Artificial Intelligence (AI) is a field that, in addition to being in continuous and rapid evolution, is already deeply integrated into our daily lives, revolutionizing various sectors. For anyone who wants to understand the engine of this change, it is essential to understand its mechanisms and learning possibilities. In this article, we will explore how AI works and answer an increasingly common question: is it possible to learn AI on your own?
Artificial intelligence is the ability of a system to exhibit human-like skills such as reasoning, learning, planning, and creativity. An AI system allows a computer to understand its surroundings, interact with what it perceives, and solve problems to achieve a specific goal. Its operation is based on receiving data, which is processed to produce a response.
These systems are able to adapt their behavior by analyzing the effects of previous actions and working autonomously. Advances in computer power, the availability of large amounts of data, and the development of new algorithms have allowed AI to make significant strides in recent years.
Machine learning is a subset of AI that focuses on training algorithms to recognize patterns and make predictions. Deep learning is a subset of machine learning that is distinguished by the use of artificial neural networks. These networks are composed of multiple layers of interconnected “nodes” (artificial neurons), organized in a manner similar to the neural structures of the human brain.
In practice, while a traditional machine learning model might analyze an image by manually identifying specific features (like edges and colors), a deep learning model does so autonomously. Each layer of the neural network analyzes the information received from the previous layer, learning to recognize increasingly complex details. For example, to recognize a face in a photo, the first layer might identify lines and curves, the second layer might combine these lines to form more defined contours and shapes (like eyes or a nose), and the subsequent layers might assemble these shapes to recognize the entire face.
Artificial intelligence systems do not all learn in the same way. There are three main approaches, each with its specific characteristics:
AI is now everywhere. Think of voice assistants like Alexa or Siri, which understand commands and respond. Recommendation systems on Netflix or Spotify use AI to suggest content based on your preferences.
But AI is not limited to consumption: it is also revolutionizing the world of work. For example, it is increasingly fundamental for project managers, used to predict risks and automate planning, and for human resources, applied to speed up candidate selection and personalize training paths.
Absolutely yes. Learning AI on your own is possible thanks to the wide availability of online resources. Here are the steps to get started:
Remember that learning AI is a continuous journey that requires patience and perseverance.
AI offers significant advantages, such as the automation of repetitive tasks and the analysis of complex data for more informed decisions. However, it also has limitations: models can be influenced by biases present in training data, and they raise important ethical questions regarding privacy, security, and the impact on employment.
On this topic, Valentino Megale, Program Director of the International Master in Artificial Intelligence at Rome Business School, offers an in-depth perspective:
“AI is more than just a simple tool, and working with this technology—especially in professional settings—requires skills that go beyond traditional technical knowledge. These include negotiation, an understanding of industry-specific language, the ability to grasp ethical and social implications through dedicated frameworks, and strategic process analysis.
Recent developments in AI have drastically lowered the barrier to entry, making its functionalities accessible to a wider and not necessarily technical audience. This has repositioned human-machine interaction to an often purely conversational level, capable of involving relational and emotional aspects as well.
As a result, this technology now has the potential to dismantle traditional team collaboration dynamics, influence our ability to access information and interpret its validity, and even expose us to new paradigms of cybersecurity vulnerability. The necessary AI literacy, therefore, translates into markedly transversal skills, supported by a methodology focused on functional adaptability to keep pace with its future evolutions.”
Valentino Megale
Entrepreneur with 7 years of experience in the digital health sector
To excel in this field, you need solid management skills and a strategic vision. To develop these abilities, the International Master in Artificial Intelligence at Rome Business School provides you with the knowledge and tools needed to turn your vision into reality.
