Article by Ayman Alheraki on January 11 2026 10:36 AM
Yes, this is extremely important advice for every programmer who has not yet studied artificial intelligence (AI). AI is no longer just a specialized field limited to researchers or scientists; it has become a fundamental part of programming and everyday life. In recent years, AI has dominated the technological landscape and has permeated almost all areas of programming, from application development to data analysis, and even non-traditional fields like medicine, agriculture, and finance.
Significant Impact on All Programming Fields
AI is no longer limited to specific applications. It is now present in:
App development: such as recommendations on Netflix or Amazon.
Mobile apps: like image or voice recognition.
Gaming: such as enhancing player experiences using machine learning algorithms.
Web development: like improving search engines (SEO) using natural language processing (NLP) models.
Increased Demand in the Job Market
AI and machine learning skills are among the most in-demand skills in the job market. Major companies like Google, Microsoft, and Amazon are looking for programmers with knowledge of these technologies.
Even if you work in a field not directly related to AI, understanding its basics can make you more competitive.
Rapid Technological Advancements
AI is evolving at an incredible pace. If you don’t keep up with this progress, you risk falling behind.
Technologies like ChatGPT, deep learning, and computer vision have become part of our daily lives.
Practical Applications in Everyday Life
AI is everywhere around us: from self-driving cars to voice assistants like Siri and Alexa, and even in improving user experiences on social media platforms.
Data Science and AI Are Two Sides of the Same Coin
If you work in data science, AI is the natural next step. Understanding how to build and apply machine learning models to data will make your work more effective.
Learn the Basics First
Start by understanding fundamental concepts such as:
What is AI, and how is it different from machine learning?
What are the types of machine learning (supervised, unsupervised, and reinforcement learning)?
What are the basic algorithms like linear regression and neural networks?
Learn a Suitable Programming Language
Python is the most popular language in AI due to its powerful libraries, such as:
TensorFlow and PyTorch for deep learning.
Scikit-learn for traditional machine learning.
Pandas and NumPy for data processing.
Learn Basic Mathematics
AI heavily relies on mathematics, especially:
Linear algebra.
Probability and statistics.
Calculus.
Start with Simple Projects
Applying what you learn in practical projects is the best way to understand AI. Start with simple projects like:
Image classification using machine learning algorithms.
Building a price prediction model.
Sentiment analysis of texts.
Use Free and Paid Learning Resources
There are many resources available for learning AI, such as:
Courses on platforms like Coursera, edX, and Udemy.
YouTube channels like "3Blue1Brown" for visual explanations of mathematical concepts.
Books like "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow."
AI might seem complex at first, especially if you’re new to the field. But the key is to start with small steps and apply what you learn in practical projects. Over time, you’ll gain experience and confidence, and you’ll find that AI is not only an exciting field but also a powerful tool that can enhance your programming skills and open new doors in your career.
Learning AI is no longer optional—it’s a necessity for every programmer, especially as it permeates all areas of life and technology. Whether you’re a computer programmer or a data expert, mastering AI will give you a significant competitive edge and expand your professional horizons. Start now, and don’t wait!