tools and libraries, and is used in a variety of domains, ranging from web development to machine learning.

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Python

What is Python?

Python is a popular programming language. It was created by Guido van Rossum, and released in 1991.

It is used for :

What can Python do?
Why Python?
Good to know
Python Syntax compared to other programming languages

Java

What is Java?

Java is a popular programming language, created in 1995.

It is owned by Oracle, and more than 3 billion devices run Java.

It is used for :

Why Use Java?

C++

What is C++ ?

Why Use C++
Difference between C and C++

C++ was developed as an extension of C, and both languages have almost the same syntax. The main difference between C and C++ is that C++ support classes and objects, while C does not.


HTML & CSS

What is HTML?

What is CSS?

What is an HTML Element?

An HTML element is defined by a start tag, some content, and an end tag.

Web Browsers

The purpose of a web browser (Chrome, Edge, Firefox, Safari) is to read HTML documents and display them correctly.

Why Use CSS?

CSS is used to define styles for your web pages, including the design, layout and variations in display for different devices and screen sizes.


Data Science

What is Data Science?

Data Science is about data gathering, analysis and decision-making.

Data Science is about finding patterns in data, through analysis, and make future predictions.

By using Data Science, companies are able to make:

Where is Data Science Needed?

Data Science is used in many industries in the world today, e.g. banking, consultancy, healthcare, and manufacturing.

Examples of where Data Science is needed:

Data Science can be applied in nearly every part of a business where data is available. Examples are:

How Does a Data Scientist Work?

A Data Scientist requires expertise in several backgrounds:

A Data Scientist must find patterns within the data. Before he/she can find the patterns, he/she must organize the data in a standard format.


Machine Learning

What is Machine Learning?

Machine Learning is making the computer learn from studying data and statistics.

Machine Learning is a step into the direction of artificial intelligence (AI).

Machine Learning is a program that analyses data and learns to predict the outcome.

Data Types

To analyze data, it is important to know what type of data we are dealing with.

We can split the data types into three main categories:

Numerical data are numbers, and can be split into two numerical categories:

Categorical data are values that cannot be measured up against each other. Example: a color value, or any yes/no values.

Ordinal data are like categorical data, but can be measured up against each other. Example: school grades where A is better than B and so on.