You are going to learn the basics of artificial intelligence with different concepts
What you'll learn
You are going to learn various concepts of AI
You are going to learn learn the various types models in AI
You are going to learn Architecture of AI
You are going to learn various concepts of comparations of AI
Requirements
You need to have internet to take this course
Description
Artificial intelligence refers to the development of computer systems capable of performing tasks that typically require human intelligence. These tasks include reasoning, learning, problem-solving, understanding language, and perceiving environments. AI encompasses a wide range of techniques and applications, from simple algorithms to complex systems capable of mimicking human cognition.AI can be categorized into two main types: narrow AI and general AI. Narrow AI, or weak AI, is designed to perform specific tasks, such as voice assistants, recommendation algorithms, and self-driving cars. General AI, or strong AI, refers to systems that possess the ability to perform any intellectual task that a human can do, although this level of AI remains theoretical at present. The potential benefits of AI are vast, ranging from healthcare innovations, such as early disease detection, to automating tedious tasks, which can increase productivity and efficiency. However, AI also raises ethical concerns, such as job displacement, privacy violations, and the development of autonomous weapons. The creation of AI systems that are transparent, accountable, and aligned with human values is critical for ensuring that AI is used responsibly.AI represents a transformative technology with the potential to revolutionize industries and improve quality of life. As it continues to evolve, understanding its core principles and societal impact is essential for harnessing its full potential while mitigating associated risks.
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 Comparation Chart
Lecture 3 Various types of models
Lecture 4 Lambda functions
Lecture 5 Architecture of Resources in AI
Lecture 6 RAG basics in AI
Lecture 7 Resources to learn
If you want to learn with detailed examples for every concept, this course will be for you
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