Created by Management Study Guide | Last updated 7/2019
Duration: 49m | 1 sections | 13 lectures | Video: 1280x720, 44 KHz | 575 MB
Genre: eLearning | Language: English + Sub
John McCarthy organised the Dartmouth Conference, at which the term 'Artificial Intelligence' was first adopted.
What you'll learn
History of Artificial Intelligence
What is Artificial Intelligence?
Application of Artificial Intelligence
Artificial Intelligence - Intelligent Systems
Problems in Artificial Intelligence
Approaches used in Artificial Intelligence
Tools used in Artificial Intelligence
Different types of Artificial Intelligence Technology
Agents and Environments in Artificial Intelligence
Artificial Intelligence Expert Systems
Artificial Intelligence - Robotics
What is strong and weak Artificial Intelligence?
Requirements
No prior knowledge is required
Description
A well designed course for students, IT professionals and those working in networking department. The course covers both basics and advanced concepts in Artificial Intelligence. During the Second World War, noted British computer scientist Alan Turing worked to crack the 'Enigma' code which was used by German forces to send messages securely. Alan Turing and his team created the Bombe machine that was used to decipher Enigma's messages.
The Enigma and Bombe Machines laid the foundations for Machine Learning. According to Turing, a machine that could converse with humans without the humans knowing that it is a machine would win the "imitation game" and could be said to be "intelligent". In 1956, American computer scientist John McCarthy organised the Dartmouth Conference, at which the term 'Artificial Intelligence' was first adopted. Research centres popped up across the United States to explore the potential of AI. Researchers Allen Newell and Herbert Simon were instrumental in promoting AI as a field of computer science that could transform the world.
In the 1960s, researchers emphasized developing algorithms to solve mathematical problems and geometrical theorems. In the late 1960s, computer scientists worked on Machine Vision Learning and developing machine learning in robots. WABOT-1, the first 'intelligent' humanoid robot, was built in Japan in 1972.
Some AI funding dried up when the dotcom bubble burst in the early 2000s. Yet machine learning continued its march, largely thanks to improvements in computer hardware. Corporations and governments successfully used machine learning methods in narrow domains. Exponential gains in computer processing power and storage ability allowed companies to store vast, and crunch, vast quantities of data for the first time. In the past 15 years, Amazon, Google, Baidu, and others leveraged machine learning to their huge commercial advantage.
Who this course is for:
IT Professionals
Students
Networking professionals
Software engineers
Homepage
https://www.udemy.com/course/artificial-intelligence-e/
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