Where to Start Coding

New to coding? A clear, beginner-friendly guide to choosing your first programming language and starting the right way.

To become a web developer, start with the subjects below, in the following order:

Backend Development

Continue your journey with backend technologies and other programming languages:

AI & Machine Learning

Dive into artificial intelligence and machine learning to build intelligent applications:

Or Explore Every Course

Not sure which path fits? Browse all courses and start anywhere:

Create your first web page

The first thing you have to learn, is HTML, which is the standard markup language for creating web pages.

Style your web page

The next step is to learn CSS, to set the layout of your web page with beautiful colors, fonts, and much more.

Make your web page interactive

After studying HTML and CSS, you should learn JavaScript to create dynamic and interactive web pages for your users.

Learn a backend language

Start with Python, a versatile language perfect for backend development, data science, and AI applications.

Master databases

Learn SQL to store, retrieve, and manage data efficiently for your backend applications.

Server-side scripting

Learn PHP for server-side scripting to create dynamic web applications and APIs.

Enterprise development

Master Java for building scalable enterprise applications and Android mobile apps.

Modern application development

Learn C# for game development with Unity and building powerful .NET applications.

High-performance programming

Advanced programming with C++ for high-performance applications and systems programming.

Master Python fundamentals

Python is the foundation for AI and machine learning. Master the basics before diving into AI libraries and frameworks.

Introduction to AI & ML

Learn the fundamentals of artificial intelligence and machine learning, including key concepts, algorithms, and applications.

Data preprocessing

Learn to clean, transform, and prepare data for machine learning models using Python libraries like Pandas and NumPy.

Machine learning algorithms

Master supervised and unsupervised learning algorithms including regression, classification, and clustering techniques.

Neural networks & deep learning

Dive into neural networks, deep learning architectures, and frameworks like TensorFlow and PyTorch.

Advanced AI applications

Learn advanced AI applications including computer vision, natural language processing, and transformers.