Primarily artificial intelligence can be defined as the theory and development of computer systems that are able to perform tasks generally acquiring human intelligence, such as visual perception, speech recognition, decision-making and considering many other aspects of humans. In other words, it is the creation of a machine that reacts and works like humans.
Artificial intelligence can be further subdivided into three categories, that are analytical, human-inspired and humanized artificial intelligence. Analytical AI uses cognitive intelligence which is learning based that learns from past experiences and then provide with the best possible result for future decisions. Human-inspired characterizes the emotional intelligence in addition to cognitive intelligence i.e it understands and studies human emotion and considering such factors makes a decision. Humanized artificial intelligence characterizes the combination of cognitive, emotional and social intelligence which is gaining self-conscious and well aware of any situation before taking any decision.
Why artificial intelligence?
As a beginner artificial intelligence may seem to be exactly like a science fiction movie like we have seen what an iron man is capable of. But the reality is we come across artificial intelligence in our everyday lives. The best example of AI can be seen as phone assistants like Siri and Google now, and also some games like chess where humans compete with a system or even more sophisticated games.
Taking up an artificial intelligence course will open up a new world of opportunities in front of you and getting a good hand to it can help you invent new machines that are still believed to be only in movies.
Artificial intelligence is being practiced from decades now, and it has revealed a great new world who is looking for a safe career in artificial intelligence. According to several surveys done by various firms and organizations, AI is attracting more and more aspirants with incredible salary packages, a wide range of vacancies. It has been also notified that the number of AI professionals throughout the world is not enough to fill all the job vacancies. The artificial intelligence market was valued at USD 16.06 billion in 2017 and is expected to touch the height of USD 190.61 billion by 2025.
According to the Gartner report, Artificial intelligence is going to pave the way to 2.3 million opportunities by 2020. So that’s absolute sounds great if you are looking for a career in AI or still confused to take up an artificial intelligence course.
Now let’s move onto the things that we are going to learn taking up an artificial intelligence course.
Learn intelligent system
Intelligence is composed of reasoning, learning, problem-solving, perception, linguistic intelligence. Intelligence is the ability of a system to calculate, reason, retrieve information, learn from past experiences, solve problems comprehend complex ideas and most importantly adapt to new situations. The composition of Intelligence can be divided into various areas like reasoning characterizes judgment, decision making, and prediction, learning consists of motor learning, observational learning, perceptual learning, etc. Linguistic intelligence is an ability to read and write the verbal and written languages.
Learn machine learning algorithms
Machine learning is an application of artificial intelligence the provides the ability to automatically learn and improve from past experiences. It can be categorized as direct instructions or instructions in order to look find patterns and make a better decision in the future. The basic motive is to make computers to learn by themselves without any interventions of humans.
Machine learning algorithms are often characterized by supervised or unsupervised, such as:
- Supervised machine learning algorithms learn from past events and facts and predict future events. First the machine studies from a given set of data, and produces a function to make predictions about the best possible output values. The algorithm can also compare its output with the correct ones, and find errors or modify the obtained output values.
- Unsupervised machine learning algorithms on the other hand when the information is not exactly labeled. Unsupervised algorithms learn from hidden data without knowing the right output but it explores the whole new structure from unlabeled data.
- Semi-supervised machine learning algorithms is a combination of both supervised and unsupervised learning as they have both labeled and unlabeled dataset – basically a small amount of labeled data and a huge amount of unlabeled data. These algorithms tend to learn accurately as systems can compare their outputs as well as finds their whole new way of getting to an output.
- Reinforcement machine learning algorithms deal with learning the behavior of its environment by discovering actions and producing error patterns. This algorithm allows a system or machine to determine the actual behavior and also notify in case of any erroneous behavior to maximize its performance.
Machine learning enables an analysis of the huge amount of information and delivers accurate, faster results in order to identify profitable opportunities or dangerous risks. It is capable to train itself depending on new circumstances or situations to provide more effective performance.
Agents and environments
An agent could be anything capable of making decisions like a person, firm, machine or software. It carries out an action with the best outcome after considering the past and current percepts. An artificial intelligence system is generally composed of agents and its environment. An agent perceives its environment through sensors and acts upon that environment through actuators.
Many of you are well aware of robotics, it is a branch of Artificial intelligence which is composed of mechanical engineering, electrical engineering and computer science for designing, construction, and application of robots. Robots are expected to have a mechanical construction, form or shape designed particularly to accomplish a specific task. The power and control of the robots are electrical components, and it also consists of a computer program to determine what, when and how a robot does something.
There are many more exciting features to learn in artificial intelligence courses such as fuzzy logic systems, neural networks, natural language processing, etc.
Basic requirements to learn artificial intelligence involves three main things. First, deep knowledge in any programming languages (Python is widely accepted as the best language for artificial intelligence). Second, sound in math and logic like algorithms and third domain knowledge of the problem you are solving.