Module 2: Introduction to AI Algorithms

Artificial intelligence is a filed of IT that deals with the development of machines that can think, make decisions independently of human intervention. With AI algorithms, complex tasks that humans can do can be completed more quickly. However, due to the nature of the work, some AI algorithms or models can complete simple tasks, while others are built to complete more complex tasks. Some models may not require human intervention. The said algorithm or model is the set of instructions in the operations to be performed. In short, at a basic level, an AI algorithm is a set of instructions that tells a computer how to learn to work on its own.

Artificial intelligence and the algorithms that make it up are, of course, complex. This is due to a complex set of rules that give AI algorithms their ability to learn. In fact, it is the algorithms themselves that are referred to as AI. Basically, an AI algorithm receives labeled or unlabeled training data and uses this information to learn. It completes new tasks based on what it learns from this data. Some AI algorithms have been given the ability to learn on their own and process new data to change and improve processes. However, the majority of machine learning algorithms require human intervention to facilitate the process.

There are three main categories of artificial intelligence. These are supervised learning, unsupervised learning and reinforcement learning. The main differences between these categories are how they are trained and how they work.

There are dozens of different algorithms under these categories. We will discuss the most popular and widely used ones from each category and where they are used.