Where To Start

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

    HTML

    1. Create your first web page

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

    Learn HTML

    CSS

    2. 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.

    Learn CSS

    JavaScript

    3. 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 JavaScript

    Backend Development

    Continue your journey with backend technologies and other programming languages:

    Python

    1. Learn a backend language

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

    Learn Python

    SQL

    2. Master databases

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

    Learn SQL

    PHP

    3. Server-side scripting

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

    Learn PHP

    Java

    4. Enterprise development

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

    Learn Java

    C#

    5. Modern application development

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

    Learn C#

    C++

    6. High-performance programming

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

    Learn C++

    AI & Machine Learning

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

    Python

    1. Master Python fundamentals

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

    Learn Python

    AI/ML Basics

    2. Introduction to AI & ML

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

    Learn AI/ML Basics

    Data Science

    3. Data preprocessing

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

    Learn Data Science

    ML Models

    4. Machine learning algorithms

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

    Learn ML Models

    Deep Learning

    5. Neural networks & deep learning

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

    Learn Deep Learning

    Computer Vision & NLP

    6. Advanced AI applications

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

    Learn Computer Vision & NLP

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