In computer science, artificial intelligence (AI), also referred to as machine intelligence, is the intelligence exhibited by machines, not at all like the normal intelligence demonstrated by humans and animals.
Leading AI textbooks characterize the field as the study of “intelligent agents”: any gadget that perceives its surroundings and performs actions that amplify its chance of effectively accomplishing its objectives.
Casually, the term “artificial intelligence” is frequently used to portray machines (or computers) that impersonate “intellectual” works that humans associate with the human psyche, for example, “learning” and “critical thinking”.
The conventional issues (or objectives) of AI research includes reasoning, knowledge representation, natural language processing, planning, learning, perception and the capacity to move and control objects.
General intelligence is among the field’s drawn out objectives. Approaches include computational intelligence, statistical methods, and traditional symbolic AI. Numerous tools are utilized in AI, including forms of search and mathematical optimization, methods based on statistics, artificial neural networks, probability and economics. The AI field draws upon computer science, information engineering, linguistics, psychology, philosophy, mathematics, and many other fields
In this crash course, we’ll be taking you through the various aspects of Artificial Intelligence like:
- What is AI?
- How AI Works
- Examples of AI
- Benefits & Risks of AI
- AI Examples
- Advantages & Disadvantages of AI
- Application of AI per Industry
- Artificial Intelligence Projects
- AI Terminologies
